diff --git a/ngraph/frontend/frontend_manager/include/frontend_manager/place.hpp b/ngraph/frontend/frontend_manager/include/frontend_manager/place.hpp
index c81a3a01f58..033bc01a6cb 100644
--- a/ngraph/frontend/frontend_manager/include/frontend_manager/place.hpp
+++ b/ngraph/frontend/frontend_manager/include/frontend_manager/place.hpp
@@ -103,7 +103,7 @@ public:
     ///
     /// \return A vector with all operation node references that consumes data from this
     /// place
-    virtual std::vector<Ptr> get_consuming_operations(const std::string& outputPortName) const;
+    virtual std::vector<Ptr> get_consuming_operations(const std::string& outputName) const;
 
     /// \brief Returns references to all operation nodes that consume data from this place
     /// for specified output port
@@ -127,16 +127,14 @@ public:
     /// \return A tensor place which hold the resulting value for this place
     virtual Ptr get_target_tensor() const;
 
-    /// \brief Returns a tensor place that gets data from this place; applicable for
-    /// operations, output ports and output edges which have only one output port
+    /// \brief Returns a tensor place that gets data from this place; applicable for operations
     ///
     /// \param outputName Name of output port group
     ///
     /// \return A tensor place which hold the resulting value for this place
     virtual Ptr get_target_tensor(const std::string& outputName) const;
 
-    /// \brief Returns a tensor place that gets data from this place; applicable for
-    /// operations, output ports and output edges which have only one output port
+    /// \brief Returns a tensor place that gets data from this place; applicable for operations
     ///
     /// \param outputName Name of output port group, each group can have multiple ports
     ///
@@ -146,8 +144,7 @@ public:
     /// \return A tensor place which hold the resulting value for this place
     virtual Ptr get_target_tensor(const std::string& outputName, int outputPortIndex) const;
 
-    /// \brief Returns a tensor place that gets data from this place; applicable for
-    /// operations, output ports and output edges
+    /// \brief Returns a tensor place that gets data from this place; applicable for operations
     ///
     /// \param output_port_index Output port index if the current place is an operation node
     /// and has multiple output ports
@@ -161,24 +158,21 @@ public:
     /// \return A tensor place which supplies data for this place
     virtual Ptr get_source_tensor() const;
 
-    /// \brief Returns a tensor place that supplies data for this place; applicable for
-    /// operations, input ports and input edges
+    /// \brief Returns a tensor place that supplies data for this place; applicable for operations
     ///
     /// \param input_port_index Input port index for operational nodes.
     ///
     /// \return A tensor place which supplies data for this place
     virtual Ptr get_source_tensor(int input_port_index) const;
 
-    /// \brief Returns a tensor place that supplies data for this place; applicable for
-    /// operations, input ports and input edges
+    /// \brief Returns a tensor place that supplies data for this place; applicable for operations
     ///
     /// \param inputName Name of input port group
     ///
     /// \return A tensor place which supplies data for this place
     virtual Ptr get_source_tensor(const std::string& inputName) const;
 
-    /// \brief Returns a tensor place that supplies data for this place; applicable for
-    /// operations, input ports and input edges
+    /// \brief Returns a tensor place that supplies data for this place; applicable for operations
     ///
     /// \param inputName If a given place is itself an operation node, this specifies name
     /// of output port group, each group can have multiple ports
diff --git a/ngraph/frontend/onnx/frontend/src/edge_mapper.cpp b/ngraph/frontend/onnx/frontend/src/edge_mapper.cpp
index 4c6132dd78e..4602a2db623 100644
--- a/ngraph/frontend/onnx/frontend/src/edge_mapper.cpp
+++ b/ngraph/frontend/onnx/frontend/src/edge_mapper.cpp
@@ -95,37 +95,41 @@ std::vector<int> onnx_editor::EdgeMapper::get_node_input_indexes(int node_index,
 }
 
 InputEdge onnx_editor::EdgeMapper::find_input_edge(const EditorNode& node, const EditorInput& in) const {
-    // identification can be both based on node name and output name
-    const auto& node_indexes = find_node_indexes(node.m_node_name, node.m_output_name);
-    int node_index = -1;
-    if (node_indexes.size() == 1) {
-        node_index = node_indexes[0];
-    } else if (node_indexes.empty()) {
-        throw ngraph_error("Node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
-                           " and output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
-                           " was not found");
-    } else if (!in.m_input_name.empty())  // input indexes are not deterministic if a node name is ambiguous
-    {
-        // many nodes with the same name
-        // check if some of found index matches input name
-        int matched_inputs_number = 0;
-        for (const auto& index : node_indexes) {
-            if (std::count(std::begin(m_node_inputs[index]), std::end(m_node_inputs[index]), in.m_input_name) > 0) {
-                node_index = index;
-                ++matched_inputs_number;
-            }
-        }
-        if (matched_inputs_number == 0) {
-            throw ngraph_error("Input edge described by: " + node.m_node_name + " and input name: " + in.m_input_name +
+    int node_index = node.m_node_index;
+    if (node_index == -1) {  // the node index is not provided
+        // identification can be both based on node name and output name (if the node index is not provided)
+        const auto& node_indexes = find_node_indexes(node.m_node_name, node.m_output_name);
+        if (node_indexes.size() == 1) {
+            node_index = node_indexes[0];
+        } else if (node_indexes.empty()) {
+            throw ngraph_error("Node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
+                               " and output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
                                " was not found");
+        } else if (!in.m_input_name.empty())  // input indexes are not deterministic if a node name is ambiguous
+        {
+            // many nodes with the same name
+            // check if some of found index matches input name
+            int matched_inputs_number = 0;
+            for (const auto& index : node_indexes) {
+                if (std::count(std::begin(m_node_inputs[index]), std::end(m_node_inputs[index]), in.m_input_name) > 0) {
+                    node_index = index;
+                    ++matched_inputs_number;
+                }
+            }
+            if (matched_inputs_number == 0) {
+                throw ngraph_error("Input edge described by: " + node.m_node_name +
+                                   " and input name: " + in.m_input_name + " was not found");
+            }
+            if (matched_inputs_number > 1) {
+                throw ngraph_error("Given node name: " + node.m_node_name + " and input name: " + in.m_input_name +
+                                   " are ambiguous to determine input edge");
+            }
+        } else {
+            throw ngraph_error("Given node name: " + node.m_node_name + " and input index: " +
+                               std::to_string(in.m_input_index) + " are ambiguous to determine input edge");
         }
-        if (matched_inputs_number > 1) {
-            throw ngraph_error("Given node name: " + node.m_node_name + " and input name: " + in.m_input_name +
-                               " are ambiguous to determine input edge");
-        }
-    } else {
-        throw ngraph_error("Given node name: " + node.m_node_name + " and input index: " +
-                           std::to_string(in.m_input_index) + " are ambiguous to determine input edge");
+    } else {  // the node index is provided
+        check_node_index(node_index);
     }
     if (in.m_input_index != -1)  // input index is set
     {
@@ -146,33 +150,38 @@ InputEdge onnx_editor::EdgeMapper::find_input_edge(const EditorNode& node, const
 }
 
