Green Computing in Wireless Sensor Networks through Energy-Efficient Techniques for Lifetime Improvement

Introduction

The technological advancement in wireless communication has led to the development of wireless sensor networks (WSNs). With the exceptional capability of not only sensing but processing, WSNs became popular and very much required for many applications. Sensor nodes are small and are deployed in the monitoring area in large amount to detect events. But they are resource constrained. They are tiny nodes with low-cost processor, limited storage capacity, limited transceiver range and limited battery lifetime. Sensor nodes sense the monitoring area such as forests, fields, underwater areas, cities, human body, etc. and transmit the sensed data to the sink. This transmission may take place via single hop or through multi-hops. In single-hop networks, nodes can directly send data to the sink. But generally, a sensor network field is large and the node transmission range is limited, so the nodes may send data to the sink via intermediate nodes or forwarding nodes, which is called as the multi-hop network [1]. In single hop, sensor nodes deplete their energy due to direct data transmission, whereas in a multi-hop, the forwarding nodes deplete their energy and reduce the network lifetime. The lifetime of sensor nodes mainly depends upon a finite source of energy like battery. Therefore, it is crucial to consider the energy-efficient techniques to increase the life span of the network and consequently their role in green computing.

Taxonomy of Energy-Efficient Routing Protocols

There are a few common requirements of sensor networks for all types of applications in WSN, which are given as follows [2]:

  • 1. Network lifetime - Nodes are deployed in an unattended environment; therefore, it is required to conserve energy of nodes and prolong the network lifetime. If a network fails due to energy depletion of nodes, communication failure occurs.
  • 2. Network size - Sensor nodes are deployed in a large network area to detect more events. A large coverage area is the interest of most applications.
  • 3. Minimum faults - Data packet may be lost in transmission of data to the sink. Many events may be missed, and monitoring of environment is broken. Data reliability is the major concern of applications.

The sensor nodes are generally deployed in an inaccessible area. These sensor nodes are limited in battery power, and replacement of batteries is not an easy task in remote areas. The major challenge is to keep the network alive. A limited battery power makes it difficult to manage and monitor the network. Therefore, it is required to conserve the node energy in order to increase the network life span.

Various sources of energy dissipation, which we have already discussed in the previous chapter, are idle listening, collisions, over-hearing, over-emitting, etc.

Energy Conservation Techniques

Various ways for conserving energy are discussed in Ref. [3], which are given as follows:

1. Sensor nodes consume equal amount of energy in ready mode as well as in receiving mode; therefore, sleep mode and a wake-up schedule must be set for event sensing to save energy. The idle scheduling time depends on the network traffic.

  • 2. To conserve the energy in WSNs, the sensor network nodes use data fusion. Using data fusion, the amount of data transmitted from sensor nodes to the base station is reduced. Data fusion combines one or more data packets from different sensor nodes to produce a single packet. Also, data must be aggregated to reduce the transmission load. Sensor network is divided into clusters. Member nodes in the cluster send the data to the cluster head (CH), where the data is aggregated and data fusion takes place.
  • 3. In WSN, data processing is much cheaper than data transmission. Data compression performed through various algorithms saves energy.
  • 4. In a clustered network, CHs aggregate the data and transmit it to the base station (BS). The responsibility of a CH node is more as compared to the member nodes in the network. Therefore, CH consumes more energy or dies quickly in a homogeneous network. The communication load must be balanced to increase the lifetime of the network. Load balancing technique equally distributes the traffic load in the network, and a good network performance can be attained. Load balancing of CHs can be achieved through a random rotation of CH. It can also be achieved via appointing advanced nodes as CH in a heterogeneous network as they have more battery power.
  • 5. By lowering the transmission range, the energy can be conserved, but network coverage is still required. Therefore, a mechanism that takes care of transmission range as well as coverage of network is needed. Heterogeneous sensor networks consider the concept of remaining energy and distance [4].

There are different layers which work in their own way to achieve energy efficiency.

 
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