<｜begin▁of▁sentence｜>### Instruction:
In the context of optimizing network resources in a telecommunication environment, consider the task of pairing connection nodes in a manner that minimizes the links between them without leaving any single node overly burdened or acting as a central hub. 

Imagine a network topology represented by the following pairs of interconnected nodes: (1, 2), (2, 3), (3, 4), (4, 5), (5, 1), (2, 5), and (3, 1). For the purpose of efficient resource management, you are tasked with finding the smallest set of node pairs—termed the "minimal maximal matching"—such that the busiest node is as unburdened as possible while ensuring no node is left without a partner.

In documenting this scenario for a technical manual or guide, you would lay out the situation as follows:

"Within the given network topology, a set of connections has been established as depicted by the edge set comprised of [(1, 2), (2, 3), (3, 4), (4, 5), (5, 1), (2, 5), (3, 1)]. When engineering a solution for maximal efficiency in this topology, the objective is to determine the minimal maximal matching. This matches nodes with their peers in such a manner that the most connected node has the least number of connections required by any such matching. This ensures an optimal load distribution across the network nodes."

By presenting this technical challenge in a structured context, you guide stakeholders or systems engineers through the specifics of network optimization without veering away from the concrete example provided.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add edges to the graph (nodes are added automatically)
G.add_edges_from([(1, 2), (2, 3), (3, 4), (4, 5), (5, 1), (2, 5), (3, 1)])

# Find the minimum maximal matching using the API
def min_maximal_matching(G):
    """Returns the set of edges in the minimum maximal matching."""
    return nx.algorithms.matching.min_maximal_matching(G)

# Invoke the function
matching = min_maximal_matching(G)

# Output the matching
print(matching)
<|EOT|>
