Robust Routing Design with Consideration of Lifetime Maximization for Wireless Sensor Networks in a Framework of Anti-risk Strategy with the Improved Constrained Particle Swarm Optimization Approach

Since the energy constraint is a fundamental issue for wireless sensor networks, the expectation of network lifetimes becomes a critical performance index. In actual applications, the data traffic on an available routing path could fluctuate from time to time, so there is a compelling need for a robust routing strategy to make the links robust enough when the link outage happens. In the paper, we jointly integrate the maximization of network lifetime and the designing of robust routing strategy into consideration, by which both two subproblems are modeled in a framework of cross-layer nonlinear optimization. By using the popular anti-risk methods popularly used in financial mathematics, our proposed cross-layer optimization problem can be transformed to a convex expression, while its uncertain probabilistic constraints are further changed to a specific solvable expression. Inspired by the particle swarm intelligence in recent development of evolutionary computation, a penalty function based method is introduced and applied in the optimal solution searching process. The effectiveness of our robust routing design is validated by the extensive simulation results, and the quantitative interactions among different neighboring links are also analysed in a typical network topology.