Problem Is One Of Fundamental Issu Computer Science Essay

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Coverage problem is one of the fundamental issues that arise during the implantation of the network, which reflects how well sensors are monitoring. The ratio of total area covered to the total intended coverage area is called coverage ratio. Network Coverage Quality can be measured as the time from the construction time of the network with particular coverage ratio to the time up to that the intended area is covered with same coverage ratio.

Quality of Service of the sensor network is identified by its network coverage metrics. Similarly, individual sensor nodes quality and capacity is measured by its coverage metrics. To increase the lifetime of network, sensing unit of sensors are controlled using power management techniques by switching ON or OFF. Many protocols are used to minimize the coat and maximise the coverage area in the wide area network.

Based on the entity to be covered using the network, coverage have been categorized with respect to Area, Target and Barrier. Area Coverage aims to cover the entire intended area; Target coverage concerns about particular predetermined points in the area whereas Barrier coverage about moving objects.

The most important problem in coverage of the sensor is how to prolong the network lifetime with less energy spent. Based on application specific problems clustering and scheduling mechanism are widely used. Network Clustering divides nodes into clusters that depend upon the applications or protocols. Cluster Head (CH) is chosen among the sensor nodes based on some criteria such as node's remaining energy, coverage ratio of the node, number of nodes within its communication range and distance between them and the Base Station (BS). In most of the applications, Clusters members (CM) are having minimum overlapping coverage with other nodes. To maintain the balanced energy consumption of the network, even sized clusters are formed but in no uniform distributed network, it is not possible. To equalize the level of energy, intra and inter cluster techniques are used. In sensor scheduling, only some group of nodes are to be started for sensing and the others in the clusters are to be kept in sleep mode for reducing the energy consumption. Though limited numbers of sensors are sensing the area, it should be same as the one covered by all the nodes in a cluster. In some cases, instead of clusters, multiple subsets of sensor nodes are formed for sensing the network and by applying some routing techniques, the sink node gathers the sensed data from those subsets.

Various routing techniques are used to find out the routing path to the base station for forwarding the sensed information. In clusters, using single-hop or multi-hop communications CH gathers the sensed data that should be forwarded by the neighbouring cluster heads to the base station. Routing path is to be selected which consumes minimum amount of energy for data transmission.

Now-a-days Wireless Sensor Networks (WSNs) are used widely due to the efficiency for performing several tasks such as examination, ecological observing, and engineering applications. Clearly, for efficient wireless sensor network, we have to concentrate on energy utilization and coverage life span.


Sensors are less expensive, limited-power devices which are used to convert the physical stimulus such as temperature, aquatic and acoustic into the recordable signals. The fundamental component of sensor network is sensor node or motes is which naturally includes several units for power, sensing, processing or microcontroller, a storage, and communication. A node is categorized into normal sensor node and gateway sensor node. Normal sensor node is deployed for usual sensing purpose and the Gateway sensor node is acted as an crossing point between the network and the world. Sun Microsystems developed a sensor node as SunSpot (Sun Small Programmable Object Technology) for indoor environmental quality measurement which is fitted in the palm of the hand. It is having 180MHz 32 bit ARM 920T core and automatic battery management. Group of sensor nodes forms a sensor network which monitors the physical phenomena of a particular area or field.

A sensor network not only contains the sensor nodes but also has one or more sink nodes. Nodes in a network consecutively examine the environment and produce the data. A sink node takes the responsibility to accumulate the information from the senor nodes in the network which does not produce any data by itself. Sink node is acted as a gateway. Sink node is having more energy than the other nodes in the sensor network along with advanced computation capability. Fig 1.1 shows the simple view of sensor node.

Microcontroller Unit

It is the central part of a node which gathers and processes the sensor unit's data and decides transmission and response of data. A microcontroller can be executed either by an application-specific integrated circuit (ASIC) or by a reduced instruction set computer (RISC) architectures running on some operating systems like TinyOS. Normally, it can operate in various modes for saving the energy by switching on or off some parts of the controller. It is represented as different modes. Widely used microcontroller is SA-1100TM model of the Intel StrongARM.

