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Abstract: The positioning of wireless nodes has been an active research area over the last decade. Many network positioning algorithms have been proposed to solve this problem. The vast majority assume that a fixed set of nodes (called seeds) have a mechanism to position themselves at all times (using GPS or other means). The other nodes estimate their positions based on positional information exchanged between nodes using wireless communication. The monetary cost of a GPS unit is decreasing so systems where most nodes are equipped with a GPS unit is foreseeable. A problem with this assumption is that the task of self-positioning via a GPS unit is expensive in terms of energy consumption which results in faster battery decay. In this paper, we assume that every node is capable of self-positioning but activates that module selectively. This allows for balancing the energy costs of self-positioning among all nodes and results in reduced positional error. We investigate several different strategies for governing the self-positioning module and report on their performance. [Copyright &y& Elsevier]

Abstract: Localization is defined as the problem of determining the geographical locations of nodes in a wireless ad hoc or sensor network. Networks typically have some nodes (called seeds) that know their locations (using GPS or other means). Other (non-seed) nodes compute their locations by exchanging messages with nodes within their radio range.Several algorithms have been proposed for localization in different scenarios. Algorithms have been designed for networks in which each node has ranging capabilities (i.e., can estimate distances to its neighbors). Other algorithms have been proposed for networks in which no node has such capabilities. Some algorithms only work when nodes are static. Some other algorithms are designed specifically for networks in which all nodes are mobile. In this paper we propose a range-based localization algorithm RMCB for wireless sensor networks. Our algorithm uses a small fraction of seeds. It also makes use of the received signal strength measurements that are available from the sensor hardware. Our algorithm works well when nodes are static or mobile. We demonstrate using empirical data from sensor hardware (Texas Instruments EZ 430-RF2500) and simulations that RMCB outperforms a very good range-free algorithm WMCL in terms of localization error and has a similar computational complexity to WMCL. [Copyright &y& Elsevier]