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A Wireless Sensor Network (WSN), a spatially distributed network, consists of tiny devices called “sensor nodes” also referred to as “Motes”. A Wireless network’s success is attributed to its monumental advancement in processor power, communication and usage of low power embedded computing devices. Sensor nodes (Ann Holms et al., 2006) are used to monitor environmental conditions like temperature, pressure, humidity, sound, vibration, position etc. The focal characteristics of sensor nodes are energy efficiency, low power consumption, small size, multi hop communication, adaptability over a network, self-configure mode etc. In real time, sensor nodes are more constrained in terms of computational energy and storage resources. Factors such as accuracy, reliability, physical parameters and real time constraints are the important restraints for the design of sensor node and network.
Sensor nodes are equipped with four broad units namely sensing, processing, communication and power management (Holms et al., 2006). Each and every node has the ability to perform data gathering (Tharini et al., 2010), sensing, processing and communication. The sensing unit perceives the environment, the processing unit computes the limited permutations of the sensed data, and the communication unit executes exchange of processed information among neighbor nodes. Sensing unit integrates data from different types of sensors like thermal sensors, magnetic sensors, vibration sensors, chemical sensors, bio sensors and light sensors. The parameters measured by the sensors are fed into the processing unit which is the core of a sensor node.
In the processing unit, selection of processor/controller is the key, as it controls WSN’s development in spheres of cost, flexibility, scalability, ease of programming and low power consumption (Gholamzadeh et al., 2008). This central unit executes different tasks and controls the functionality of other components. The required services from the same are pre-programmed and installed into the processor. The energy utilization rate of the processor varies depending upon the nodes. The performance variation of the processor is identified from evaluating factors like speed, data rate, memory and peripherals supported by it. ATMEGA 128L, MSP 430 controllers are used popularly in motes (Healy et al., 2008). The computations are performed in the processing unit and the acquired result is transmitted to the base station through the communication unit.
In communication unit, a common transceiver acts as an exchange unit to facilitate transmission and reception of information amidst the nodes and base station. Radio frequency (RF) is mainly used for node-to-node communication since it does not require any line of sight (LOS). The four states in the communication systems are transmit, receive, idle (Ready to receive) and sleep (a function to switch off hardware thereby saving energy). These states are used to enhance the overall performance.
A sensor node is identified for WSN based on the parameters like computation rate, processing speed, storage, communication range (Healy et al., 2008). Relay node is an intermediate node assisting communication with the adjacent node. Actor node resolves actions depending upon the environment. It facilitates remote and automated interaction. Actor (Akyildiz et al., 2004) and Relay nodes are resource-rich devices. They are furnished with good processing capabilities, higher transmission powers and greater battery life. Sensor nodes (Tapia et al., 2009) are clustered along with a gateway; relay and actor nodes (Zhang et al., 2010) within its communication range and thus establishes the WSN. Cluster is nothing but a collection of sensor nodes in that particular sensor field. A typical WSN comprises of many clusters.