 OutputEdge onnx_editor::EdgeMapper::find_output_edge(const EditorNode& node, const EditorOutput& out) const {
-    // identification can be both based on node name and output name
-    const auto& node_indexes = find_node_indexes(node.m_node_name, node.m_output_name);
-    int node_index = -1;
-    if (node_indexes.size() == 1) {
-        node_index = node_indexes[0];
-    } else if (node_indexes.empty()) {
-        throw ngraph_error("Node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
-                           " and output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
-                           " was not found");
-    } else if (!out.m_output_name.empty())  // output indexes are not deterministic if a node name is ambiguous
-    {
-        // many nodes with the same name
-        // check if some of found index matches output name
-        int matched_outputs_number = 0;
-        for (const auto& index : node_indexes) {
-            if (std::count(std::begin(m_node_outputs[index]), std::end(m_node_outputs[index]), out.m_output_name) > 0) {
-                node_index = index;
-                ++matched_outputs_number;
+    int node_index = node_index = node.m_node_index;
+    if (node_index == -1) {  // the node index is not provided
+        // identification can be both based on node name and output name (if the node index is not provided)
+        const auto& node_indexes = find_node_indexes(node.m_node_name, node.m_output_name);
+        if (node_indexes.size() == 1) {
+            node_index = node_indexes[0];
+        } else if (node_indexes.empty()) {
+            throw ngraph_error("Node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
+                               " and output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
+                               " was not found");
+        } else if (!out.m_output_name.empty())  // output indexes are not deterministic if a node name is ambiguous
+        {
+            // many nodes with the same name
+            // check if some of found index matches output name
+            int matched_outputs_number = 0;
+            for (const auto& index : node_indexes) {
+                if (std::count(std::begin(m_node_outputs[index]), std::end(m_node_outputs[index]), out.m_output_name) >
+                    0) {
+                    node_index = index;
+                    ++matched_outputs_number;
+                }
             }
+            if (matched_outputs_number == 0) {
+                throw ngraph_error("Output edge described by: " + node.m_node_name +
+                                   " and output name: " + out.m_output_name + " was not found");
+            }
+        } else {
+            throw ngraph_error("Given node name: " + node.m_node_name + " and output index: " +
+                               std::to_string(out.m_output_index) + " are ambiguous to determine output edge");
         }
-        if (matched_outputs_number == 0) {
-            throw ngraph_error("Output edge described by: " + node.m_node_name +
-                               " and output name: " + out.m_output_name + " was not found");
-        }
-    } else {
-        throw ngraph_error("Given node name: " + node.m_node_name + " and output index: " +
-                           std::to_string(out.m_output_index) + " are ambiguous to determine output edge");
+    } else {  // the node index is provided
+        check_node_index(node_index);
     }
     if (out.m_output_index != -1)  // output index is set
     {
@@ -197,16 +206,45 @@ std::vector<InputEdge> onnx_editor::EdgeMapper::find_output_consumers(const std:
         const auto node_idx = it->second;
         const auto port_indexes = get_node_input_indexes(node_idx, output_name);
         for (const auto& idx : port_indexes) {
-            input_edges.push_back(InputEdge{node_idx, idx});
+            const auto consumer_edge = InputEdge{node_idx, idx};
+            if (std::find_if(std::begin(input_edges), std::end(input_edges), [&consumer_edge](const InputEdge& edge) {
+                    return edge.m_node_idx == consumer_edge.m_node_idx && edge.m_port_idx == consumer_edge.m_port_idx;
+                }) == std::end(input_edges)) {
+                // only unique
+                input_edges.push_back(consumer_edge);
+            }
         }
     }
     return input_edges;
 }
 
 bool onnx_editor::EdgeMapper::is_correct_and_unambiguous_node(const EditorNode& node) const {
+    if (node.m_node_index >= 0 && node.m_node_index < static_cast<int>(m_node_inputs.size())) {
+        return true;
+    }
     return find_node_indexes(node.m_node_name, node.m_output_name).size() == 1;
 }
 
+namespace {
+void check_node(bool condition, const EditorNode& node) {
+    NGRAPH_CHECK(condition,
+                 "The node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
+                     ", output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
+                     ", node_index: " + (node.m_node_index == -1 ? "not_given" : std::to_string(node.m_node_index)) +
+                     " is ambiguous");
+}
+}  // namespace
+
+int onnx_editor::EdgeMapper::get_node_index(const EditorNode& node) const {
+    if (node.m_node_index != -1) {  // the node index provided
+        check_node_index(node.m_node_index);
+        return node.m_node_index;
+    }
+    const auto indexes = find_node_indexes(node.m_node_name, node.m_output_name);
+    check_node(indexes.size() == 1, node);
+    return indexes[0];
+}
+
 bool onnx_editor::EdgeMapper::is_correct_tensor_name(const std::string& name) const {
     if (m_node_output_name_to_index.find(name) != std::end(m_node_output_name_to_index)) {
         return true;
@@ -218,20 +256,25 @@ bool onnx_editor::EdgeMapper::is_correct_tensor_name(const std::string& name) co
 }
 
 std::vector<std::string> onnx_editor::EdgeMapper::get_input_ports(const EditorNode& node) const {
-    NGRAPH_CHECK(is_correct_and_unambiguous_node(node),
-                 "The node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
-                     ", output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
-                     " is ambiguous");
-    const auto node_index = find_node_indexes(node.m_node_name, node.m_output_name)[0];
+    check_node(is_correct_and_unambiguous_node(node), node);
+    auto node_index = node.m_node_index;
+    if (node_index == -1) {  // the node index is provided
+        node_index = find_node_indexes(node.m_node_name, node.m_output_name)[0];
+    } else {
+        check_node_index(node_index);
+    }
     return m_node_inputs[node_index];
 }
 
 std::vector<std::string> onnx_editor::EdgeMapper::get_output_ports(const EditorNode& node) const {
-    NGRAPH_CHECK(is_correct_and_unambiguous_node(node),
-                 "The node with name: " + (node.m_node_name.empty() ? "not_given" : node.m_node_name) +
-                     ", output_name: " + (node.m_output_name.empty() ? "not_given" : node.m_output_name) +
-                     " is ambiguous");
-    const auto node_index = find_node_indexes(node.m_node_name, node.m_output_name)[0];
+    check_node(is_correct_and_unambiguous_node(node), node);
+    auto node_index = node.m_node_index;
+    if (node_index == -1)  // the node index is provided
+    {
+        node_index = find_node_indexes(node.m_node_name, node.m_output_name)[0];
+    } else {
+        check_node_index(node_index);
+    }
     return m_node_outputs[node_index];
 }
 
@@ -250,3 +293,8 @@ std::string onnx_editor::EdgeMapper::get_target_tensor_name(const OutputEdge& ed
     }
     return "";
 }
+
+void onnx_editor::EdgeMapper::check_node_index(int node_index) const {
+    NGRAPH_CHECK(node_index >= 0 && node_index < static_cast<int>(m_node_inputs.size()),
+                 "Provided node index: " + std::to_string(node_index) + " is out of scope");
+}
diff --git a/ngraph/frontend/onnx/frontend/src/edge_mapper.hpp b/ngraph/frontend/onnx/frontend/src/edge_mapper.hpp
index fb16d147ade..d9fe93fcaf0 100644
--- a/ngraph/frontend/onnx/frontend/src/edge_mapper.hpp
+++ b/ngraph/frontend/onnx/frontend/src/edge_mapper.hpp
@@ -92,6 +92,16 @@ public:
     ///
     bool is_correct_and_unambiguous_node(const EditorNode& node) const;
 
+    /// \brief Returns index (position) of provided node in the graph
+    ///        in topological order.
+    ///
+    /// \param node An EditorNode helper structure created based on a node name
+    ///             or a node output name.
+    ///
+    /// \note  The exception will be thrown if the provided node is ambiguous.
+    ///
+    int get_node_index(const EditorNode& node) const;
+
     /// \brief Returns true if a provided tensor name is correct (exists in a graph).
     ///
     /// \param name The name of tensor in a graph.
@@ -130,6 +140,7 @@ private:
     // note: a single node can have more than one inputs with the same name
     std::vector<int> get_node_input_indexes(int node_index, const std::string& input_name) const;
     int get_node_output_idx(int node_index, const std::string& output_name) const;
+    void check_node_index(int node_index) const;
 
     std::vector<std::vector<std::string>> m_node_inputs;
     std::vector<std::vector<std::string>> m_node_outputs;
diff --git a/ngraph/frontend/onnx/frontend/src/editor.cpp b/ngraph/frontend/onnx/frontend/src/editor.cpp
index 6551543d5f1..c2741e68f46 100644
--- a/ngraph/frontend/onnx/frontend/src/editor.cpp
+++ b/ngraph/frontend/onnx/frontend/src/editor.cpp
@@ -444,6 +444,11 @@ bool onnx_editor::ONNXModelEditor::is_correct_and_unambiguous_node(const EditorN
     return m_pimpl->m_edge_mapper.is_correct_and_unambiguous_node(node);
 }
 
+int onnx_editor::ONNXModelEditor::get_node_index(const EditorNode& node) const {
+    update_mapper_if_needed();
+    return m_pimpl->m_edge_mapper.get_node_index(node);
+}
+
 bool onnx_editor::ONNXModelEditor::is_correct_tensor_name(const std::string& name) const {
     update_mapper_if_needed();
     return m_pimpl->m_edge_mapper.is_correct_tensor_name(name);
diff --git a/ngraph/frontend/onnx/frontend/src/editor.hpp b/ngraph/frontend/onnx/frontend/src/editor.hpp
index 66d4d7e5ff0..bfda345efe3 100644
--- a/ngraph/frontend/onnx/frontend/src/editor.hpp
+++ b/ngraph/frontend/onnx/frontend/src/editor.hpp
@@ -198,6 +198,16 @@ public:
     ///
     bool is_correct_and_unambiguous_node(const EditorNode& node) const;
 
