Hybrid Approach for Detecting and Healing the

Coverage-Hole in Wireless Sensor Network

Nikitha Kukunuru

Asst. Prof., CSE Department GITAM University, Hyderabad

Andhra Pradesh, India

Dr. Davuluri RajyaLakshmi Professor of CSE Department

JNTUK, Vizainagaram Andhra Pradesh, India

Dr. Avula Damodaram Professor of CSE & Director,

Academic Audit Cell JNTUH, Andhra Pradesh, India

Abstract- The foremost functionality of the Wireless Sensor

Network (WSN) is monitoring of the given target field. The

formation of holes in the target field is quite common and is

unavoidable due to the nature of the WSN, and random

deployment. On the other hand, it is very important to ensure

that the target field is completely and continuously covered. VorLag technique and Virtual Force Algorithm are the two main

approaches that detect and repair the coverage hole formed due

to random deployment. There are some drawbacks in each of

these approaches. This paper proposes an approach called the

Hybrid Hole Detection and Healing (HHDH) taking the

advantages from VorLag and Virtual Force Algorithm to detect

and heal the coverage hole effectively with minimum sensor

movements. The proposed HHDH uses a VorLag approach for

detecting and Virtual Force Algorithm for healing the coverage­

hole formed due to random deployment. A special feature of the

HHDH is that it deploys a Hole Healing Controller (HHC) and

determines the Hole Healing Region (HHR). The determination

of the HHR assists the HHC in selecting an appropriate node for

the healing process. Only nodes that are located in the

appropriate locations are involved in the healing procedure. HHDH is a distributed coverage-hole healing algorithm that

outperforms the existing VorLag and Virtual Force Algorithm.

Keywords-Wireless Sensor Network, Coverage Hole, Hybrid

Coverage-Hole Detection and Healing, Virtual Force Algorithm.

I. INTRODUCTION

A Wireless Sensor Network (WSN) comprise of tiny sensors with constrained computational and communication power. WSN is an autonomously distributed network that has several real time applications like military security, environmental monitoring, industrial process and health monitoring, agriculture and farming, and location tracking [1] [2]. The sensed data can reach its target, fulfilling the application requirements, provided the area sensed by the sensors has no coverage holes. Due to random deployment or energy exhausting, various classes of holes will appear in WSN that results in coverage holes, jamming holes, and routing holes.

For a given set of sensor nodes and a target region, if each position in the target region is not covered with at least 'n' sensor, it would result in the coverage-hole in which 'n' is the minimum scale of coverage required for a specific application. The coverage hole becomes an issue only if the coverage does

978-1-4799-3140-8/14/$31.00 ©2014 IEEE

not meet the application requirements; i.e., coverage-hole issue is dependent on application requirements [3]. The formation of coverage-hole is shown in "Fig. 1". This paper focus on detecting and healing the coverage hole formed due to random deployment, energy depletion and physical damage of the sensor nodes.

Fig. I. Coverage Hole

In the past few years, an extensive study of the coverage issues in WSNs was made. Most of the approaches are based on geometrical tools like Voronoi diagram and Delaunay triangulations, to find out the coverage-holes [4] [5] [6]. These techniques depend on the accurate location information about the sensor nodes. The process of obtaining the exact physical location information is either expensive or not viable in many applications. This paper combines the concept of virtual force algorithm with the Vorlag approach.

The main contributions of this paper are as follows:

110

• The major contribution is to maximize the sensing coverage in the heterogeneous network using VorLag diagrams and virtual forces resulting in a hybrid approach that takes the advantage of both these schemes.

• This paper proposes a hybrid model to heal the coverage hole formed due to the energy depletion using the VorLag diagram and virtual force that has very low computational complexity. The VorLag diagram detects the coverage hole and virtual force assists the movement of the sensors in healing the coverage hole. This work avoids the major

drawbacks of the earlier systems using virtual force algorithms and VorLag.

• The Hybrid Hole-Detection and Healing (HHDH) works in two distinct phases. The first phase of the approach uses distributed hole-detection algorithm by constructing the VorLag polygon. HHDH has very low complexity and deals with holes of different sizes regardless of the node's density and distribution.