Memory Unit

The storage unit contains on-chip random access memory (RAM) for microcontroller and for accumulating codes and data on-board read-only memory (ROM) is used.

Sensor Unit

Sensor unit is the combination of different types of sensors which converts the sensed data in the form of analog signals to the digital signals and transmits that signals to the microcontroller unit for processing the data. For increasing the sensor network lifetime, sensor unit may be in the state of active or sleep depending on the situation. Sensor unit's activation or deactivation is done by the microcontroller unit based on the coverage control algorithms used in the sensor node.

Communication Unit

Communication unit takes the responsibility to exchange the data among the nodes within the network and with the other networks. Transceiver is used for broadcasting and accepting data in the network by means of transmitter and receiver. It carries outs the modulation or demodulation techniques for the secured transmission in the wireless medium. Microcontroller controls the communication unit depends upon the algorithms and protocols to be used.

Power Unit

Power unit may consist of one or more rechargeable or non-rechargeable batteries which produce the power by the conversion of chemical energy to the electrical energy. Each battery may have various capabilities that are very small in size. Sensor board is the top layer of the sensor node which supports different types for sensor nodes including acoustic, aquatic, temperature and light etc.

Sensor networks may be used in different environments and applications depends upon the sensor nodes capabilities and functionalities. Various sensor networks scenarios are applicable for different applications such as homogeneous or heterogeneous networks and stationary or mobility networks. In homogeneous networks, all the nodes are having same sensing, processing and communication capabilities. All the nodes provide equal contribution to the efficiency of the sensor network. In the heterogeneous networks, each sensor node has different capabilities for sensing, processing and transmitting sensed data to other nodes in the network. Stationary sensor networks have immovable or stationary sensor nodes which must be located in a position where it is designed in the network. But in the case of mobility networks, sensor nodes are moved everywhere within the network for gathering the data. In some mobility networks, Sink node only moves around the network for getting data from immovable nodes in the sensor network which improves the network performance. In the case of energy consumption, compared with mobility sensor networks stationary networks consume less energy. For the flexibility and adaptability of the sensor nodes, Sensor networks have been deployed widely.

1.2.1 Challenges

Though sensor networks are widely used in almost every area there are some challenges raised for reducing the performance of the sensor networks owing to the limited amount of assets and node's capabilities.

Energy Efficiency:

In wireless sensor networks, how to consume energy is very crucial thing. Mostly sensor nodes are implemented by non-rechargeable batteries with limited energy supply. A node may be stopped its function owing to minimum power means the entire network will be collapsed. Different energy consumption mechanisms have been implemented in node's hardware for balance the network's performance.

Network Autonomy:

Depends upon the applications to be used sensor nodes are located in the area either deterministic or randomized manner. Sensor nodes are randomly scattered where there is no assurance for safety. In that situation, sensor nodes itself organize the deployment of the network such as structure and topology of the network, sensing and routing tasks. Sometimes for enhancing the operation of the network, nodes are interacted with other network interfaces.

Network Scalability:

In most of the applications, more number of sensor nodes is implemented. Scalability of the network does not affect the performance of the network. So for achieving network extendibility dispersed and restricted algorithms might be favoured. This is particularly useful for vast-range networks.

Fault Tolerance:

Nodes are very sensitive which are easily failed. Particularly in hostile or dangerous environments node failure rate is very high. Node failure rate is severely affecting the network performance. For improving the performance of the networks, sensor nodes are equipped with fault tolerance mechanisms in the design of the nodes and algorithms to be used.

Data Accuracy:

Most of the applications require accurate information from the sensor networks. Combined signal processing by cooperative nodes improve the accuracy of data. But in some cases network lifetime may be affected by maintaining the accuracy in information. In order to improve performance of the networks, it is necessary to balance to the correctness and the power utilization rate.