+    /// \brief Returns index (position) of provided node in the graph
+    ///        in topological order.
+    ///
+    /// \param node An EditorNode helper structure created based on a node name
+    ///             or a node output name.
+    ///
+    /// \note  The exception will be thrown if the provided node is ambiguous.
+    ///
+    int get_node_index(const EditorNode& node) const;
+
     /// \brief Returns true if a provided tensor name is correct (exists in a graph).
     ///
     /// \param name The name of tensor in a graph.
diff --git a/ngraph/frontend/onnx/frontend/src/editor_types.hpp b/ngraph/frontend/onnx/frontend/src/editor_types.hpp
index 0d3db82f588..febbbb01449 100644
--- a/ngraph/frontend/onnx/frontend/src/editor_types.hpp
+++ b/ngraph/frontend/onnx/frontend/src/editor_types.hpp
@@ -114,11 +114,14 @@ struct EditorOutput {
 ///        You can indicate test_node by name as EditorNode("test_node")
 ///        or by assigned output as EditorNode(EditorOutput("out1"))
 ///        or EditorNode(EditorOutput("out2"))
+///        or you can determine the node by postition of a node in an ONNX graph (in topological order).
 struct EditorNode {
     EditorNode(std::string node_name) : m_node_name{std::move(node_name)} {}
     EditorNode(EditorOutput output) : m_output_name{std::move(output.m_output_name)} {}
+    EditorNode(const int node_index) : m_node_index{node_index} {}
     const std::string m_node_name = "";
     const std::string m_output_name = "";
+    const int m_node_index = -1;
 };
 }  // namespace onnx_editor
 }  // namespace ngraph
diff --git a/ngraph/frontend/onnx/frontend/src/place.cpp b/ngraph/frontend/onnx/frontend/src/place.cpp
index 915b6a401f5..15a6bb74172 100644
--- a/ngraph/frontend/onnx/frontend/src/place.cpp
+++ b/ngraph/frontend/onnx/frontend/src/place.cpp
@@ -47,6 +47,18 @@ Place::Ptr PlaceInputEdgeONNX::get_source_tensor() const {
     return std::make_shared<PlaceTensorONNX>(m_editor->get_source_tensor_name(m_edge), m_editor);
 }
 
+std::vector<Place::Ptr> PlaceInputEdgeONNX::get_consuming_operations() const {
+    return {std::make_shared<PlaceOpONNX>(onnx_editor::EditorNode{m_edge.m_node_idx}, m_editor)};
+}
+
+Place::Ptr PlaceInputEdgeONNX::get_producing_operation() const {
+    return get_source_tensor()->get_producing_operation();
+}
+
+Place::Ptr PlaceInputEdgeONNX::get_producing_port() const {
+    return get_source_tensor()->get_producing_port();
+}
+
 PlaceOutputEdgeONNX::PlaceOutputEdgeONNX(const onnx_editor::OutputEdge& edge,
                                          std::shared_ptr<onnx_editor::ONNXModelEditor> editor)
     : m_edge{edge},
@@ -85,6 +97,18 @@ Place::Ptr PlaceOutputEdgeONNX::get_target_tensor() const {
     return std::make_shared<PlaceTensorONNX>(m_editor->get_target_tensor_name(m_edge), m_editor);
 }
 
+std::vector<Place::Ptr> PlaceOutputEdgeONNX::get_consuming_ports() const {
+    return get_target_tensor()->get_consuming_ports();
+}
+
+Place::Ptr PlaceOutputEdgeONNX::get_producing_operation() const {
+    return std::make_shared<PlaceOpONNX>(onnx_editor::EditorNode{m_edge.m_node_idx}, m_editor);
+}
+
+std::vector<Place::Ptr> PlaceOutputEdgeONNX::get_consuming_operations() const {
+    return get_target_tensor()->get_consuming_operations();
+}
+
 PlaceTensorONNX::PlaceTensorONNX(const std::string& name, std::shared_ptr<onnx_editor::ONNXModelEditor> editor)
     : m_name{name},
       m_editor{std::move(editor)} {}
@@ -112,10 +136,8 @@ std::vector<Place::Ptr> PlaceTensorONNX::get_consuming_ports() const {
     return ret;
 }
 
-Place::Ptr PlaceTensorONNX::get_input_port(int input_port_index) const {
-    return std::make_shared<PlaceInputEdgeONNX>(
-        m_editor->find_input_edge(onnx_editor::EditorOutput(m_name), onnx_editor::EditorInput(input_port_index)),
-        m_editor);
+Place::Ptr PlaceTensorONNX::get_producing_operation() const {
+    return get_producing_port()->get_producing_operation();
 }
 
 bool PlaceTensorONNX::is_input() const {
@@ -146,6 +168,19 @@ bool PlaceTensorONNX::is_equal_data(Place::Ptr another) const {
            eq_to_consuming_port(another);
 }
 
+std::vector<Place::Ptr> PlaceTensorONNX::get_consuming_operations() const {
+    std::vector<Place::Ptr> consuming_ports = get_consuming_ports();
+    std::vector<Place::Ptr> consuming_ops;
+    std::transform(std::begin(consuming_ports),
+                   std::end(consuming_ports),
+                   std::back_inserter(consuming_ops),
+                   [](const Place::Ptr& place) {
+                       return place->get_consuming_operations().at(0);
+                   });
+
+    return consuming_ops;
+}
+
 PlaceOpONNX::PlaceOpONNX(const onnx_editor::EditorNode& node, std::shared_ptr<onnx_editor::ONNXModelEditor> editor)
     : m_node{node},
       m_editor{std::move(editor)} {}
@@ -158,6 +193,10 @@ std::vector<std::string> PlaceOpONNX::get_names() const {
     return {m_node.m_node_name};
 }
 
+onnx_editor::EditorNode PlaceOpONNX::get_editor_node() const {
+    return m_node;
+}
+
 Place::Ptr PlaceOpONNX::get_output_port() const {
     if (m_editor->get_output_ports(m_node).size() == 1) {
         return get_output_port(0);
@@ -209,3 +248,133 @@ Place::Ptr PlaceOpONNX::get_input_port(const std::string& input_name) const {
     }
     return nullptr;
 }
+
+std::vector<Place::Ptr> PlaceOpONNX::get_consuming_ports() const {
+    std::vector<Place::Ptr> consuming_ports;
+    const auto out_ports_size = m_editor->get_output_ports(m_node).size();
+    for (int out_idx = 0; out_idx < out_ports_size; ++out_idx) {
+        auto consuming_ops_out = get_output_port(out_idx)->get_consuming_ports();
+        consuming_ports.insert(consuming_ports.end(), consuming_ops_out.begin(), consuming_ops_out.end());
+    }
+    return consuming_ports;
+}
+
+namespace {
+std::vector<Place::Ptr> get_consuming_ops(std::vector<Place::Ptr> input_ports) {
+    std::vector<Place::Ptr> consuming_ops;
+    std::transform(std::begin(input_ports),
+                   std::end(input_ports),
+                   std::back_inserter(consuming_ops),
+                   [](const Place::Ptr place) {
+                       return place->get_consuming_operations().at(0);
+                   });
+
+    return consuming_ops;
+}
+}  // namespace
+
+std::vector<Place::Ptr> PlaceOpONNX::get_consuming_operations() const {
+    std::vector<Place::Ptr> consuming_ports = get_consuming_ports();
+    return get_consuming_ops(consuming_ports);
+}
+
+std::vector<Place::Ptr> PlaceOpONNX::get_consuming_operations(int output_port_index) const {
+    std::vector<Place::Ptr> consuming_ports = get_output_port(output_port_index)->get_consuming_ports();
+    return get_consuming_ops(consuming_ports);
+}
+
+std::vector<Place::Ptr> PlaceOpONNX::get_consuming_operations(const std::string& output_port_name) const {
+    std::vector<Place::Ptr> consuming_ports = get_output_port(output_port_name)->get_consuming_ports();
+    return get_consuming_ops(consuming_ports);
+}
+
+Place::Ptr PlaceOpONNX::get_producing_operation() const {
+    const auto input_port = get_input_port();
+    if (input_port != nullptr) {
+        return input_port->get_producing_operation();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_producing_operation(int input_port_index) const {
+    const auto input_port = get_input_port(input_port_index);
+    if (input_port != nullptr) {
+        return input_port->get_producing_operation();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_producing_operation(const std::string& input_port_name) const {
+    const auto input_port = get_input_port(input_port_name);
+    if (input_port != nullptr) {
+        return input_port->get_producing_operation();
+    }
+    return nullptr;
+}
+
+bool PlaceOpONNX::is_equal(Place::Ptr another) const {
+    if (const auto place_op = std::dynamic_pointer_cast<PlaceOpONNX>(another)) {
+        const auto& another_node = place_op->get_editor_node();
+        if (m_editor->is_correct_and_unambiguous_node(m_node) ||
+            m_editor->is_correct_and_unambiguous_node(another_node)) {
+            return m_editor->get_node_index(m_node) == m_editor->get_node_index(another_node);
+        }
+    }
+    return false;
+}
+
+Place::Ptr PlaceOpONNX::get_target_tensor() const {
+    const auto output_port = get_output_port();
+    if (output_port != nullptr) {
+        return output_port->get_target_tensor();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_target_tensor(int output_port_index) const {
+    const auto output_port = get_output_port(output_port_index);
+    if (output_port != nullptr) {
+        return output_port->get_target_tensor();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_target_tensor(const std::string& output_name) const {
+    const auto output_port = get_output_port(output_name);
+    if (output_port != nullptr) {
+        return output_port->get_target_tensor();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_source_tensor() const {
+    const auto input_port = get_input_port();
+    if (input_port != nullptr) {
+        return input_port->get_source_tensor();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_source_tensor(int input_port_index) const {
+    const auto input_port = get_input_port(input_port_index);
+    if (input_port != nullptr) {
+        return input_port->get_source_tensor();
+    }
+    return nullptr;
+}
+
+Place::Ptr PlaceOpONNX::get_source_tensor(const std::string& input_name) const {
+    const auto input_port = get_input_port(input_name);
+    if (input_port != nullptr) {
+        return input_port->get_source_tensor();
+    }
+    return nullptr;
+}
+
+bool PlaceOpONNX::is_input() const {
+    return false;
+}
+
+bool PlaceOpONNX::is_output() const {
+    return false;
+}
diff --git a/ngraph/frontend/onnx/frontend/src/place.hpp b/ngraph/frontend/onnx/frontend/src/place.hpp
index efc7e7a8155..82d961998a4 100644
--- a/ngraph/frontend/onnx/frontend/src/place.hpp
+++ b/ngraph/frontend/onnx/frontend/src/place.hpp
@@ -7,6 +7,7 @@
 #include <editor.hpp>
 #include <frontend_manager/place.hpp>
 #include <memory>
+#include <sstream>
 
