In wireless sensor networks, a few sensor nodes end up being vulnerable to potentially rapid depletion of the battery reserves due to either their central location or just the traffic patterns generated by the application. Traditional energy management strategies, such as those which use topology control algorithms, reduce the energy consumed at each node to the minimum necessary. In this paper, we use a different approach that balances the energy consumption at each of the nodes, thus increasing the functional lifetime of the network. We propose a new distributed dynamic topology control algorithm called Energy Balanced Topology Control (EBTC) which considers the actual energy consumed for each transmission and reception to achieve the goal of an increased functional lifetime. We analyze the algorithm's computational and communication complexity and show that it is equivalent or lower in complexity to other dynamic topology control algorithms. Using an empirical model of energy consumption, we show that the EBTC algorithm increases the lifetime of a wireless sensor network by over 40 compared to the best of previously known algorithms.
Traditional topology control algorithms use an energy management strategy in which each sensor node reduces its transmission power from its maximum value to a relatively small quantity while maintaining the connectivity of the network. Algorithms of this class include Directed Relative Neighborhood Graph (DRNG) @cite_14 , Directed Local Spanning Subgraph (DLSS) @cite_14 , @cite_11 and @cite_2 . The topology of the network is determined at the very beginning of the network's life, and remains the same throughout the network lifetime.
@cite_14 @cite_2 @cite_11
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Most existing topology control algorithms assume homogeneous wireless networks with uniform maximal transmission power, and cannot be directly applied to heterogeneous wireless networks where the maximal transmission power of each node may be different. We present two localized topology control algorithms for heterogeneous networks: Directed Relative Neighborhood Graph (DRNG) and Directed Local Spanning Subgraph (DLSS). In both algorithms, each node independently builds its neighbor set by adjusting the transmission power, and defines the network topology by using only local information. We prove that: 1) both DRNG and DLSS can preserve network connectivity; 2) the out-degree of any node in the resulting topology generated by DRNG or DLSS is bounded by a constant; and 3) DRNG and DLSS can preserve network bi-directionality. Simulation results indicate that DRNG and DLSS significantly outperform existing topology control algorithms for heterogeneous networks in several aspects. The topology of a wireless multi-hop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a cone-based distributed topology-control (CBTC) algorithm. This algorithm does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node u transmits with the minimum power p sub u, spl alpha required to ensure that in every cone of degree spl alpha around u, there is some node that u can reach with power p sub u, spl alpha . We show that taking spl alpha =5 spl pi 6 is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from s to t when every node communicates at maximum power then, if spl alpha spl les 5 spl pi 6, there is still a path in the smallest symmetric graph G sub spl alpha containing all edges (u,v) such that u can communicate with v using power p sub u, spl alpha . On the other hand, if spl alpha >5 spl pi 6, connectivity is not necessarily preserved. We also propose a set of optimizations that further reduce power consumption and prove that they retain network connectivity. Dynamic reconfiguration in the presence of failures and mobility is also discussed. Simulation results are presented to demonstrate the effectiveness of the algorithm and the optimizations. Each node in a wireless multi-hop network can adjust the power level at which it transmits and thus change the topology of the network to save energy by choosing the neighbors with which it directly communicates. Many previous algorithms for distributed topology control have assumed an ability at each node to deduce some location-based information such as the direction and the distance of its neighbor nodes with respect to itself. Such a deduction of location-based information, however, cannot be relied upon in real environments where the path loss exponents vary greatly leading to significant errors in distance estimates. Also, multipath effects may result in different signal paths with different loss characteristics, and none of these paths may be line-of-sight, making it difficult to estimate the direction of a neighboring node. In this paper, we present Step Topology Control (STC), a simple distributed topology control algorithm which reduces energy consumption while preserving the connectivity of a heterogeneous sensor network without use of any location-based information. The STC algorithm avoids the use of GPS devices and also makes no assumptions about the distance and direction between neighboring nodes. We show that the STC algorithm achieves the same or better order of communication and computational complexity when compared to other known algorithms that also preserve connectivity without the use of location-based information. We also present a detailed simulation-based comparative analysis of the energy savings and interference reduction achieved by the algorithms. The results show that, in spite of not incurring a higher communication or computational complexity, the STC algorithm performs better than other algorithms in uniform wireless environments and especially better when path loss characteristics are non-uniform.