Topology control of ad hoc wireless networks for energy efficiency

Abstract

Abstract-In this paper, we address the Topology control with Cooperative Communication (TCC) problem in ad hoc wireless networks. Cooperative communication is a novel model introduced recently that allows combining partial messages to decode a complete message. The objective of the TCC problem is to obtain a strongly-connected topology with minimum total energy consumption. We show that the TCC problem is NP-complete and design two distributed and localized algorithms to be used by the nodes to set up their communication ranges. Both algorithms can be applied on top of any symmetric, strongly-connected topology to reduce total power consumption. The first algorithm uses a distributed decision process at each node that makes use of only 2-hop neighborhood information. The second algorithm sets up the transmission ranges of nodes iteratively, over a maximum of six steps, using only 1-hop neighborhood information. We analyze the performance of our approaches through extensive simulation.

Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks

“…Since energy is an important constraint in the setting of sensor networks, a lot of work has focused on constructing low energy subgraphs (see e.g., [9], [6]). However, it is counterproductive to use a lot of resources (e.g.…”

“…Thus it is necessary to develop simple, local, distributed algorithms which are energy-efficient, and preferably also time-efficient, even at the cost of being sub-optimal (see e.g., [5], [8], [9] for such algorithms in the context of wireless sensor networks -discussed more below). This adds a new dimension to the design of distributed algorithms for such networks.…”

“…This is especially true in a dynamic setting -when the network needs to be reconfigured (e.g., due to mobility or failures) frequently and quickly. Reconfiguration is also necessary to evenly distribute the energy consumption among all nodes and thus, to increase network lifetime [7].Thus it is necessary to develop simple, local, distributed algorithms which are energy-efficient, and preferably also time-efficient, even at the cost of being sub-optimal (see e.g., [5], [8], [9] for such algorithms in the context of wireless sensor networks -discussed more below). This adds a new dimension to the design of distributed algorithms for such networks.…”

“…Thus we can potentially tradeoff optimality of the solution to work done by the algorithm. In a sensor network, the total energy required ("energy complexity") in a distributed algorithm typically depends on the time needed, the number of messages exchanged, and the radiation energy needed to transmit the messages over a certain distance (see e.g., [9], [10]). The radiation energy needed to transmit a message is typically assumed proportional to some work function f (typically square or some small power) of the distance between the sender and the receiver [7], [11].…”

Multiobjective Optimization for a Wireless Ad Hoc Sensor Distribution on Shaped-Bounded Areas

“…It is worth mentioning that sensor distribution with minimum energy connectivity is an NP-complete problem [9][10][11][12]. In the literature, different strategies for wireless ad hoc and sensor networks related to topology control [2], node localization [13,14], distributed coverage [15], and network lifetime [16] are described to provide solutions for sensor distribution, coverage area, and energy consumption problems.…”