 namespace ngraph {
 namespace frontend {
@@ -15,17 +16,18 @@ public:
     PlaceInputEdgeONNX(const onnx_editor::InputEdge& edge, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
     PlaceInputEdgeONNX(onnx_editor::InputEdge&& edge, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
 
+    // internal usage
     onnx_editor::InputEdge get_input_edge() const;
 
+    // external usage
     bool is_input() const override;
-
     bool is_output() const override;
-
     bool is_equal(Place::Ptr another) const override;
-
     bool is_equal_data(Place::Ptr another) const override;
-
     Place::Ptr get_source_tensor() const override;
+    std::vector<Place::Ptr> get_consuming_operations() const override;
+    Place::Ptr get_producing_operation() const override;
+    Place::Ptr get_producing_port() const override;
 
 private:
     onnx_editor::InputEdge m_edge;
@@ -37,17 +39,18 @@ public:
     PlaceOutputEdgeONNX(const onnx_editor::OutputEdge& edge, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
     PlaceOutputEdgeONNX(onnx_editor::OutputEdge&& edge, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
 
+    // internal usage
     onnx_editor::OutputEdge get_output_edge() const;
 
+    // external usage
     bool is_input() const override;
-
     bool is_output() const override;
-
     bool is_equal(Place::Ptr another) const override;
-
     bool is_equal_data(Place::Ptr another) const override;
-
     Place::Ptr get_target_tensor() const override;
+    std::vector<Place::Ptr> get_consuming_ports() const override;
+    Place::Ptr get_producing_operation() const override;
+    std::vector<Place::Ptr> get_consuming_operations() const override;
 
 private:
     onnx_editor::OutputEdge m_edge;
@@ -59,21 +62,16 @@ public:
     PlaceTensorONNX(const std::string& name, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
     PlaceTensorONNX(std::string&& name, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
 
+    // external usage
     std::vector<std::string> get_names() const override;
-
     Place::Ptr get_producing_port() const override;
-
     std::vector<Place::Ptr> get_consuming_ports() const override;
-
-    Ptr get_input_port(int input_port_index) const override;
-
+    Place::Ptr get_producing_operation() const override;
     bool is_input() const override;
-
     bool is_output() const override;
-
     bool is_equal(Place::Ptr another) const override;
-
     bool is_equal_data(Place::Ptr another) const override;
+    std::vector<Place::Ptr> get_consuming_operations() const override;
 
 private:
     std::string m_name;
@@ -86,6 +84,10 @@ public:
     PlaceOpONNX(onnx_editor::EditorNode&& node, std::shared_ptr<onnx_editor::ONNXModelEditor> editor);
     std::vector<std::string> get_names() const override;
 
+    // internal usage
+    onnx_editor::EditorNode get_editor_node() const;
+
+    // external usage
     Place::Ptr get_output_port() const override;
     Place::Ptr get_output_port(int output_port_index) const override;
     Place::Ptr get_output_port(const std::string& output_port_name) const override;
@@ -94,6 +96,27 @@ public:
     Place::Ptr get_input_port(int input_port_index) const override;
     Place::Ptr get_input_port(const std::string& input_name) const override;
 
+    std::vector<Place::Ptr> get_consuming_ports() const override;
+    std::vector<Place::Ptr> get_consuming_operations() const override;
+    std::vector<Place::Ptr> get_consuming_operations(int output_port_index) const override;
+    std::vector<Place::Ptr> get_consuming_operations(const std::string& output_port_name) const override;
+
+    Place::Ptr get_producing_operation() const override;
+    Place::Ptr get_producing_operation(int input_port_index) const override;
+    Place::Ptr get_producing_operation(const std::string& input_port_name) const override;
+
+    Place::Place::Ptr get_target_tensor() const override;
+    Place::Ptr get_target_tensor(int output_port_index) const override;
+    Place::Ptr get_target_tensor(const std::string& output_name) const override;
+
+    Place::Place::Ptr get_source_tensor() const override;
+    Place::Ptr get_source_tensor(int input_port_index) const override;
+    Place::Ptr get_source_tensor(const std::string& input_name) const override;
+
+    bool is_equal(Place::Ptr another) const override;
+    bool is_input() const override;
+    bool is_output() const override;
+
 private:
     onnx_editor::EditorNode m_node;
     std::shared_ptr<onnx_editor::ONNXModelEditor> m_editor;
diff --git a/ngraph/test/onnx/onnx_editor.cpp b/ngraph/test/onnx/onnx_editor.cpp
index 96034029677..21c7be215b6 100644
--- a/ngraph/test/onnx/onnx_editor.cpp
+++ b/ngraph/test/onnx/onnx_editor.cpp
@@ -693,6 +693,26 @@ NGRAPH_TEST(onnx_editor, editor_api_select_input_edge_by_node_name_and_input_ind
     EXPECT_EQ(edge2.m_new_input_name, "custom_input_name_2");
 }
 
+NGRAPH_TEST(onnx_editor, editor_api_select_input_edge_by_node_index) {
+    ONNXModelEditor editor{file_util::path_join(SERIALIZED_ZOO, "onnx/model_editor/subgraph_extraction_tests.onnx")};
+
+    const InputEdge edge = editor.find_input_edge(EditorNode{0}, EditorInput{0, "custom_input_name_1"});
+    EXPECT_EQ(edge.m_node_idx, 0);
+    EXPECT_EQ(edge.m_port_idx, 0);
+    EXPECT_EQ(edge.m_new_input_name, "custom_input_name_1");
+
+    const InputEdge edge2 = editor.find_input_edge(EditorNode{5}, EditorInput{0});
+    EXPECT_EQ(edge2.m_node_idx, 5);
+    EXPECT_EQ(edge2.m_port_idx, 0);
+
+    try {
+        editor.find_input_edge(EditorNode{99}, EditorInput{"conv1/7x7_s2_1"});
+    } catch (const std::exception& e) {
+        std::string msg{e.what()};
+        EXPECT_TRUE(msg.find("Provided node index: 99 is out of scope") != std::string::npos);
+    }
+}
+
 NGRAPH_TEST(onnx_editor, editor_api_select_input_edge_empty_node_name) {
     ONNXModelEditor editor{file_util::path_join(SERIALIZED_ZOO, "onnx/model_editor/subgraph_extraction_tests.onnx")};
 
