Abstract
Abstract In this paper, we propose a topology control technique to reduce the energy consumption of wireless sensor networks (WSNs). The technique makes use of both power control and power management methods. The algorithm uses the power management technique to put as many idle nodes as possible into the sleep mode while invoking the power control method to adjust the transmission range of the active nodes. On the contrary to earlier works in which both of these methods were used separately, in this algorithm, they are utilized simultaneously to decide about the sleep nodes and the ranges of active nodes. It is an approximation algorithm which is called simultaneous power control and power management algorithm (SPCPM). The performance bound of this centralized algorithm is determined analytically. Then, to make the proposed method practical for WSNs, a distributed algorithm based on SPCPM is introduced. To assess the efficiency of the proposed algorithm, we compare its average energy consumption with those of three existing topology control algorithms for a sector-based WSN. The simulation results which were obtained for different numbers of transmitting sensor nodes reveal less average energy consumptions for SPCPM compared to other algorithms.
Highlights
Recent advances in wireless and electronic technologies have led to the emergence of wireless sensor networks (WSNs) with large-scale nodes
The results shown in this figure reveal that Minimum Power Configuration (MPC) and simultaneous power control and power management algorithm (SPCPM) provide considerably higher energy preservations compared to Transmission power Shortest Path Tree (TSPT) and TMST
The results were extracted based on definitions and assumptions discussed in [9]. These results indicate that SPCPM leads to a longer lifetime for the network compared to those of basic power control (BPC), minimum power configuration protocol (MPCP), and minimum transmission routing (MTR)
Summary
Recent advances in wireless and electronic technologies have led to the emergence of wireless sensor networks (WSNs) with large-scale nodes. Backbone-based sleep management can improve network performance by maintaining a backbone composed of a small number of active nodes, while scheduling the other nodes to be active for small periods of time to conserve energy From another aspect, the techniques may be divided based on the dimension that they use for the power management. We show that these findings hold true for a sector-shaped WSN too Based on these facts, in this paper, we suggest a unified algorithm which makes a coherent use of both power control and power management algorithms to minimize the energy consumption both in the idle and transmit/receive states. This approach is based on a joint duty-cycle optimization and transmission power control By simultaneously adapting both parameters, the node can maximize the number of transmitted packets while respecting the limited and time-varying amount of available energy.
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