الفهرس 
MOTIVATION
LOCALIZATION TECHNIQUESOnly 14 pages are availabe for public view
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Abstract
Wireless Sensor Networks (WSNs) are composed of hundreds, possibly thousands, of tiny low-cost and smart devices called sensor nodes that are capable of measuring various physical values like temperature, sound, pressure……etc. WSNs can be used in many applications such as smart homes, precision agriculture, environmental monitoring and traffic control ……etc. Localization is a fundamental problem in WSN. Localization means the determination of geographical locations of sensor nodes, consequently detecting the event location and initiating a prompt action whenever necessary. WSN may include in addition to the normal sensor nodes Beacon Nodes (BNs). BNs are expensive nodes relative to the normal sensor nodes. Most of localization algorithms need three or more beacons to estimate nodes location which add cost to the network. As low localization error is desirable many localization algorithms use a lot of BNs and bear this high cost to reduce the localization error. In many localization algorithms localization error is affected directly with number of beacons which add high cost to WSN design. Other algorithms may assume a certain pattern of the WSN that restrict its applicability. After studying many localization algorithms a new algorithm called Beam-width Related Motion (BRM) algorithm has been proposed to enhance the localization accuracy of traditional WSN localization algorithms. The proposed algorithm has the following features; low localization error, low power consumption, and low beacons number. Moreover BRM algorithm can work with both randomly deployed sensor nodes and sensor nodes deployed in a certain pattern. The performance of BRM algorithm has been evaluated with respect to the following parameters: mean error, beam width, power consumption and number of localized sensors. Then BRM results are compared to
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results of an algorithm called Directional algorithm (DIR algorithm) [24]. The results show that BRM has achieved its desired task of achieving high localization accuracy with consuming low energy as BRM average localization error is reduced by 37% compared to DIR algorithm, BRM average transmission energy consumption is reduced by 92.3581% compared to DIR algorithm, BRM average reception energy consumption is reduced by 95.9417% compared to DIR algorithm , BRM overall average energy consumption is reduced by 93.6455% compared to DIR algorithm and BRM average localized nodes number is increased by 0.8904% compared to DIR algorithm. Moreover, in order to achieve better localization accuracy for BRM algorithm, BRM has been modified and called after modification; Two-Phases BRM. Then Two-Phases BRM results are compared to DIR algorithm results. The results show that Two-Phases BRM has achieved its desired task of achieving higher localization accuracy as Two-Phases average localization error is reduced by 66.53% compared to DIR algorithm which is better than BRM before modification.