Information Security:

It is the most general and important constraint for all the networks needs that sensing data should be handled in secure manner. Many security algorithms are implemented for sensor networks to ensure the secured processing of data.

1.2.2 Key Issues

For the successful wireless sensor networks, some issues are to be taken as the primary criterion such as node system, middleware services and communication protocols.

Node System:

Each node contains microcontroller, integration of various components that lies in sensor board and etc for running sensor nodes which requires lots of attention for planning and employment of networks.

Communication Protocols:

Communication protocols are used to transfer the information with each other in the network and to the sink. For successful communication, physical, data link, network and transport layers are designed and implemented with highly improved protocols.

Middleware Services:

Software modules are used to enhance network organization along with improved network competency and application performance. These are achieved by the middleware services which are placed in between the application and communication protocol layer. Localization of node, network organization, and management of coverage, information aggregation and examination of safety are come under middleware services.

Coverage Control

Among these services coverage control is a major problem which reflects the sensor network performance. Especially in a large scale networks, this problem takes place a major role. Coverage control must be implemented in each sensor node in terms of design stage or algorithm implementation. Energy consumption and the coverage control are co-related each other which are the main factors for network lifetime and ensure the improved network efficiency. Coverage control in each sensor node is implemented by the sensor

coverage models.

Sensor Coverage Models:

Each sensor nodes capacity and quality is analysed through sensor coverage model. These models are used in WSNs for providing complete coverage of the network without any hole in conjunction with minimum amount of energy consumption. Sensing capability of each sensor node is calculated by the distance and angles between the sensor nodes within the sensor network. Euclidean distance formula is used to find out the coverage function of each sensor nodes.

Euclidean Distance =

Where p - Node 1

d - Node 2

D - Distance between node 1 and node 2

These models can be implemented in different geometrical shapes such as circle and hexagonal. One of the sensor coverage model is sector model (Figure 1) otherwise called as directional coverage model which is fully depends upon the angle and the sensing range of a sensor. That individual sensor has covered all the area within the sector. Another model is disk coverage model (Figure 2) in which a sensor sense the area within its sensing range in the form of circle. Disk coverage model uses least amount of nodes for jacketing the entire network. Sensing area of a sensor is considered as hexagonal (Figure 3) or cell. This hexagonal model is used in most of the real time applications as mobile communications, which provides the complete coverage.

Network Coverage Model:

Network Coverage model measures the entire QOS given by the sensor network where the nodes are placed at various ecological positions. The main aim of the network coverage model is to preserve the utilization of energy of sensor network. Based on the state of the applications, capability of sensor nodes and performance metrics, different coverage control problems are raised. Placement and the state of sensor nodes within the network place a vital role for achieving network coverage as well as the reduced energy consumption.

Each sensor node has communication, intellection and process finally silent state. Among these, communication process utilizes less energy than the other two states. So scheduling of sensor node's state will improve the coverage along with less energy utilization. Different design issues are described for coverage problems.

Coverage Type:

It defines the way for covering the sensor network which is categorized as point coverage, area coverage and coverage in barrier. Instead of the whole network, particular points of the network only covered by the point or target coverage.

In area coverage, nodes in the network covers entire sensor field. Barrier coverage is entirely different from the other two types in which during the node's deployment only coverage is known and based on the Euclidean distance path is to be found in the network.

Deployment Method:

Deployment method defines the construction of the sensor network either by deterministic or randomly scattered manner. In the deterministic deployment, sensor nodes are placed for achieving the required coverage with leaser amount. But nodes are placed randomly in randomly scattered network where the large sensor field is to be monitored.

