PROJECT TITLE :
Multiperiod Scheduling for Wireless Sensor Networks: A Distributed Consensus Approach
In wireless sensor networks, many sensors face energy constraints and can switch among completely different work modes to save lots of energy. A way to properly schedule work modes is important for network utility maximization (NUM) in the long run. This paper proposes multiperiod scheduling to maximize total network utility by considering energy constraints and periodic sensing requirements. This NUM drawback presents challenging mixed-integer programming, and it is troublesome to solve by using a centralized approach beneath complete info. So, we tend to first simplify the multiperiod problem to constant single-amount downside, and then more cut back it to a pure-integer programming downside, which can be solved easily in a very centralized method. As for the cases while not a centralized coordinator among all sensors, we propose a median consensus-based distributed algorithm (ACDA) to distributively schedule the work modes of all sensors using only local info. We have a tendency to prove that ACDA converges exponentially quick and reaches global optimum as long because the energy consumption of running the algorithm is ignorable. The proposed distributed resolution is also sturdy against packet drop, node failures, and also the changes of communication topology. Intensive simulation results have conjointly shown the effectiveness of the proposed distributed algorithms.
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