@@ -767,6 +787,21 @@ NGRAPH_TEST(onnx_editor, editor_api_select_output_edge_by_node_name_and_output_i
     EXPECT_EQ(edge2.m_port_idx, 1);
 }
 
+NGRAPH_TEST(onnx_editor, editor_api_select_output_edge_by_node_index) {
+    ONNXModelEditor editor{file_util::path_join(SERIALIZED_ZOO, "onnx/model_editor/subgraph_extraction_tests.onnx")};
+
+    const OutputEdge edge = editor.find_output_edge(EditorNode{5}, EditorOutput{1});
+    EXPECT_EQ(edge.m_node_idx, 5);
+    EXPECT_EQ(edge.m_port_idx, 1);
+
+    try {
+        editor.find_output_edge(EditorNode{99}, EditorOutput{"conv1/7x7_s2_1"});
+    } catch (const std::exception& e) {
+        std::string msg{e.what()};
+        EXPECT_TRUE(msg.find("Provided node index: 99 is out of scope") != std::string::npos);
+    }
+}
+
 NGRAPH_TEST(onnx_editor, editor_api_select_edge_const_network) {
     ONNXModelEditor editor{file_util::path_join(SERIALIZED_ZOO, "onnx/model_editor/subgraph_extraction_tests_2.onnx")};
 
@@ -1044,6 +1079,12 @@ NGRAPH_TEST(onnx_editor, editor_api_is_correct_and_unambiguous_node) {
     is_correct_node = editor.is_correct_and_unambiguous_node(EditorNode{"relu1_name"});
     EXPECT_EQ(is_correct_node, true);
 
+    is_correct_node = editor.is_correct_and_unambiguous_node(EditorNode{2});
+    EXPECT_EQ(is_correct_node, true);
+
+    is_correct_node = editor.is_correct_and_unambiguous_node(EditorNode{99});
+    EXPECT_EQ(is_correct_node, false);
+
     is_correct_node = editor.is_correct_and_unambiguous_node(EditorNode{EditorOutput{"in3"}});
     EXPECT_EQ(is_correct_node, false);
 
@@ -1054,6 +1095,32 @@ NGRAPH_TEST(onnx_editor, editor_api_is_correct_and_unambiguous_node) {
     EXPECT_EQ(is_correct_node, false);
 }
 
+NGRAPH_TEST(onnx_editor, editor_api_get_node_index) {
+    ONNXModelEditor editor{file_util::path_join(SERIALIZED_ZOO, "onnx/model_editor/subgraph_extraction_tests.onnx")};
+
+    EXPECT_EQ(editor.get_node_index(EditorNode{2}), 2);
+    EXPECT_EQ(editor.get_node_index(EditorNode{EditorOutput{"relu1"}}), 0);
+    EXPECT_EQ(editor.get_node_index(EditorNode{EditorOutput{"split2"}}), 5);
+    EXPECT_EQ(editor.get_node_index(EditorNode{"relu1_name"}), 0);
+
+    try {
+        editor.get_node_index(EditorNode{99});
+    } catch (const std::exception& e) {
+        std::string msg{e.what()};
+        EXPECT_TRUE(msg.find("Provided node index: 99 is out of scope") != std::string::npos);
+    }
+
+    try {
+        editor.get_node_index(EditorNode{"add_ambiguous_name"});
+    } catch (const std::exception& e) {
+        std::string msg{e.what()};
+        EXPECT_TRUE(
+            msg.find(
+                "The node with name: add_ambiguous_name, output_name: not_given, node_index: not_given is ambiguous") !=
+            std::string::npos);
+    }
+}
+
 NGRAPH_TEST(onnx_editor, editor_api_input_edge_from_tensor_with_single_consumer) {
     ONNXModelEditor editor{file_util::path_join(SERIALIZED_ZOO, "onnx/model_editor/add_ab.onnx")};
 
@@ -1365,15 +1432,18 @@ NGRAPH_TEST(onnx_editor, get_input_ports) {
         editor.get_input_ports(EditorNode{"add_ambiguous_name"});
     } catch (const std::exception& e) {
         std::string msg{e.what()};
-        EXPECT_TRUE(msg.find("The node with name: add_ambiguous_name, output_name: not_given is ambiguous") !=
-                    std::string::npos);
+        EXPECT_TRUE(
+            msg.find(
+                "The node with name: add_ambiguous_name, output_name: not_given, node_index: not_given is ambiguous") !=
+            std::string::npos);
     }
     try {
         editor.get_input_ports(EditorNode{""});
     } catch (const std::exception& e) {
         std::string msg{e.what()};
-        EXPECT_TRUE(msg.find("The node with name: not_given, output_name: not_given is ambiguous") !=
-                    std::string::npos);
+        EXPECT_TRUE(
+            msg.find("The node with name: not_given, output_name: not_given, node_index: not_given is ambiguous") !=
+            std::string::npos);
     }
 }
 NGRAPH_TEST(onnx_editor, get_output_ports) {
@@ -1393,14 +1463,17 @@ NGRAPH_TEST(onnx_editor, get_output_ports) {
         editor.get_output_ports(EditorNode{"add_ambiguous_name"});
     } catch (const std::exception& e) {
         std::string msg{e.what()};
-        EXPECT_TRUE(msg.find("The node with name: add_ambiguous_name, output_name: not_given is ambiguous") !=
-                    std::string::npos);
+        EXPECT_TRUE(
+            msg.find(
+                "The node with name: add_ambiguous_name, output_name: not_given, node_index: not_given is ambiguous") !=
+            std::string::npos);
     }
     try {
         editor.get_output_ports(EditorNode{""});
     } catch (const std::exception& e) {
         std::string msg{e.what()};
-        EXPECT_TRUE(msg.find("The node with name: not_given, output_name: not_given is ambiguous") !=
-                    std::string::npos);
+        EXPECT_TRUE(
+            msg.find("The node with name: not_given, output_name: not_given, node_index: not_given is ambiguous") !=
+            std::string::npos);
     }
 }
diff --git a/runtime/bindings/python/src/compatibility/pyngraph/frontend/place.cpp b/runtime/bindings/python/src/compatibility/pyngraph/frontend/place.cpp
index 79c88a76bf5..60bf74528ab 100644
--- a/runtime/bindings/python/src/compatibility/pyngraph/frontend/place.cpp
+++ b/runtime/bindings/python/src/compatibility/pyngraph/frontend/place.cpp
@@ -89,13 +89,23 @@ void regclass_pyngraph_Place(py::module m) {
 
     place.def(
         "get_consuming_operations",
-        [](const ngraph::frontend::Place& self, py::object outputPortIndex) {
-            if (outputPortIndex == py::none()) {
-                return self.get_consuming_operations();
+        [](const ngraph::frontend::Place& self, py::object outputName, py::object outputPortIndex) {
+            if (outputName == py::none()) {
+                if (outputPortIndex == py::none()) {
+                    return self.get_consuming_operations();
+                } else {
+                    return self.get_consuming_operations(py::cast<int>(outputPortIndex));
+                }
             } else {
-                return self.get_consuming_operations(py::cast<int>(outputPortIndex));
+                if (outputPortIndex == py::none()) {
+                    return self.get_consuming_operations(py::cast<std::string>(outputName));
+                } else {
+                    return self.get_consuming_operations(py::cast<std::string>(outputName),
+                                                         py::cast<int>(outputPortIndex));
+                }
             }
         },
+        py::arg("outputName") = py::none(),
         py::arg("outputPortIndex") = py::none(),
         R"(
                 Returns references to all operation nodes that consume data from this place for specified output port.
@@ -103,6 +113,8 @@ void regclass_pyngraph_Place(py::module m) {
 
                 Parameters
                 ----------
+                outputName : str
+                    Name of output port group. May not be set if node has one output port group.
                 outputPortIndex : int
                     If place is an operational node it specifies which output port should be considered
                     May not be set if node has only one output port.
@@ -115,13 +127,22 @@ void regclass_pyngraph_Place(py::module m) {
 
     place.def(
         "get_target_tensor",
-        [](const ngraph::frontend::Place& self, py::object outputPortIndex) {
-            if (outputPortIndex == py::none()) {
-                return self.get_target_tensor();
+        [](const ngraph::frontend::Place& self, py::object outputName, py::object outputPortIndex) {
+            if (outputName == py::none()) {
+                if (outputPortIndex == py::none()) {
+                    return self.get_target_tensor();
+                } else {
+                    return self.get_target_tensor(py::cast<int>(outputPortIndex));
+                }
             } else {
-                return self.get_target_tensor(py::cast<int>(outputPortIndex));
+                if (outputPortIndex == py::none()) {
+                    return self.get_target_tensor(py::cast<std::string>(outputName));
+                } else {
+                    return self.get_target_tensor(py::cast<std::string>(outputName), py::cast<int>(outputPortIndex));
+                }
             }
         },
+        py::arg("outputName") = py::none(),
         py::arg("outputPortIndex") = py::none(),
         R"(
                 Returns a tensor place that gets data from this place; applicable for operations,
@@ -129,6 +150,8 @@ void regclass_pyngraph_Place(py::module m) {
 