Node Heterogeneity:

In the heterogeneous networks, sensor nodes are having different capabilities for sensing, processing or communication. Sensor nodes may be either stationary or mobile nodes depends upon the application scenario. Stationary sensor nodes are placed in a network during the deployment stage which cannot be modified. But in mobile networks, nodes are having the ability to move around the network. Though compared with stationary network, setup cost for the construction of mobile networks is very high it produces better performance.

Activity Scheduling:

Status of sensor unit is processed in terms of the implementation of sensor scheduling algorithms. In the case of randomly deployed network, area of the one is to be covered by the other nodes in the network which causes the redundant coverage leads to the more energy utilization. For reducing the redundancy in coverage, some nodes are to be entered into sleep state if the area is covered by the neighbouring nodes. Activity scheduling is used to increase the network lifetime with the required coverage. In Distributed scheduling algorithms, each sensor node itself schedules the process based on its own and neighbours information. One particular node takes the scheduling decision and transmits the results to sensor nodes. Distributed algorithms give more advantage than the centralized one in terms of dynamic large sensor networks.

Coverage Degree:

Coverage degree is defined as how much amount of nodes is used to wrap a particular spot in the entire network. In the least only one sensor node should cover the area in the network for ensuring the network coverage.

Coverage Ratio:

Coverage ratio is defined as how much amount of area is to be covered by the nodes in the network. Complete coverage refers that the 100% coverage satisfaction and the partial coverage refers that some point of area is not covered by the sensor nodes.

Network Connectivity:

Network connectivity provides the guarantee that entire nodes are to be connected. It is carried out by the routing algorithms in the network layer combined with coverage control algorithms. Single-hop and multi-hop communications are used based on the applications. Network connectivity is incorporated with the activity scheduling.

Performance Metric:

Performance of the network is analyzed by the energy consumption, coverage lifetime and number of sensor nodes. For an ideal network, minimum numbers of sensor nodes are used to sense the sensor field with complete coverage or fixed number of nodes deployment which utilizes limited energy for sensing, processing and transmission of data.

Area Coverage

Most of the applications require the entire coverage of the network that is wireless sensor networks are deployed for sensing each spot of the field. Complete coverage along with limited energy consumption is the basic requirement for most of the wireless sensor network applications. However, providing complete coverage is not an easy thing with minimum energy utilization. Some problems are raised in area coverage.

Enhancing the wireless sensor network with complete area coverage, we have to concentrate on sensor density, sensor scheduling and node movement strategy. Sensor nodes are deployed in either deterministic or randomly scattered but large scale networks related applications require the random employment of nodes. least amount of sensor nodes are to be used for achieving the complete area coverage which utilizes limited energy for sensing, processing and transmitting the sensed data to the other nodes.

Sensor activity scheduling is carried out by means of scheduling algorithms along with coverage control algorithms. Various scheduling algorithms are used depends upon the application scenario whether application needs complete coverage or partial coverage. Scheduling tasks will be varied based on the networks such as distributed or centralized. In distributed networks, decision about the scheduling is taken by the every individual sensor nodes in the network. In case of centralized networks, a central node takes the responsibility for the decision of scheduling that is which nodes are sensed at which time and how much time after sensing every node distributes the information to the vital node for further processing.

Movement of node is another critical factor for deciding the complete coverage of the entire sensor field. Fixed node deployment sometimes leads to coverage hole that is if a node gets failed means that area is not covered by the other nodes in the fixed deployment. But if the nodes are having the capability to move around the network, there is very less possibility for the coverage hole in which nodes are moved from their own place to other place where the area is not covered. Most of the wireless sensor applications require randomly scattered networks with mobile nodes even though it consumes little bit more energy than the others it gives the fulfilment for the complete coverage.