• The second phase deals the coverage hole healing with a fresh notion called coverage hole healing region (HHR). This phase initially determines the HHR and then relocates the nodes. This approach proposes a virtual force-based local healing approach based on the HHR, in which the forces will be effective. This work also deploys a Hole Healing Controller (HHC) that heals the coverage-hole locally in which only the nodes located at a suitable distance from the hole will be selected for the healing process. This hybrid approach heals coverage holes using appropriate nodes in minimum time with low power consumption.

II. RELATED WORKS

An approach in [7] called VorLag, which a simplified form of Voronoi based on the Laguerre geometry, ensures better coverage in the heterogeneous network. It effectively manages the coverage hole formed due to random deployment by exploiting the movement of the sensor of empty polygon. The approach in [8] has suggested two techniques for solving a single coverage problem based on the equilibrium of molecules that minimizes the molecular energy and inter­nuclear repulsion and exploits the nummum energy consumption feature of the clustering process.

The idea in [5] exploited Voronoi construction to identify and heal the coverage-hole. This process utilizes Vector, Voronoi and Minimax based deployment protocols. These protocols depend on the sensor's mobility from a densely to sparsely deployed region. The distributed algorithm in [4] detects the boundary of the coverage hole that results in the formation of new routes. This technique forms an alternative path to the target, but does not attempt to heal the coverage hole. This approach used a heuristic technique for detecting coverage holes that depends on the node's position over the communication graph. The idea in [9] depends on the triangular holes using Rips complex. They accurately evaluate the size of the triangular holes and use a linear-time algorithm for detecting the coverage hole. It does not produce better results in a sparse network scenario. An approach in [10] suggests a Virtual Force, if the distance between two nodes is too close, exerts a repulsive force. In contrast, if the distance between two nodes is too large, exerts an attractive force.

In the VorLag approach, the energy depleting sensor relocates itself using a sensor of null polygon or alternate sensor. By doing so, the depleting sensor depletes its energy quickly. Moreover, in the VorLag approach, the nodes move

independently without considering the movement of the other nodes that will not help in healing the coverage hole. Several earlier works used virtual force between two sensors to heal the coverage hole. The sensor moves only if the resultant local coverage increases by its movement from the current location to the target location. If there is no improvement in the local coverage, there is no use in moving the particular sensor. Even if the sensor moves in accurate directions, it could not offer improved coverage all the times as the target location may be too far away from the current location. Though virtual force rearranges the sensor's position based on the distance between them, it does not support sensor heterogeneity and consumes more time to converge.

III. HYBRID ALGORITHM FOR HOLE-DETECTION AND

HEALING IN THE HETEROGENEOUS WIRELESS SENSOR NETWORK

This section presents a hybrid algorithm for healing the coverage hole in the heterogeneous wireless sensor network. It detects the coverage hole using Vorlag construction [7] and heals the coverage hole using Virtual Force Algorithm [11].

A. Detection of coverage holes using VorLag construction

1) Coverage-hole identification

The Laguerre-Voronoi diagrams (VorLag) are formed by the portions of straight lines that are perpendicular to the line segments connecting the centers of the corresponding generating points. Laguerre geometry supports the construction of VorLag diagram, especially in constructing the radical axis. VorLag is an effective choice as it generates straight edges rather than complex curves. It accurately divides the target area into two planes based on the location and sensing radius of the sensors. Among those two planes, the meeting point of all the left over half planes forms the Voronoi-Laguerre polygon of the sensor and the other is eliminated. VorLag polygon encloses each sensor in the network and together covers the target region. Each point in the polygon is closer to the sensor inside its polygon than any other sensor in the network. Each sensor is accountable for coverage issues in its own VorLag polygon. Special cases of VorLag construction are null polygon and empty polygon. The empty polygon does not contain the center of its generating circle (sensing range). If the sensing range of the sensor is completely overlapped with another sensor, it is null polygon.

