Evolutionary Routing

Evolutionary algorithms are inspired by the biological evolution. They use reproduction, mutation, selection, and recombination of a population of entities to solve problems that are considered hard. The individuals are evaluated by a given fitness function which determines their survival. After several generations, one individual with the highest fitness will represent a solution to a particular problem. This solution might be sub-optimal but a good and satisfying approximation.

This approach can also be applied to routing in networks as other researchers have already proposed. In our context we are interested in a specification and implementation for a wireless mesh network that takes into account the most common application scenarios. Very often evolutionary algorithms are centralized which means a central entity calculates the solution. This is fine for some scenarios, but we intend to get a distributed variant.

Objectives

• Get familiar with evolutionary algorithms
• Get familiar with the proposed application of evolutionary algorithms for networks
• Specify and implement a distributed algorithm that provides routes in a (mobile) wireless network
• Evaluate your implementation on our testbed