<｜begin▁of▁sentence｜>### Instruction:
Imagine you're piloting your drone over a new region, mapping out the landscape below to ensure comprehensive coverage for your aerial survey. The region you're flying over is a network of interconnected waypoints represented by nodes 1, 2, 3, 4, and 5. Your current flight path includes traversing the connections (or 'edges') between these waypoints as follows: from waypoint 1 to waypoints 2, 3, and 4; between waypoints 3 and 4; and also between waypoints 3, 4, and 5.

For optimizing future flight plans, you’d want to identify the most remote waypoints in your network, meaning those that require the longest path to reach from any other point. This would determine your drone's maximum distance to cover from any one waypoint to the farthest one. In network analysis terms, you're looking for the 'periphery' of this waypoint network, which includes all waypoints (nodes) with an 'eccentricity' equal to the 'diameter' – that's the greatest distance between any pair of waypoints in your survey grid.

Could you reframe your flight data to pinpoint these key waypoints, ensuring that no part of the region is overlooked in future surveillance exercises?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (1, 4), (3, 4), (3, 5), (4, 5)])

# Compute the periphery of the graph
periphery_nodes = nx.periphery(G)

print('Periphery nodes:', periphery_nodes)
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