Optimizations for charged service provision in Mobile Ad Hoc Networks

Optimized service provisioning is a challenging problem in dynamic environments such as mobile ad hoc networks (MANETs). Most of the existing approaches assume an environment, where service provision is free (and dictated) and servers do not have an incentive to maximize their benefit. In this paper we consider the nodes in MANETs to be independent, rational agents trying to maximize their profits through service provision. We model this problem as a generalized assignment problem (GAP). We adopt a pay-as-you-go model and introduce into the proposed profit maximization algorithm expected payoffs based on estimates of server-to-client connectivity. We define connectivity as the lifetime of the network connection between a client and a server. We experimentally study cases with non-cooperative and cooperative servers and investigate the gain of the estimate based maximization algorithm versus a classic maximization algorithm, which does not take into account the networkpsilas dynamics that affect server-to-client connectivity. The results show that our approach achieves up to three-fold improved server profits compared to the classical one and is especially suited for MANETs with high-mobility.