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A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks

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Abstract

Sensor networks have a wide range of potential, practical and useful applications. However, there are issues that need to be addressed for efficient operation of sensor network systems in real applications. Energy saving is one critical issue for sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime. To extend the lifetime of a sensor network, one common approach is to dynamically schedule sensors' work/sleep cycles (or duty cycles). Moreover, in cluster-based networks, cluster heads are usually selected in a way that minimizes the total energy consumption and they may rotate among the sensors to balance energy consumption. In general, these energy-efficient scheduling mechanisms (also called topology configuration mechanisms) need to satisfy certain application requirements while saving energy. In this paper, we provide a survey on energy-efficient scheduling mechanisms in sensor networks that have different design requirements than those in traditional wireless networks. We classify these mechanisms based on their design assumptions and design objectives. Different mechanisms may make different assumptions about their sensors including detection model, sensing area, transmission range, failure model, time synchronization, and the ability to obtain location and distance information. They may also have different assumptions about network structure and sensor deployment strategy. Furthermore, while all the mechanisms have a common design objective to maximize network lifetime, they may also have different objectives determined by their target applications.

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Authors and Affiliations

  1. Department of Computer Science, The University of Memphis, 373 Dunn Hall, Memphis, TN, 38152, USA

    Lan Wang & Yang Xiao

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  1. Lan Wang
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  2. Yang Xiao
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Correspondence to Lan Wang.

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A preliminary was presented in BROADNETS 2006 [29]

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Wang, L., Xiao, Y. A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks. Mobile Netw Appl 11, 723–740 (2006). https://doi.org/10.1007/s11036-006-7798-5

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