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The state of the art for optimal data-gathering in wireless sensor networks is to use additive increase algorithms to achieve max-min fair rate allocation ([1], [3]) while implicity trying to maximize network utilization. In this work we explicitly formulate the problem of maximizing the network utilization subject to a max-min fair rate allocation constraint in the form of two separate but dependent linear programs. We adopt a dual based approach to design an efficient distributed algorithm to achieve our objectives. The analysis of the dual proves the sub-optimality of previously proposed additive increase algorithms for this problem. We show through numerical evaluations that the proposed dual-based distributed algorithm can obtain solutions within 0.02 % of the optimal in 99.65 % of the cases (and within 20 % in even the worst case) within just one iterative update of shadow prices through sub-gradient search, requiring a polynomial number of message exchanges (which appears to grow as O(n 2) where n is the number of sources in the network). I.

End-to-end reliability of communications is an important requirement in many applications of wireless sensor networks. For this reason, a number of reliable transport protocols specifically designed for wireless sensor networks have been proposed in the literature. Besides providing end-to-end reliability, some of those protocols also address the problems of fairness and congestion control, and they are all optimized for low energy consumption. However, in this paper, we show that most of those protocols completely neglect security issues. As a consequence, they ensure reliable communications and low energy consumption only in a benign environment, but they fail in a hostile environment, where an adversary can forge or replay control packets of the protocol. More specifically, our analysis shows that control packet injection and replay can cause permanent loss of data packets, and thus, such misdeeds make the hitherto reliable protocol unreliable. In addition, even if the protocol can recover from such an attack, the recovery overhead caused by forged or replayed control packets can be large, which gives an opportunity for energy depletion attacks. 1

journal homepage: www.elsevier.com/locate/adhoc Locally scheduled packet bursting for data collection