Approximation algorithms for power-aware scheduling of wireless sensor networks with rate and duty-cycle constraints
We develop algorithms for finding the minimum energy transmission schedule for duty-cycle and rate constrained wireless sensor nodes transmitting over an interference channel. Since traditional optimization methods using Lagrange multipliers do not work well and are computationally expensive given the non-convex constraints, we develop fully polynomial approximation schemes (FPAS) for finding optimal schedules by considering restricted versions of the problem using multiple discrete power levels. We first show a simple dynamic programming solution that optimally solves the restricted problem. For two fixed transmit power levels (0 and P), we then develop a 2-factor approximation for finding the optimal fixed transmission power level per time slot, P opt, that generates the optimal (minimum) energy schedule. This can then be used to develop a (2, 1 + ε)-FPAS that approximates the optimal power consumption and rate constraints to within factors of 2 and arbitrarily small ε > 0, respectively. Finally, we develop an algorithm for computing the optimal number of discrete power levels per time slot (O(1/ε)), and use this to design a (1, 1 + ε)-FPAS that consumes less energy than the optimal while violating each rate constraint by at most a 1 + ε factor. © Springer-Verlag Berlin Heidelberg 2006.
Publication Source (Journal or Book title)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Kannan, R., & Wei, S. (2006). Approximation algorithms for power-aware scheduling of wireless sensor networks with rate and duty-cycle constraints. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4026 LNCS, 463-479. https://doi.org/10.1007/11776178_28