Power-saving geographic routing in the presence of location errors
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
| Hi-index | 0.01 |
Maximizing the network lifetime while maintaining application constraints of delay and reliability is the most important goal while designing protocols for wireless sensor networks. This dissertation focuses on a complete protocol stack solution that deals with the problem from two angles. The first part is a routing and MAC layer protocol that minimizes the power consumption required to transmit packets across the network. The cross-layer solution, called region-based opportunistic routing, utilizes the spatial diversity due to high node density to lower the average power consumption, reduce latency and be more robust to bad channels and node failures. Opportunistic routing is a new routing paradigm where the network layer only selects a set of potential forwarding nodes, while the MAC layer does the actual next hop selection based on node availability. This leads to improvements of up to 30% in the average power consumption and 40% in the end to end latency of packets over traditional approaches such as geographic routing. The second part of the solution is a mechanism to shift the forwarding workload among nodes so as to maximize the time till the first node runs out of energy. This is achieved by a distributed duty cycling algorithm that adjusts the duty cycle of each node individually without requiring any communication whatsoever among nodes. The algorithm ensures that the duty cycles of the nodes achieve the optimal duty cycle that minimizes the total power consumption of the network while ensuring fairness in node lifetimes. Moreover, it also ensures that the application latency and reliability constraints are satisfied. The optimal linear control policy is derived, which is a weighted multiplicative increase multiplicative decrease policy. Simulations show that the algorithm achieves a network lifetime fairly close to the optimal lifetime that would have been possible using a centralized approach that had complete knowledge about the network topology, traffic and channel conditions.