                 Parameters
                 ----------
+                outputName : str
+                    Name of output port group. May not be set if node has one output port group.
                 outputPortIndex : int
                     Output port index if the current place is an operation node and has multiple output ports.
                     May not be set if place has only one output port.
@@ -141,19 +164,31 @@ void regclass_pyngraph_Place(py::module m) {
 
     place.def(
         "get_producing_operation",
-        [](const ngraph::frontend::Place& self, py::object inputPortIndex) {
-            if (inputPortIndex == py::none()) {
-                return self.get_producing_operation();
+        [](const ngraph::frontend::Place& self, py::object inputName, py::object inputPortIndex) {
+            if (inputName == py::none()) {
+                if (inputPortIndex == py::none()) {
+                    return self.get_producing_operation();
+                } else {
+                    return self.get_producing_operation(py::cast<int>(inputPortIndex));
+                }
             } else {
-                return self.get_producing_operation(py::cast<int>(inputPortIndex));
+                if (inputPortIndex == py::none()) {
+                    return self.get_producing_operation(py::cast<std::string>(inputName));
+                } else {
+                    return self.get_producing_operation(py::cast<std::string>(inputName),
+                                                        py::cast<int>(inputPortIndex));
+                }
             }
         },
+        py::arg("inputName") = py::none(),
         py::arg("inputPortIndex") = py::none(),
         R"(
                 Get an operation node place that immediately produces data for this place.
 
                 Parameters
                 ----------
+                inputName : str
+                    Name of port group. May not be set if node has one input port group.
                 inputPortIndex : int
                     If a given place is itself an operation node, this specifies a port index.
                     May not be set if place has only one input port.
@@ -260,13 +295,22 @@ void regclass_pyngraph_Place(py::module m) {
 
     place.def(
         "get_source_tensor",
-        [](const ngraph::frontend::Place& self, py::object inputPortIndex) {
-            if (inputPortIndex == py::none()) {
-                return self.get_source_tensor();
+        [](const ngraph::frontend::Place& self, py::object inputName, py::object inputPortIndex) {
+            if (inputName == py::none()) {
+                if (inputPortIndex == py::none()) {
+                    return self.get_source_tensor();
+                } else {
+                    return self.get_source_tensor(py::cast<int>(inputPortIndex));
+                }
             } else {
-                return self.get_source_tensor(py::cast<int>(inputPortIndex));
+                if (inputPortIndex == py::none()) {
+                    return self.get_source_tensor(py::cast<std::string>(inputName));
+                } else {
+                    return self.get_source_tensor(py::cast<std::string>(inputName), py::cast<int>(inputPortIndex));
+                }
             }
         },
+        py::arg("inputName") = py::none(),
         py::arg("inputPortIndex") = py::none(),
         R"(
                 Returns a tensor place that supplies data for this place; applicable for operations,
@@ -274,6 +318,8 @@ void regclass_pyngraph_Place(py::module m) {
 
                 Parameters
                 ----------
+                inputName : str
+                    Name of port group. May not be set if node has one input port group.
                 inputPortIndex : int
                     Input port index for operational node. May not be specified if place has only one input port.
 
diff --git a/runtime/bindings/python/tests/mock/mock_py_ngraph_frontend/mock_py_frontend.hpp b/runtime/bindings/python/tests/mock/mock_py_ngraph_frontend/mock_py_frontend.hpp
index 5e089770ec2..3143aa96fda 100644
--- a/runtime/bindings/python/tests/mock/mock_py_ngraph_frontend/mock_py_frontend.hpp
+++ b/runtime/bindings/python/tests/mock/mock_py_ngraph_frontend/mock_py_frontend.hpp
@@ -107,12 +107,29 @@ public:
     std::vector<Place::Ptr> get_consuming_operations() const override {
         m_stat.m_get_consuming_operations++;
         m_stat.m_lastArgInt = -1;
+        m_stat.m_lastArgString = "";
         return {std::make_shared<PlaceMockPy>()};
     }
 
     std::vector<Place::Ptr> get_consuming_operations(int outputPortIndex) const override {
         m_stat.m_get_consuming_operations++;
         m_stat.m_lastArgInt = outputPortIndex;
+        m_stat.m_lastArgString = "";
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
+    std::vector<Place::Ptr> get_consuming_operations(const std::string& outputName) const override {
+        m_stat.m_get_consuming_operations++;
+        m_stat.m_lastArgInt = -1;
+        m_stat.m_lastArgString = outputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
+    std::vector<Place::Ptr> get_consuming_operations(const std::string& outputName,
+                                                     int outputPortIndex) const override {
+        m_stat.m_get_consuming_operations++;
+        m_stat.m_lastArgInt = outputPortIndex;
+        m_stat.m_lastArgString = outputName;
         return {std::make_shared<PlaceMockPy>()};
     }
 
@@ -128,6 +145,20 @@ public:
         return std::make_shared<PlaceMockPy>();
     }
 
+    Place::Ptr get_target_tensor(const std::string& outputName) const override {
+        m_stat.m_get_target_tensor++;
+        m_stat.m_lastArgInt = -1;
+        m_stat.m_lastArgString = outputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
+    Place::Ptr get_target_tensor(const std::string& outputName, int outputPortIndex) const override {
+        m_stat.m_get_target_tensor++;
+        m_stat.m_lastArgInt = outputPortIndex;
+        m_stat.m_lastArgString = outputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
     Place::Ptr get_producing_operation() const override {
         m_stat.m_get_producing_operation++;
         m_stat.m_lastArgInt = -1;
@@ -140,6 +171,20 @@ public:
         return std::make_shared<PlaceMockPy>();
     }
 
+    Place::Ptr get_producing_operation(const std::string& inputName) const override {
+        m_stat.m_get_producing_operation++;
+        m_stat.m_lastArgInt = -1;
+        m_stat.m_lastArgString = inputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
+    Place::Ptr get_producing_operation(const std::string& inputName, int inputPortIndex) const override {
+        m_stat.m_get_producing_operation++;
+        m_stat.m_lastArgInt = inputPortIndex;
+        m_stat.m_lastArgString = inputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
     Place::Ptr get_producing_port() const override {
         m_stat.m_get_producing_port++;
         return std::make_shared<PlaceMockPy>();
@@ -236,6 +281,20 @@ public:
         return {std::make_shared<PlaceMockPy>()};
     }
 
+    Place::Ptr get_source_tensor(const std::string& inputName) const override {
+        m_stat.m_get_source_tensor++;
+        m_stat.m_lastArgInt = -1;
+        m_stat.m_lastArgString = inputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
+    Place::Ptr get_source_tensor(const std::string& inputName, int inputPortIndex) const override {
+        m_stat.m_get_source_tensor++;
+        m_stat.m_lastArgInt = inputPortIndex;
+        m_stat.m_lastArgString = inputName;
+        return {std::make_shared<PlaceMockPy>()};
+    }
+
     //---------------Stat--------------------
     PlaceStat get_stat() const {
         return m_stat;
diff --git a/runtime/bindings/python/tests/test_frontend/test_frontend_onnx_editor.py b/runtime/bindings/python/tests/test_frontend/test_frontend_onnx_editor.py
index e241945dd0c..586cdd577a5 100644
--- a/runtime/bindings/python/tests/test_frontend/test_frontend_onnx_editor.py
+++ b/runtime/bindings/python/tests/test_frontend/test_frontend_onnx_editor.py
@@ -9,6 +9,7 @@ from ngraph import PartialShape
 from ngraph.frontend import FrontEndManager
 
