Achieving Max-Min lifetime and fairness with rate allocation for data aggregation in sensor networks

We consider the rate allocation problem for data aggregation in wireless sensor networks with two objectives: 1) maximizing the minimum (Max-Min) lifetime of an aggregation cluster and 2) achieving fairness among all data sources. The two objectives are generally correlated with each other and usually, they cannot be maximized simultaneously. We adopt a lexicographic method to solve this multi-objective programming problem. First, we recursively induce the Max-Min lifetime for the aggregation cluster. Under the given Max-Min lifetime, we then formulate the problem of maximizing fairness as a convex optimization problem, and derive the optimal rate allocation strategy by iterations. We also present low-complexity algorithms that an aggregation cluster can use to determine the Max-Min network lifetime and the fair rate allocation. Our simulation results validate our analytical results and illustrate the effectiveness of the approach.