Short-Hops vs. Long-Hops: Energy-Efficiency Analysis in Wireless Sensor Networks

Short-Hops vs. Long-Hops: Energy-Efficiency Analysis in Wireless Sensor Networks

Mekkaoui Kheireddine (Dr Moulay Tahar University, Algeria) and Rahmoun Abdellatif (Djillali Liabès University, Algeria)
Copyright: © 2014 |Pages: 10
DOI: 10.4018/978-1-4666-4789-3.ch005
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Sensor networks are composed of miniaturized wireless sensor nodes with limited capacity and energy source. Generally, these sensor networks are used, in many applications, to monitor inaccessible environments (battlefields, volcano monitoring, animal tracking…), hence the impossibility to replace or to recharge the batteries. As sensors may be deployed in a large area, radio transceivers are the most energy consuming of sensor nodes, which means that their usage needs to be very efficient in order to maximize node life, which leads us to maximize the network's life. In wireless sensor networks and in order to transmit its data, a node can route its messages towards destination, generally the base station, either by using small or large hops, so optimizing the hop length can extend significantly the lifetime of the network. This chapter provides a simple way to verify, which makes the energy consumption minimal by choosing proper hop length.
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Recent development in Micro-Electro-Mechanical Systems (MEMS) technology, wireless communications and digital electronics have allowed the development of low-cost, low-power, multifunctional sensor nodes that are small in size and communicate un-tethered in short and long distances. These sensors, also known as motes, are generally composed of a power source (battery), a processing unit with limited capacity and a communication component (transceiver) (Gerard, 2008).The deployment of sensor nodes for the monitoring and the detection of different events in the environment is known as Wireless Sensor Network (WSN).

In these last years, wireless sensor networks have been deployed in many applications, to perform the monitoring tasks, like military surveillance, disaster management (Simon, Maroti, Lèdeczi & Balogh, 2004), forest fire detection, seismic detection (Werner-Allen and all, 2006), habitat monitoring, biomedical health monitoring (Lorincz and al, 2004), inventory tracking, animal tracking, hazardous environment sensing and smart spaces, general engineering, commercial applications, home applications (Akyildiz & Vuran, 2010; Sohraby, Minoli & Znati, 2007), Indeed, Business 2.0 lists wireless sensor networks as one of the top six technologies that will change the world, and Technology Review at MIT and Globalfuture identify WSNs as one of the 10 new technologies that will change our life (Imad & Mohammed, 2005).

A wireless sensor network consists of hundreds to myriads of sensor nodes, which appear to be deployed randomly by a car, airplane or a rocket launcher. Each node has a strict limitation in the usage of its electric power as well as computation and memory resources. They typically utilize intermittent wireless communication. Therefore, sensor networks should be well-formed to achieve its purposes and to extend the network life’s; indeed how well the network is formed determines the life of the whole network as well as the quality of data transmission, also the manner to reduce channel contention.

Sensor nodes are, always, endowed by a limited battery power and, generally, deployed randomly in inaccessible fields; which make it almost the time impossible to recharge or to replace the dead battery. So, battery power in WSN is considered as scarce resource and must be used efficiently. Sensor node consumes battery in sensing data, receiving data, sending data and processing data. The most energy-consuming component is the Radio Frequency module that provides wireless communications (Akyildiz, & Vuran, 2010). Consequently, Out of all sensor node operation, sending and receiving data consumes more energy than any other operation. The energy consumption when transmitting 1 bit of data, by a sensor, on the wireless channel is equivalent to the energy required to execute thousands of cycles of CPU instructions (Yick, Mukherjee & Ghosal, 2008). Therefore, the energy efficiency of the wireless communication protocol largely affects the energy consumption and network lifetime of wireless sensor networks.

In the most times, sensor nodes in WSN do not have the necessary power and the communication range to directly send its collected data from the environment to the base station. So, the multi-hops mode of communication, is generally, used to forward data and to reach the base station (Akyildiz & Vuran, 2010), this multi-hop protocol consists to send the data from each sensor to its neighbors, which, in their turns send the data to their neighbors, and so on, until the base station is reached. Hence, a typical sensor node will not only sense and forwards its own data but also have to play the role of a router, i.e. forward the data of its neighbors in the base station's direction, and as discussed above, the two operations of sending and receiving data consume more energy than any other operation. It can be inferred that data gathering and routing are the nucleus area in WSN, where good protocols should be developed in order to achieve optimal energy consumption.

Currently, all modern radio transceivers can adjust their transmitting power (Pesovie, Mohorko & Karl, 2010), in order to reach their closer or their farthest neighbors or relays, so, in WSNs, the base station could be reached with either large number of smaller hops or small number of larger hops both by using multi-hops protocol. Energy efficiency, of these two approaches, is based on:

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