 
+# ------Test input model 1------
 #       in1        in2        in3
 #        |          |          |
 #        \          /          |
@@ -24,9 +25,32 @@ from ngraph.frontend import FrontEndManager
 #     /     \       |
 #   out1   out2    out4
 #
+#
+# ------Test input model 2------
+#       in1        in2
+#        |          |
+#        \          /
+#         +--------+
+#         |  Add   |
+#         +--------+
+#          <add_out>
+#             |
+#        +--------+
+#        | Split  |
+#        |(split2)|
+#        +--------+
+#        /         \
+#   <sp_out1>    <sp_out2>
+#   +-------+    +-------+
+#   |  Abs  |    |  Sin  |
+#   | (abs1)|    |       |
+#   +------ +    +-------+
+#      |             |
+#     out1          out2
+#
 def create_test_onnx_models():
     models = {}
-    # Input model
+    # Input model 1
     add = onnx.helper.make_node("Add", inputs=["in1", "in2"], outputs=["add_out"])
     split = onnx.helper.make_node("Split", inputs=["add_out"],
                                   outputs=["out1", "out2"], name="split1", axis=0)
@@ -48,6 +72,24 @@ def create_test_onnx_models():
     models["input_model.onnx"] = make_model(graph, producer_name="ONNX Importer",
                                             opset_imports=[onnx.helper.make_opsetid("", 13)])
 
+    # Input model 2
+    split_2 = onnx.helper.make_node("Split", inputs=["add_out"],
+                                    outputs=["sp_out1", "sp_out2"], name="split2", axis=0)
+    abs = onnx.helper.make_node("Abs", inputs=["sp_out1"], outputs=["out1"], name="abs1")
+    sin = onnx.helper.make_node("Sin", inputs=["sp_out2"], outputs=["out2"])
+
+    input_tensors = [
+        make_tensor_value_info("in1", onnx.TensorProto.FLOAT, (2, 2)),
+        make_tensor_value_info("in2", onnx.TensorProto.FLOAT, (2, 2)),
+    ]
+    output_tensors = [
+        make_tensor_value_info("out1", onnx.TensorProto.FLOAT, (1, 2)),
+        make_tensor_value_info("out2", onnx.TensorProto.FLOAT, (1, 2)),
+    ]
+    graph = make_graph([add, split_2, abs, sin], "test_graph_2", input_tensors, output_tensors)
+    models["input_model_2.onnx"] = make_model(graph, producer_name="ONNX Importer",
+                                              opset_imports=[onnx.helper.make_opsetid("", 13)])
+
     # Expected for extract_subgraph
     input_tensors = [
         make_tensor_value_info("in1", onnx.TensorProto.FLOAT, (2, 2)),
@@ -312,8 +354,9 @@ def test_extract_subgraph_4():
     model = fe.load("input_model.onnx")
     assert model
 
-    place1 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=0)
-    place2 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=1)
+    out4_tensor = model.get_place_by_tensor_name(tensorName="out4")
+    place1 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
+    place2 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=1)
     place3 = model.get_place_by_operation_name_and_input_port(operationName="split1", inputPortIndex=0)
     place4 = model.get_place_by_tensor_name(tensorName="out1")
     place5 = model.get_place_by_tensor_name(tensorName="out2")
@@ -377,8 +420,9 @@ def test_override_all_inputs():
 
     place1 = model.get_place_by_operation_name_and_input_port(
         operationName="split1", inputPortIndex=0)
-    place2 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=0)
-    place3 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=1)
+    out4_tensor = model.get_place_by_tensor_name(tensorName="out4")
+    place2 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
+    place3 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=1)
     place4 = model.get_place_by_tensor_name(tensorName="in3")
     model.override_all_inputs(inputs=[place1, place2, place3, place4])
     result_func = fe.convert(model)
@@ -432,11 +476,15 @@ def test_is_input_output():
     assert not place3.is_input()
     assert not place3.is_output()
 
-    place4 = place1 = model.get_place_by_operation_name_and_input_port(
+    place4 = model.get_place_by_operation_name_and_input_port(
         operationName="split1", inputPortIndex=0)
     assert not place4.is_input()
     assert not place4.is_output()
 
+    place5 = model.get_place_by_operation_name(operationName="split1")
+    assert not place5.is_input()
+    assert not place5.is_output()
+
 
 def test_set_partial_shape():
     skip_if_onnx_frontend_is_disabled()
@@ -520,12 +568,14 @@ def test_is_equal():
     place2 = model.get_place_by_tensor_name(tensorName="out2")
     assert place2.is_equal(place2)
 
-    place3 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=0)
-    place4 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=0)
+    out4_tensor = model.get_place_by_tensor_name(tensorName="out4")
+    place3 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
+    place4 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
     assert place3.is_equal(place4)
 
+    out1_tensor = model.get_place_by_tensor_name(tensorName="out1")
     place5 = model.get_place_by_operation_name_and_input_port(operationName="split1", inputPortIndex=0)
-    place6 = model.get_place_by_tensor_name(tensorName="out1").get_input_port(inputPortIndex=0)
+    place6 = out1_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
     assert place5.is_equal(place6)
 
     place7 = model.get_place_by_tensor_name(tensorName="out4").get_producing_port()
@@ -538,6 +588,10 @@ def test_is_equal():
     assert not place6.is_equal(place7)
     assert not place8.is_equal(place2)
 
+    place9 = model.get_place_by_operation_name(operationName="split1")
+    assert place2.get_producing_operation().is_equal(place9)
+    assert not place9.is_equal(place2)
+
 
 def test_is_equal_data():
     skip_if_onnx_frontend_is_disabled()
@@ -560,11 +614,12 @@ def test_is_equal_data():
     place4 = place2.get_producing_port()
     assert place2.is_equal_data(place4)
 
-    place5 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=0)
+    out4_tensor = model.get_place_by_tensor_name(tensorName="out4")
+    place5 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
     assert place2.is_equal_data(place5)
     assert place4.is_equal_data(place5)
 
-    place6 = model.get_place_by_tensor_name(tensorName="out4").get_input_port(inputPortIndex=1)
+    place6 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=1)
     assert place6.is_equal_data(place5)
 
     place7 = model.get_place_by_operation_name_and_input_port(operationName="split1", inputPortIndex=0)
@@ -648,3 +703,198 @@ def test_get_input_port():
 