Each sensor iteratively constructs its VorLag polygon based on the radical axis constructed with its neighbors. Each sensor maps its polygon area with its sensing area. The uncovered region is described as "coverage-hole". In this manner, each sensor determines the coverage-hole locally, and if necessary it monitors a small region around it. The construction of VorLag polygon mlrumlzes the communication complexity as the sensors need to know only their VorLag neighbors. The construction of VorLag polygon may result in the sensors of empty and/or null polygon. The polygon of a sensor is said to be null if the sensor has no polygon. This occurs if the sensing range of a sensor is fully included in the common area of the sensing ranges of other sensors. In this scenario, the movement of the sensors does not improve the local coverage. Therefore, it should wait till it

2014 International Conference on Signal Propagation and Computer Technology (ICSPCT) 111

gets a place to move. There is another category called the sensor of an empty polygon in which the center of the sensor may be situated outside its polygon. In this scenario, even if the other sensors completely cover the polygon, the sensor ensures better coverage in the target field by moving towards its own polygon.

The sensor with an uncovered region in its polygon is called trapped node. Each trapped node sends hole-detected (HD) messages to another trapped node without any synchronization. This process discovers the hole in a redundant manner, generating unnecessary traffic and packet collision. A node considers the HD packet as redundant and deletes it only if it receives the HD packet with the Hole_ID greater than the Hole_ID carried by a packet previously passed. A node with the least Hole_ID eliminates the HD packet, and labels it as a Hole Healing controller (HHC). HHC is completely responsible for broadcasting the announcements necessary for the hole - healing process. The nodes also share their residual energy level periodically.

2) Coverage Hole-Border Detection

The construction of Laguerre Voronoi diagrams is based on portions of straight lines that are perpendicular to the line segments joining the centers of the associated generating points. The VorLag diagram partitions the target field into several polygons; each of them corresponds to its generating sensor. In this approach, each sensor exploits the information related to VorLag polygon construction to detect the coverage hole. Sensors broadcast hole-detected (HD) messages locally and wait till it receives a message back. At every hop, the direction of the HD packet gives the previously trapped node that forwards this packet. Each hole-border node is considered as a vertex of an irregular VorLag Polygon that forms the boundary of the coverage hole.

B. Coverage-hole healing using virtual forces

At the end of the hole-detection phase, the hole-healing phase is executed. The hole-border nodes play a vital role in healing the coverage hole formed by the energy depletion of the nodes using selective virtual forces. To overcome the drawbacks of the existing approaches using the virtual forces, this work deploys the HHC to maximize the local coverage and exploits the node's mobility to heal the detected holes. This hybrid algorithm is distributed and developed on the basis of VorLag and selective virtual force. There are two kinds of forces called attractive and repulsive. An attractive force acts from the center of the hole that attracts the nodes towards it. Similarly, the repulsive force separates the two sensors that are too closer to maximize the coverage locally. To overcome the drawback in using the virtual forces, this approach defines a region called Hole-Healing Region (HHR) in which the forces will be more effective. This enables a local healing where only the selected nodes located at a suitable distance from the hole will be moved.

1) Determination of HHR

The main purpose of determining HHR is to find out the number of nodes necessary to heal the coverage hole locally. After the detection of the coverage-hole by VorLag algorithm, HHC node determines the coverage-hole size. The hole is a circle with a radius of the longest distance between two boundary nodes, represented as RH. It is necessary to determine the radius of the circle that corresponds to HHR. This approach uses an iterative approach to find the appropriate radius of the HHR, RHHR.

(1)

K is a constant that depends on the sensing range (RS) and

the node density (0). Let K=O be the starting point that equals the estimated RH as this region may contain adequate number nodes required for healing the hole. The area defined by this circle, HHRO becomes 1t RH2. The required number of nodes that covers the region of HHRO is given as:

(2)

The HHC node estimates the number of nodes present in HHRo. HHC requests its one-hop neighbors to estimate their one-hop neighbors in this area. HHC broadcasts Hole-Healing Region Estimation (HHRE) packet containing information about the hole. If the number of nodes estimated by the HHC is less than the required number to heal the hole, the movement of these nodes will form new holes. To avoid the formation of the new hole, HHC starts a new round of estimating the neighboring nodes by increasing the value of K. This process is repeated till it finds the adequate number of nodes required to heal the hole. The sensors of empty and null polygon are given higher priority among the estimated nodes. After estimating the HHR, the HHC sends the START_MOVE packet containing information about the hole to the concerned nodes. The nodes that receive the START_MOVE packet will enter into the node replacement phase.