Clustering TechniquesS

Network clustering is the approach which provides the maximum coverage with the minimum energy consumption. Within the sensor network, sensor nodes are divided into group of sensors called clusters for ensuring the maximum coverage. Depends upon the networks, cluster size may be varied. In homogeneous network, all the clusters are in same size and sensor nodes are having same capabilities. In case of heterogeneous networks, cluster size may vary and sometimes nodes are having different capabilities. First of all, some group of nodes are elected as Cluster Heads (CH) which are having extra energy than the others in the network. Nodes which are closest to the CHs elected as the Cluster Members (CM). CMs sense the sensor field and transmit the intellectual information to the CH. It receives information from their members and processes them such as aggregate and sends back to the base station via sink node or straight to base station. Normally Clustering reduces the energy utilization in the network.


Clustering approach is the one of the most used approach in coverage control of WSN. It divides the nodes in the network into different clusters for efficient governing of the network. A suitable Cluster Head node controls each cluster, to which its Cluster members will be reporting its data. This paper analyses some of the recent clustering protocols introduced for coverage control in Wireless Sensor Network.

2.1.1 Distributed Energy Efficient Clustering Algorithm with Improved Coverage (DEECIC):

This [1] is deployed for increasing the network lifetime along with improved coverage. It proposes an average cluster size for the formation of the clusters, which reduces end- to-end delay by limiting the communications within 2-hop members as well as efficiency in data fusion. Cluster head is selected from a dense area, which is having more residual energy and more number of neighbours (Node degree). If the cluster head dies due to the depletion of its energy, it may not influence the whole network coverage due to the redundancy in coverage by its neighbours. DEECIC updates cluster head by setting energy threshold(Eth ) designed for each CH then checks that the remaining energy of a cluster head is less than its Eth if so that will be replaced by one of its neighbours in the next round. This will reduce the loss of data packets by the death of cluster head during the execution process and provides more coverage rounds than other algorithms as EECF and LEACH [19].

2.1.2 Coverage-Aware Clustering Protocol (CACP):

It [2] increases network coverage lifetime in wireless sensor network using two techniques such as clustering and scheduling. It uses a coverage aware cost metric for discovery of CH, which is having more redundancy in coverage. This will be achieved by means of sponsor sets in which node's sensing area is overlapped with other nodes in the sensor field. A layered self-activation algorithm is used for choosing the CMs. Instead of activating all the nodes, a set of nodes is only activated for sensing its area. If the sensing area of one node overlaps with other node, it will enter sleep mode for preserving energy. CACP will reduce the standard power utilization and maximize network coverage lifetime.

2.1.3 Cluster-Based Routing Protocol (CBR):

This [7] encompasses energy aware clustering algorithm EADC and Cluster Based Routing algorithm for non uniform node distributed WSNs to decrease power utilization among the nodes and boost the network lifetime. EADC constructs the clusters with even size of members to equalize the power utilization among them. In order to balance the power utilization among CHs in non-uniform node allocation, CBR algorithm with multi hop approach is introduced. If the cluster head and the Base Station (BS) is having distance less than the threshold DIST_TH, it directly communicates to the BS otherwise use multi-hop approach to select the next cluster head neighbour for forwarding the data to the BS. A cluster head, which is having more residual energy, minimum number of members, more coverage ratio and nearest to the BS, is elected as a next hop for routing the data in the network. Network lifetime will be significantly improved by adjusting intra-cluster and inter-cluster energy consumption.

2.1.4 Multi-Criterion Optimization (MCOP):

This [9] is proposed for the creation of clusters which ensures energy efficiency and coverage. In the beginning of clustering phase, each node is in the PLAIN state and calculates the probability for a Cluster head (CH) by comparing its remaining energy with the threshold value. If the probability is less than the threshold means nodes, change its state into CH contender state and broadcasts their residual energy to their neighbours within the competition range. Each node compares its residual energy with the receiving energy and finally nodes with higher residual energy are declared as CHs. Each CH sends CH Advertisement message to neighbours with its id and residual energy. If a node may receive more than one CH Advertisement message, it uses MCOP algorithm for selecting the proper CH by means of decision matrices and weight vector that is the distance from the node to CH, space between the CH and the Base Station and CH's remaining energy. Clusters, which are formed by MCOP, improves network lifetime than EECS, LEACH and HEED [20] protocols.

