Survivability and performance optimization of mobile wireless communication networks in the event of base station failure
In this paper, we investigate the survivability of mobile wireless communication networks in the event of base station (BS) failure. A survivable network is modeled as a mathematical optimization problem in which the objective is to minimize the total amount of blocked traffic. We apply Lagrangean relaxation as a solution approach and analyze the experiment results in terms of the blocking rate, service rate, and CPU time. The results show that the total call blocking rate (CBR) is much less sensitive to the call blocking probability (CBP) threshold of each BS when the load is light, rather than heavy; therefore, the more traffic loaded, the less the service rate will vary. BS recovery is much more important when the network load is light. However, the BS recovery ratio (BSRR), which is a key factor in reducing the blocking rate for a small number of BSs, is more important when a system is heavily loaded. The proposed model provides network survivability subject to available resources. The model also fits capacity expansion requirements by locating mobile/portable BSs in the places they are most needed.
lagrangean relaxation network survivability base station recovery mathematical modeling performance evaluation quality of service