2) Node Replacement Phase The HHC sends START_MOVE packet only to the

particular nodes among the HHR. If the hole center exerts a force on another node, the node should move towards the hole center. This phase is a prioritized node replacement phase; movement of sensors of empty and null polygon is assigned a higher priority in the hole-healing process.

a) Impact of attractive force

The hole center He exerts an attractive force on each node in HHR. If it is located at a distance greater than the threshold distance, DTHR from He, node M in the HHR experiences an attractive force from He, V[FA (M, Hc)] (V represents the vector form) and is given by:

112 20 J 4 International Conference on Signal Propagation and Computer Technology (ICSPCT)

OeM, He)<p(A) V[FA (M, He)l=

0,

In (3), V [uAl is the unit vector originated from the point M to He. OeM, He) is the Euclidean distance between M and He. <peA) is the distance co-efficient and FA(I) is a co-efficient representing the intensity of the attractive force. The exponential factor controls the movement of nodes in the HHA.

OeM, N)<p(R) V[FR (M, N)l=

0,

In (4), UR represents the unit vector originated from node M to N. FR(I) is a factor that corresponds to the intensity of the repulsi ve force and <p(R) is the di stance

c) Movement prediction

The ultimate position of a node M is the resultant force of the repulsive forces that sustained the node M from its collection of neighbors (Ne) and the attractive force from the coverage-hole center. This resultant force is denoted as V[FMl and is expressed as shown in (5).

V[FMl = L V[FA (M, He)l + V[FR (M, N)l (5)

With this information, the magnitude and direction of V[FMl can be easily computed. If V[FMl =0, the node M remains in its current position. Otherwise, the node M should move one time step in the direction indicated by the V[FMl. The ultimate position of node M is given by:

V[Mp (t+�t)l = ____ * v + V[Mp (t)l (6)

In (6), v denotes the node velocity and V[Mp(t)l is its position at instant 'r'. The existence of a coverage-hole upon the termination of the healing process can be checked to ensure the accuracy in the coverage-hole healing process. If a coverage-hole is detected, the healing process can be triggered for the second time.

OeM, He) > OTHR(A)

OeM, He):::; OTHR(A)

b) Impact of repulsive force

(3)

If two nodes are too closer than the required overlap, there exists a repulsive force, V[FRl in the range of 0 < V[FRl < OTHR(R). If the distance between two nodes M and N is less than OTHR(R), then V[FR(M,N)l will detach these nodes to reduce the overlapped coverage. V[FR(M,N)l is indirectly proportional to the O(M,N) and is given by:

OeM, N) > OTHR(R)

OeM, N):::; OTHR(R)

d) Healing of multiple coverage-holes

(4)

The proposed HHOH can deal with more than one coverage-hole simultaneously over the network. HHOH can detect multiple holes using the same procedure as discussed in the previous section. However, several HHRs may overlap and hence, control the node in the overlapped area using more than one HHC. In this case, the movement of such nodes can be determined using two strategies, namely, the distance based and hole bashed. In the distance based strategy, the distance traversed by the nodes during the healing process is minimized. A node reacts only according to the first START_MOVE packet that it receives. In the hole based strategy, if a node receives the START_MOVE packet, it waits for a predefined time. After that period, it compares the received START_MOVE packets and moves towards the largest hole. This strategy prioritizes the healing of large holes hoping that the large holes would result in a serious impact on the system performance than the small holes.

1* HHDH algorithm *1 Coverage-hole identification //lnitialization

Start VorLag construction 0 /lCoverage-hole detection If (trapped node=l) {

Create and Send the HO Packet to next hop Else

No movement; }}

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IINode receives HD packet Receive_HD_packet 0 { If (trapped node=1 && Hole_1O <10 (HD_packet» {

Disregard HD_packet; IISelection of HHC

Else { Select a node with least Hole_ID as HHC

If (Hole_1O =10 (HD_packet» { If (bordecnode = 1)

Halt 0; Else {

IIHole radius and hole center evaluation Compute RI\ and Hc;

Call senchealin�packet 0; }} Else {

Forward HD_packet; }}} Coverage-hole Healing

IIHHC determines HHR IINode has a healing packet to send Senchealing_packet 0 IIDetermination of HHR {

