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Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor’s current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm’s performance and the effect of number of targets on the resulting subset.

Wireless multimedia sensor network (WMSN) [

One of the most important issues in WSN is sensing coverage, which is also measurement for service quality in WSN [

In this paper, the coverage expectation value from node to target is delineated through probabilistic models of FoV disk, which is the ground for self-direction wireless multimedia sensor node and better coverage of target. The optimization algorithms for single-node single-target, multinode single-target, and single-node multitarget are given to solve the coverage problem. Also, the self-directed direction of target covered by FoV disk for every node is set as candidate sensor direction. Genetic algorithm is used to discriminate the self-directed coverage optimization in multinode multitarget circumstance and to discover the minimum set of nodes for coverage of all targets.

Coverage issue of randomly deployed sensor node is the hotspot in this field. In traditional WSN, most researches hypothesise that the omnidirection sensor node which covers area is a circle with its center in node. But, in WMSN, the sensor cover area is usually hypothesized as sector, which is not applicable for traditional coverage algorithm [

New distributed algorithm has been raised after research in self-directed WMSN [

In target coverage problem of directional sensor network, the direction and rotation of angle in node directional compensation were not considered [

The network field in our research is two-dimensional Euclidean field with randomly distributed multimedia sensor nodes and a certain number of interested targets, which means that the sensing direction and position of all nodes are random and independent. The same as the hypothesis in recent study [

In a WMSN,

2D FoV: 2D FoV is a directional sensing area of multimedia sensor node, which is hypothesized as a proximate sector in two-dimensional space (Figure

2D FoV sensing model.

2D FoV disk: the 2D FoV disk of multimedia sensor node is defined as a set of all possible 2D FoV of node, which should be a round area with radius as

FoV disk model.

Target coverage of multimedia sensor node

Expectation value of multimedia sensor node to target

At first, single-node single interested target coverage, the simplest circumstance, is discussed. The hypothesis is that interested target was located in FoV disk of node but not covered by node, which needs self-directed adjustment to be covered (Algorithm

Input: multimedia sensor node

Output:

Define Rotate Direction; // rotated direction of node, value as CLOCKWISE or ANTICLOCKWISE

Define Rotate Angle; // rotated angel of node

Calculate

IF

END

IF

ROTATE(

RETURN

The problem of multinode single-target self-direction is existence of multiple multimedia sensor nodes. The hypothesis is that interested target is not covered by any node while all nodes can cover the interested target through self-direction. According to the coverage expectation value

Input: set of multimedia sensor nodes

angel

Output:

Define

Define RotateDirection;

Define RotateAngle;

Let

Let

FOR each

Calculate

IF

END

END

IF

RotateDirection = anticlockwise;

RotateAngle =

END

IF

RotateDirection = clockwise;

RotateAngle =

END

ROTATE(

RETURN

The problem of single-node multitarget direction is how to cover maximal interested targets in node self-direction in the circumstance of multiple interested targets randomly located in FoV disk of some node (see Algorithm

Input: multimedia sensor node

Output:

Define RotateDirection;

Define RotateAngle; // rotated angel of node

Const

Let

Let

Let

FOR each

END

Sorting TSC from minimal to maximal;

Calculate the difference absolute value between every two elements in

absolute value less than or equal to

All elements, which numerical of every line is 1 in top triangle of Matrix

with absolute value less than or equal to

Chose the line with maximal numerical equal to 1 in top triangle of Matrix

corresponding nodes into set

Form subset

Calculate the mean of maximum and minimum in

IF

END

IF

END

ROTATE(

RETURN

The problem of multinode multitarget self-directed coverage optimization in WMSN is how to find the minimal node set

Node

The multinode multitarget self-directed coverage optimization can be described as follows:

To be described more vividly, a dilatation figure of multinode multitarget self-directed coverage optimization based on simple example in Figure

A trinode tri-interested target multimedia sensor network.

Dilatation figure of Figure

Genetic algorithm is used. According to the methods used in [

Input: dilatation

Output: subset of self-direction action(ROTATE)

randomly chose a self-direction action for every node and denote it as

Let

WHILE(every target

END

RETURN

Random algorithm showed in Algorithm

Input: dilatation

Output: minimal node set contented to target optimization

MAXGEN = 100; //maximal genetic algebra;

GGAP = 0.9; //generation gap;

trace = zeros(MAXGEN, 2); //initiate value of genetic algorithm ability tracking;

Repeatedly run algorithm in Algorithm

Chrom =

gen = 0;

ObjV = Target(Chrom); //calculate target function value (number of nodes) of initiate group;

WHILE gen < MAXGEN

END

RETURN minimal node set which can cover

Simulation analysis is performed to multinode multi-interested target self-direction optimal coverage discriminate algorithm based on genetic algorithm [

Stability of algorithm.

Figure

Optimal solution of target function and ability tracking of algorithm.

10 interested targets

20 interested targets

30 interested targets

Relationship between number of interested targets and optimal solution of target function.

In this paper, the factor of rotation angle, rotation direction, and distance between node and interested target when multimedia sensor node self-directed cover interested target in self-directed MSN is discussed. Also we investigate single-node single-target, multinode multitarget, and single-node multitarget self-directed coverage optimization, so node can self-direct in maximal coverage expectation value, which means covering more closer targets with lesser rotation angle. For multinode multitarget self-directed coverage optimization, the hypothesis that all nodes have fixed sensing direction in literature [

The authors declare that there is no conflict of interests regarding the publication of this paper.

Foundation item: This paper is sponsored by Qing Lan Project and the National Natural Science Foundation of China (nos. 61170065, 61373017, 61171053, 61103195, and 61203217).