Energy-Efficient Routing Techniques for Wireless Sensors Networks

Energy-Efficient Routing Techniques for Wireless Sensors Networks

Asmaa Osamaa (Zagazig University, Egypt), Shaimaa Ahmed El-Said (Zagazig University, Egypt) and Aboul Ella Hassanien (Cairo University, Egypt)
DOI: 10.4018/978-1-4666-9911-3.ch003
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Wireless sensor networks (WSNs), which normally consist of hundreds or thousands of sensor nodes each capable of sensing, processing, and transmitting environmental information, are deployed to monitor certain physical phenomena or to detect and track certain objects in an area of interests. The sensor nodes in WSN transmit data depending on local information and parameters such as signal strength, power consumption, location of data collection and accretion. Only reachable nodes are able to communicate with each other directly to collect and transmit data. The motes have limited energy resources along with constraints on its computational and storage capabilities. Thus, innovative techniques that eliminate energy inefficiencies that would shorten the lifetime of the network are highly required. Such constraints combined with a typical deployment of large number of sensor nodes pose many challenges to the design and management of WSNs and necessitate energy-awareness at all layers of the networking protocol stack. In this chapter, we present a survey of the state-of-the-art routing techniques in WSNs that take into consideration the energy issue.
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1. Introduction

The popularity of WSNs has increased tremendously in recent time due to growth in advances made in wireless communication, information technologies and Micro-Electro-Mechanical Systems (MEMS) technology. Sensors networks consist of tiny, autonomous and compact devices called sensor nodes or motes deployed in a remote area to detect phenomena, collect and process data and transmit sensed information to users. The development of low-cost, low-power, a multifunctional sensor has received increasing attention from various industries. Sensor nodes or motes in WSNs are small sized and are capable of sensing, gathering and processing data while communicating with other connected nodes in the network, via radio frequency (RF) channel.

Sensors Networking have profound effect on the efficiency of many military and civil applications such as target field imaging, intrusion detection, weather monitoring, security and tactical surveillance, distributed computing, detecting ambient conditions such as temperature, movement, sound, light, or the presence of certain objects, inventory control, biological detection, smart spaces, industrial diagnostics and disaster management. Deployment of sensor networks in these applications can be in random fashion (e.g., dropped from an airplane) or can be planted manually (e.g., fire alarm sensors in a facility). Initially WSN was developed for military and civilians purpose, now it is extended to wide range of applications (El-said & Hassanien, 2013) such as Disaster management and Habitat monitoring, Target tracking and Security management, Medical and health care, home automation and traffic control, machine failure diagnosis and energy management, Rescue missions, climate change, earthquake warning and monitoring the enemy territory (see Figure 1).

Figure 1.

Overview of Wireless Sensor Network applications

WSN has the potentiality to connect the physical world with the virtual world by forming a network of sensor nodes. Here, sensor nodes are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the network‘s lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization.

Routing in WSNs is very challenging due to the inherent characteristics that distinguish these networks from other wireless networks like mobile ad hoc networks or cellular networks. Presence of large number of sensor nodes and constraints in terms of energy, processing, and storage capacities requires careful management of resources. Due to such differences, many algorithms have been proposed for the routing in WSNs. These routing mechanisms have taken into consideration the inherent features of WSNs along with the application and architecture requirements. The task of finding and maintaining routes in WSNs is nontrivial since energy restrictions and sudden changes in node status (e.g., failure) cause frequent and unpredictable topological changes. To evaluate the performance of different routing algorithms, we have to answer some questions about their efficiency like; how reliable is an algorithm? How efficient does it use resources? And how fast a message can be delivered? This can be quantified by the performance metrics (Misra et al., 2009) that are described in this subsection.

  • Delivery rate is defined as the fraction of successful delivered messages over the total number of messages created at the source node.

  • Flooding rate is used as a measure of communication overhead of multipath and flooding-based strategies. It is the ratio of the number of message transmissions needed by the algorithm and the shortest possible path between source and destination node.

  • Dilation is the ratio of hop count for the given method and the hop count produced by the shortest path algorithm.

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