Managing Traffic Growth in Solar Powered Wireless Mesh Networks

Wireless mesh nodes must often be upgraded so that the network can accommodate evolving user demands. When some of the nodes are operated using a sustainable solar energy source, these upgrades must take into account the cost of updating the node energy resource configurations. This is required so that the new network configuration can properly accommodate the updated energy workloads of the re-provisioned network. In this paper we study this problem in the context of sustainable energy mesh node provisioning costs. We derive a mixed integer linear programming (MILP) formulation which is used to optimize the costs of node resource upgrades. Using this result, a lower bound on the network upgrade cost is obtained. The paper then proposes the use of a genetic algorithm based methodology for determining practical cost-effective mesh node resource upgrading. Various examples are given using networks with random, mesh and tree topologies which show the value of the proposed mechanism. In particular we find that the genetic algorithm approach achieves results which are much better than those from an algorithm which uses local optimization. It also performs well compared to our derived lower bound.