A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span

A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span

Dimitris N. Kanellopoulos, Pratik Gite
DOI: 10.4018/IJECME.2020010101
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Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH.
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A wireless sensor network (WSN) can be employed in many application areas for diverse civilian and military scenarios. It does not require a pre-defined network infrastructure and can be deployed on an ad-hoc basis (Seah & Tan, 2010). A WSN is composed of sensor nodes deployed in a field-of-interest for monitoring environment conditions such as temperature, air pressure, motion, and so on. A sensor node contains signal-processing circuits, microcontrollers, and wireless transmitters or receiver antennas. In a WSN, sensor nodes are sending their collected data to the base station (BS), if BS is within communication range. A BS (also called Sink) is a device that has more energy capacity, processing power, and memory than common sensor nodes. If BS is out of the communication range, sensed data are sent to other sensor nodes through a routing protocol. It is noteworthy that all sensor nodes are constrained in energy as their batteries do not require recharging from the time these nodes are randomly deployed in the sensing field. Obviously, this affects the network lifetime. Prolonging the life span of a WSN can be achieved by different energy efficiency techniques:

  • Energy-efficient routing protocols (Pantazis et al., 2012; Anisi et al., 2017)

  • Duty-cycling (Carrano et al. 2014) and MAC protocols (Doudou et al., 2014).

  • Topology control (Bagci et al. 2015; Deniz et al., 2016)

  • Energy efficient data aggregation schemes (Dong et al., 2016)

  • Cross-layer optimization techniques (Mendes & Rodrigues, 2011; Fu et al., 2014). A cross-layer design (CLD) allows the communication architecture to work as a system instead of a stack with different protocols. In particular, CLD permits the interactions between different non-adjacent layers in order to overcome the OSI model’s limitations (i.e., the principles of abstraction and encapsulation at each layer) and provide better network management in terms of energy, Quality of Service (QoS) etc. In WSNs, a CLD approach is adopted by many communication protocols.

Routing protocols influence the energy saving of sensor nodes because the communicating module of a sensor node consumes considerably more energy than the computing module (Heinzelman et al., 2000). The energy consumed during communication mostly depends on the distance between the sending and receiving nodes. Therefore, many routing solutions have been proposed on how to optimize this distance (Pantazis et al., 2012).

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