Abstract: can be controlled by calculating the

Abstract: Area detection and measuring is one of the fundamentalproblems in Wireless Sensor Networks (WSN) because it mainly relates to thecontinuity and functionality of any routing protocol within Region of Interest(ROI).

 While there are holes in the ROI,Field of movement tracking such as that of animals, people and vehicles can’tbe achieved. Also some phenomena such as fire spreading or water flood can becontrolled by calculating the area of the holes, resulting from the damagedsensor networks. In this paper, a new mathematical wireless sensor hole detectionalgorithm (Wireless Hole Detection) WHD is proposed to accurately estimate theexact amount of coverage holes under random deployment of sensor nodes. WHD isdeveloped for achieving Quality of Service (QoS) in terms of power consumption,and average hole detection time. The dynamic behavior of the proposed WHDdepends on executing  the followingsteps. Firstly, WHD algorithm cuts down the ROI into many cells using theadvantage of the grid construction to physically partition the ROI into manysmall individual cells.

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Secondly, WHD algorithm works on each cell individuallyby allocating the nearest three sensor nodes to each of the cell’s coordinatesby comparing their positions, WHD connects each cell’s coordinate points with theselected sensor nodes by lines which constructs a group of triangles, then WHD calculatesthe area of upcoming triangles. Repeating the previous step on all the cells,WHD can calculates and locates each hole in the ROI. The performance evaluationdepends on the NS-2 Simulator  as asimulation technique to study and analyze the performance of WHD algorithm. Resultsshow that WHD outperforms in terms of average energy consumption and averagehole discovery time as compared with Path Density algorithm (PD) and noVel CoverageHole Discovery Algorithm (VCHDA). Keywords:  Wireless Sensor Networks,WSN holes Coverage, Hole detection. 1.    Introduction WirelessSensor Network (WSN) is one of the new technologies for detecting andmonitoring life phenomenon.

WSNs are composed of large number of sensor nodesoperated by small batteries, sensor nodes are mostly deployed in open and unprotectedenvironments. Sensor nodes are limited in communication capabilities and batterypower. Nowadays sensor nodes are deployed in large scale due to rapid technologicaladvances in micro- electro-mechanical systems (MEMS) and low-power wirelesscommunication 1. WSN’s applications are highly varied, such as targettracking, environmental monitoring, and battlefield surveillance. WSN arecomposed of hundreds or thousands of sensor nodes powered by batteries, theyare deployed in open environments to detect and collect information from the surroundedphenomenon 2. Then transmit report messages to a remote base station 3. Variousapplications are dependent on WSNs such as military field exploration, flood ofwater, border protection and forest fires 4, 5, 6.

 WSNshave unique characteristics due to their physical design, such as unreliabilityof sensor nodes, undefined network topology, high computation and communicationpower consumption  and lots of storage difficulties7, 8, So many challenges are presented in the solutions design andapplications development of WSNs. In the real life applications, sensor nodesare randomly scattered over the ROI which allow the presence of some uncoveredareas (Holes) in the ROI which significantly degrade the network performance. Thehole is defined as the area within the ROI that is not covered by any livingsensor. The holes also can be created by the dynamic operations of the sensor nodes.

Sensor nodes usually vanished by impact of random deployment, over heat, movementof animals, vehicles and people accidents. Such failures occur because sensornodes are static nodes and are randomly deployed 9, 10. The failureof any part of the network directly affects the performance of the total networklocally and globally. The presence of holes in ROI definitely affect therouting paths, may cause failure of the routing protocols or separation of thenetwork to many individual small networks. For illustration,the area region that is uncovered by any sensor node is considered as a hole, inwhich events of interest cannot be accomplished. To overcome the holesproblems, the location of the holes and their areas must be determined, also alternativesensors are used respectively to keep the sensor alive as much as possible 11. Therefore, holescoverage and network connectivity are two most important aspects of WSNs 12, 13.            In thispaper, we propose a new wireless sensor holes detection algorithm WHD whichenables the sensor nodes to detect all the holes areas within the ROI, andcalculates the holes areas to help the routing protocol to change its routingpaths or to put extra mobile nodes to heal the holes areas.

The proposed WHDalgorithm uses the advantage of dividing the ROI by using the Grid theory 14to divide ROI into many clusters, and it runs in two phases.·        In phase one: WHD divides the ROIinto many equally cells by using the Grid algorithm, then it stores the exactlocation of the four edges of each cell to use them in calculating the holesarea.·        In phase two: WHD algorithm workson each single cell individually by determining the coordinates of its four edgepoints and the coordinates of the nearest three (if possible) nodes to each cell’sedge points, then WHD determines if the ranges of the selected sensor nodescover the cell’s edge point, if not means there is a hole and WHD begins tocalculate the hole area and its position, yes means that the sensing range ofthe sensor nodes cover this coordinate point so there is no hole in that regionof the cell. Figure 1 shows how WHD determines the presence of a hole in a cell.       The rest of this paper is organized asfollows: Section 2 presents related work. Section 3 presents the contributionsof the research work.

Section 4 describes the modeling assumptions and problemgoals. The Proposed WHD Algorithm is described in detail in Section 5. Section 6represents the performance evaluation and the simulation results. Conclusionand future work are presented in Section 7.


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