Call compute_RmlR 0;

Generate and send a healing_packet; Wait (to); Call Heal 0; }

compute_RHHRO {

RHHR = RH * (1+ K); } IINode receives a healin�packet Receive_healing_packet 0 { If (node's position is in HHR)

Forward the healing packet to its neighbors; Wait (tl); II checking for multiple holes Generate and send a reply_packet to the HHC; }

Heal 0 IlHeals the coverage hole { If (the number of neighbor nodes is sufficient) Generate and send a START_MOVE_packet; Else Call senchealing_packet 0; } Healing Process: Node Replacement phase Receive_START_MOVE_packetO II Healing process { Forward START_MOVE_packet; Call move 0; } Move 0 II Move the nodes virtually { Compute V[FA (M, HC)]; Compute V[FR (M, N)];

Compute V[MP (t+dt)] Replace node M to the new position;

Fig. 2. HHDH Algorithm

IV. PERFORMANCE EVALUATION

The simulation scenario consists a random deployment of 100 to 600 heterogeneous sensor nodes in the target field of 500 m X 500 m. The communication radius of each sensor is Ii mited to 50m, and they move wi th the speed of 1 ms-I. The resultant value of 10 simulation runs is plotted as the

simulation results. Since, it is designed for heterogeneous sensors; this paper sets the sensing range of every sensor to a random value in the interval [1-5m]. The simulation runs for 500 seconds.

This paper compares HHDH with the VorLag and Parallel and Distributed Network Dynamics (PDND). PDND [12] is a deployment algorithm based on the virtual forces. This paper modifies some of the features of PDND so that it could support heterogeneous sensors and/or sensor deployment of varying density. The simulation results show that HHDH ensures better local coverage compared to VorLag and PDND.

A. Simulation Analysis

1) Coverage percentage The "Fig. 3," shows the percentage of the region covered.

In all the techniques, coverage increases with the increase in the number of sensors and maximum coverage is attained in the presence of an adequate number of sensors. HHDH will detect coverage holes and heal some of them as the node density is not adequate for a complete healing in some cases. However, if the node density increases, the performance level of HHDH also increases. In this case, the process of healing becomes more effective with high node density. POND comparatively achieves low coverage as there are huge overlaps of the sensing circles resulting as a consequence of the virtual force concept. The performance of HHDH outperforms those of VorLag and POND.

Fig. 3. Comparison of coverage percentage

2) Moving Distance The "Fig. 4," demonstrates the average distance

traversed by a sensor during the coverage-hole healing process. HHDH enables the sensors to heal the coverage-hole by traversing a shorter distance compared to VorLag and PDND. The distance travelled by nodes increases with the increase in the node density. This is because HHDH detects a significant amount of coverage - holes and attempts to heal them. Compared to VorLag and PDND, the distance moved in HHDH is much lower. In POND, the traversed distance decreases with high density. This is due to the weak inter­nodal force and hence, the replacement of nodes is small and even results in poor coverage.

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100 200 300 400 500 60040

50

60

70

80

90

100

Number of sensors

Cov

erag

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Fig. 4. Comparison of moving distance

3) Number of movements From the "Fig. 5," it is clear that HHDH and VorLag

achieve nearly same level of performances with respect to the number of movements. PDND provides better coverage only after an excessive number of movements. HHDH outperforms the VorLag and PDND as the HHDH enables only the selected nodes for healing the coverage-hole in the determined Hole­Healing area. The only selected nodes are involved in the hole healing process that can heal the coverage-hole with the least number of movements.

Fig. S. Comparison of number of movements

V. CONCLUSION

This work proposed a distributed HHDH algorithm for detecting and healing the coverage-hole formed due to the random deployment in the WSN. By exploiting the advantages of VorLag construction and Virtual Force Algorithm, the proposed hybrid algorithm, HHDH ensures better coverage with low moving distance and number of sensor movements. The HHDH achieves this by detecting hole-border nodes and deploying HHC. Each HHC determines the HHR that finds an

adequate and appropriate number of nodes required to heal the coverage- hole. HHDH also suggests hole-based and distance­based strategy to heal multiple holes. The proposed HHDH outperforms the existing works in terms of moving distance, coverage percentage, and the number of movements.

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