     assert not split_op.get_input_port(inputPortIndex=1)
     assert not split_op.get_input_port(inputName="not_existed")
+
+
+def test_get_consuming_ports():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model.onnx")
+    assert model
+
+    place1 = model.get_place_by_tensor_name(tensorName="add_out")
+    add_tensor_consuming_ports = place1.get_consuming_ports()
+    assert len(add_tensor_consuming_ports) == 3
+    place2 = model.get_place_by_operation_name_and_input_port(operationName="split1", inputPortIndex=0)
+    assert add_tensor_consuming_ports[0].is_equal(place2)
+    out4_tensor = model.get_place_by_tensor_name(tensorName="out4")
+    place3 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
+    assert add_tensor_consuming_ports[1].is_equal(place3)
+    place4 = out4_tensor.get_producing_operation().get_input_port(inputPortIndex=1)
+    assert add_tensor_consuming_ports[2].is_equal(place4)
+
+    add_op_consuming_ports = place1.get_producing_operation().get_consuming_ports()
+    assert len(add_op_consuming_ports) == len(add_tensor_consuming_ports)
+    for i in range(len(add_op_consuming_ports)):
+        assert add_op_consuming_ports[i].is_equal(add_tensor_consuming_ports[i])
+
+
+def test_get_consuming_ports_2():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    split_op_consuming_ports = split_op.get_consuming_ports()
+    assert len(split_op_consuming_ports) == 2
+    abs_input_port = model.get_place_by_operation_name(operationName="abs1").get_input_port(inputPortIndex=0)
+    assert split_op_consuming_ports[0].is_equal(abs_input_port)
+    out2_tensor = model.get_place_by_tensor_name(tensorName="out2")
+    sin_input_port = out2_tensor.get_producing_operation().get_input_port(inputPortIndex=0)
+    assert split_op_consuming_ports[1].is_equal(sin_input_port)
+
+    split_out_port_0 = split_op.get_output_port(outputPortIndex=0)
+    split_out_port_0_consuming_ports = split_out_port_0.get_consuming_ports()
+    assert len(split_out_port_0_consuming_ports) == 1
+    assert split_out_port_0_consuming_ports[0].is_equal(abs_input_port)
+
+
+def test_get_producing_operation():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    split_tensor_out_2 = model.get_place_by_tensor_name(tensorName="sp_out2")
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    assert split_tensor_out_2.get_producing_operation().is_equal(split_op)
+
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    split_out_port_2 = split_op.get_output_port(outputPortIndex=1)
+    assert split_out_port_2.get_producing_operation().is_equal(split_op)
+
+
+def test_get_producing_operation_2():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    abs_op = model.get_place_by_operation_name(operationName="abs1")
+    abs_port_0 = abs_op.get_input_port()
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    assert abs_port_0.get_producing_operation().is_equal(split_op)
+    assert abs_op.get_producing_operation().is_equal(split_op)
+
+    add_out_tensor = model.get_place_by_tensor_name(tensorName="add_out")
+    add_op = add_out_tensor.get_producing_operation()
+    assert not add_op.get_producing_operation()
+
+    split_op_producing_op = split_op.get_producing_operation(inputName="add_out")
+    assert split_op_producing_op.is_equal(add_op)
+
+    out2_tensor = model.get_place_by_tensor_name(tensorName="out2")
+    sin_op = out2_tensor.get_producing_operation()
+    assert sin_op.get_producing_operation(inputPortIndex=0).is_equal(split_op)
+
+
+def test_get_consuming_operations():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    split_op_consuming_ops = split_op.get_consuming_operations()
+    abs_op = model.get_place_by_operation_name(operationName="abs1")
+    sin_op = model.get_place_by_tensor_name(tensorName="out2").get_producing_operation()
+
+    assert len(split_op_consuming_ops) == 2
+    assert split_op_consuming_ops[0].is_equal(abs_op)
+    assert split_op_consuming_ops[1].is_equal(sin_op)
+
+    split_op_port = split_op.get_input_port(inputPortIndex=0)
+    split_op_port_consuming_ops = split_op_port.get_consuming_operations()
+
+    assert len(split_op_port_consuming_ops) == 1
+    assert split_op_port_consuming_ops[0].is_equal(split_op)
+
+    add_out_port = model.get_place_by_tensor_name(tensorName="add_out").get_producing_port()
+    add_out_port_consuming_ops = add_out_port.get_consuming_operations()
+    assert len(add_out_port_consuming_ops) == 1
+    assert add_out_port_consuming_ops[0].is_equal(split_op)
+
+    sp_out2_tensor = model.get_place_by_tensor_name(tensorName="sp_out2")
+    sp_out2_tensor_consuming_ops = sp_out2_tensor.get_consuming_operations()
+    assert len(sp_out2_tensor_consuming_ops) == 1
+    assert sp_out2_tensor_consuming_ops[0].is_equal(sin_op)
+
+    out2_tensor = model.get_place_by_tensor_name(tensorName="out2")
+    out2_tensor_consuming_ops = out2_tensor.get_consuming_operations()
+    assert len(out2_tensor_consuming_ops) == 0
+    out2_port_consuming_ops = out2_tensor.get_producing_port().get_consuming_operations()
+    assert len(out2_port_consuming_ops) == 0
+
+    split_out_1_consuming_ops = split_op.get_consuming_operations(outputPortIndex=1)
+    assert len(split_out_1_consuming_ops) == 1
+    split_out_sp_out_2_consuming_ops = split_op.get_consuming_operations(outputName="sp_out2")
+    assert len(split_out_sp_out_2_consuming_ops) == 1
+    assert split_out_1_consuming_ops[0].is_equal(split_out_sp_out_2_consuming_ops[0])
+    assert split_out_1_consuming_ops[0].is_equal(sin_op)
+
+
+def test_get_target_tensor():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    assert not split_op.get_target_tensor()
+
+    split_op_tensor_1 = split_op.get_target_tensor(outputPortIndex=1)
+    sp_out2_tensor = model.get_place_by_tensor_name(tensorName="sp_out2")
+    assert split_op_tensor_1.is_equal(sp_out2_tensor)
+
+    split_tensor_sp_out2 = split_op.get_target_tensor(outputName="sp_out2")
+    assert split_tensor_sp_out2.is_equal(split_op_tensor_1)
+
+    abs_op = model.get_place_by_operation_name(operationName="abs1")
+    out1_tensor = model.get_place_by_tensor_name(tensorName="out1")
+    assert abs_op.get_target_tensor().is_equal(out1_tensor)
+
+
+def test_get_source_tensor():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    add_out_tensor = model.get_place_by_tensor_name(tensorName="add_out")
+    add_op = add_out_tensor.get_producing_operation()
+    assert not add_op.get_source_tensor()
+
+    add_op_in_tensor_1 = add_op.get_source_tensor(inputPortIndex=1)
+    in2_tensor = model.get_place_by_tensor_name(tensorName="in2")
+    assert add_op_in_tensor_1.is_equal(in2_tensor)
+
+    add_op_in_tensor_in2 = add_op.get_source_tensor(inputName="in2")
+    assert add_op_in_tensor_in2.is_equal(in2_tensor)
+
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    assert split_op.get_source_tensor().is_equal(add_out_tensor)
+
+
+def test_get_producing_port():
+    skip_if_onnx_frontend_is_disabled()
+    fe = fem.load_by_framework(framework=ONNX_FRONTEND_NAME)
+    assert fe
+    model = fe.load("input_model_2.onnx")
+    assert model
+
+    split_op = model.get_place_by_operation_name(operationName="split2")
+    split_op_in_port = split_op.get_input_port()
+    split_op_in_port_prod_port = split_op_in_port.get_producing_port()
+
+    add_out_tensor = model.get_place_by_tensor_name(tensorName="add_out")
+    add_op = add_out_tensor.get_producing_operation()
+    add_op_out_port = add_op.get_output_port()
+
+    assert split_op_in_port_prod_port.is_equal(add_op_out_port)
diff --git a/runtime/bindings/python/tests/test_frontend/test_frontendmanager.py b/runtime/bindings/python/tests/test_frontend/test_frontendmanager.py
index 920746e200a..8ecece7404a 100644
--- a/runtime/bindings/python/tests/test_frontend/test_frontendmanager.py
+++ b/runtime/bindings/python/tests/test_frontend/test_frontendmanager.py
@@ -440,6 +440,16 @@ def test_place_get_consuming_operations():
     stat = get_place_stat(place)
     assert stat.get_consuming_operations == 2
     assert stat.lastArgInt == -1
+    assert place.get_consuming_operations(outputName="2") is not None
+    stat = get_place_stat(place)
+    assert stat.get_consuming_operations == 3
+    assert stat.lastArgInt == -1
+    assert stat.lastArgString == "2"
+    assert place.get_consuming_operations(outputName="3", outputPortIndex=33) is not None
+    stat = get_place_stat(place)
+    assert stat.get_consuming_operations == 4
+    assert stat.lastArgInt == 33
+    assert stat.lastArgString == "3"
 
 
 @mock_needed
@@ -453,6 +463,16 @@ def test_place_get_target_tensor():
     stat = get_place_stat(place)
     assert stat.get_target_tensor == 2
     assert stat.lastArgInt == -1
+    assert place.get_target_tensor(outputName="2") is not None
+    stat = get_place_stat(place)
+    assert stat.get_target_tensor == 3
+    assert stat.lastArgInt == -1
+    assert stat.lastArgString == "2"
+    assert place.get_target_tensor(outputName="3", outputPortIndex=33) is not None
+    stat = get_place_stat(place)
+    assert stat.get_target_tensor == 4
+    assert stat.lastArgInt == 33
+    assert stat.lastArgString == "3"
 
 
 @mock_needed
@@ -466,6 +486,16 @@ def test_place_get_producing_operation():
     stat = get_place_stat(place)
     assert stat.get_producing_operation == 2
     assert stat.lastArgInt == -1
+    assert place.get_producing_operation(inputName="2") is not None
+    stat = get_place_stat(place)
+    assert stat.get_producing_operation == 3
+    assert stat.lastArgInt == -1
+    assert stat.lastArgString == "2"
+    assert place.get_producing_operation(inputName="3", inputPortIndex=33) is not None
+    stat = get_place_stat(place)
+    assert stat.get_producing_operation == 4
+    assert stat.lastArgInt == 33
+    assert stat.lastArgString == "3"
 
 
 @mock_needed
@@ -551,3 +581,13 @@ def test_place_get_source_tensor():
     stat = get_place_stat(place)
     assert stat.get_source_tensor == 2
     assert stat.lastArgInt == 22
+    assert place.get_source_tensor(inputName="2") is not None
+    stat = get_place_stat(place)
+    assert stat.get_source_tensor == 3
+    assert stat.lastArgInt == -1
+    assert stat.lastArgString == "2"
+    assert place.get_source_tensor(inputName="3", inputPortIndex=33) is not None
+    stat = get_place_stat(place)
+    assert stat.get_source_tensor == 4
+    assert stat.lastArgInt == 33
+    assert stat.lastArgString == "3"