The research on extending the lifetime of wireless sensor networks

We study various problems efficient energy management for wireless sensor networks. First, we research the energy efficient deployment of wireless sensor nodes so that energy consumption rates of all nodes are equal during the lifetime of the wireless sensor network. If the sensors are deployed uniformly across the network, they experience different traffic intensities and energy depletion rates depending on their locations. Usually, the sensors near the sink tend to deplete their energy sooner; when enough of them exhaust their energy, they leave holes in the network, causing the remaining nodes to be disconnected from the sink. One of the solutions to this energy-hole problem is to deploy the sensors non-uniformly. Moreover, we describe a method for deciding the sensor deployment densities so as to equalize the energy consumption rates of all nodes. The method is general and can be applied to other objectives and constraints.;Second, we propose a framework to maximize the lifetime of the wireless sensor networks by using a mobile sink when the underlying applications tolerate delayed information delivery to the sink. Within a prescribed delay tolerance level, each node does not need to send the data immediately as it becomes available. Instead, the node can store the data temporarily and transmit it when the mobile sink is at the most favorable location for achieving the longest WSN lifetime. We call the proposed framework as Delay-Tolerant Mobile Sink Wireless Sensor Network. To find the best solution within the proposed framework, we formulate optimization problems that maximize the lifetime of the WSN subject to the delay bound constraints, node energy constraints, and flow conservation constraints. We conduct extensive computational experiments on the optimization problems and find that the lifetime can be increased significantly as compared to not only the stationary sink model but also more traditional mobile sink models. We also show that the delay tolerance level does not affect the maximum lifetime of the WSN.;Third, we propose an adaptive and potentially decentralized algorithm for the DT-MSM. The distributed routing algorithms are very important in developing a practical routing protocol. Distributed algorithms are generally free from the network scalability issues in several reasons. They do not need to have knowledge about the whole network configurations and they also do not require the central node to compute the routes for all nodes in the network. Lagrange multiplier method solves dual of the primal problem. Dual problem sometimes has a nice structure with which we can decompose the dual problem into several sub-problems. We use a subgradient projection method to solve the dual problem and. A sensor node in our method keeps virtual queue which is a scalar product of the Lagrange multiplier and it is used in solving sub-problems. We propose (a possibly distributed implementable) decentralized algorithms for solving sub-problems. Moreover, we analytically show the our algorithm finds a solution arbitrarily close to the optimal solution of the primal problem. It is verified through the numerical experiments.