2.1.5 Coverage-Preserving Clustering Protocol (CPCP):

This [12] is proposed for providing the guarantee for complete coverage of the Wireless Sensor Network. Set of Cluster heads are elected from the densely populated area based on the remaining energy and redundancy in its coverage area. Cluster heads spreads across all over the network uniformly to avoid coverage holes. Cluster heads and active sensor nodes are to be selected by means of coverage-aware cost metrics. Route discovery message is generated to find path between cluster head and sink node. Each node delays the forwarding of the message to its nearby nodes based on its route cost. Then the non-CH nodes join its nearby CH nodes as its Cluster Members. Instead of activating all the nodes in the cluster, subset of sensor nodes are only activated, which covers the entire monitored area without redundancy in coverage. Thus, CPCP will preserve the network coverage with minimum energy consumption.

2.1.6 Connectivity Preserving Localized Coverage Algorithm (CPLC):

This [6] is proposed to ensure the coverage of Area of Interest (AOI) with minimum nodes to be started its processing as sets and preserving the connectivity between nodes. In a large-scale network, a node is located within other node's communication range for ensuring the connectivity and more than one cluster heads (Special Nodes) are elected randomly from that region which can be in touch with each and every Common nodes within its clusters. Coverage algorithm in special nodes will form the set of nodes. This algorithm works in three different states; they are Inquire, Active and Sleep states respectively. After the deployment of the nodes, each node enters into inquire state. Cluster head broadcasts Hello message to all the common nodes along with their location co-ordinates. If a node may receive more than one Hello messages, it will select a CH depends on the location, which is the nearest one, and send the reply messages along with the node's location. Likewise, sets are generated and their states are changed into either active or sleep states and each node is capable of covering the region independently. According to the coverage algorithm, only one set is activated at a time for decreasing the power utilization and prolong coverage lifetime by means of minimum overlapping between the nodes in the region.

2.1.7 Flow-Balanced Routing protocol (FBR):

It [15] is a centralized approach protocol for achieving energy efficiency and coverage preservation. It encompasses four algorithms as clustering algorithm, backbone construction, flow-balanced routing algorithm and finally rerouting algorithm. FBR executes algorithm of clustering for forming the clusters only once at the beginning of the network deployment in which a sink broadcasts cluster formation message (CLS_FORM) among the nodes and sensor node which is having highest overlapping degree considered as a cluster head. Non-cluster heads join itself to the nearest cluster head to ensure coverage. Backbone construction algorithm constructs backbone by sending BN_CONST message to all nodes. The CH forwards the sensed information from its CMs to the gateway node by using the flow-balanced routing algorithm. In addition, flow-based routing balances the residual energy of the clusters. Rerouting algorithm is executed when the backbone (Cluster head) is not able to withstand for further rounds and declare a CH based on highest remaining energy from the backbone construction instead of modifying the entire network. In this way, FBR provides both the power consumption and guaranteed coverage.


Clustering protocols mainly groups its members depends on the node's geographical location. The nearby 1-hop or 2-hop nodes only form clusters for sensing activities. If the non-adjacent nodes in the network are forming a group to cover the intended region, then it is called as Disjoint set. Some of the Set based approaches have been analysed here.

2.2.1 Distribution Free Approach (DFA):

Distribution Free Approach [3] ensures the network coverage lifetime of the sensor network. It estimates network coverage intensity in addition to the sensors locations field. It uses Kernel Density Estimator (KDE) to decide the node's distribution. Nodes deployed with the GPS receivers for its location awareness. Therefore, instead of calculating the coverage intensity by the assumption of node's distribution, it estimates the intensity only by the exact distribution of nodes. This will increase the lifetime of network coverage.

2.2.2 Low Coverage First Classifying Algorithm (LCFC):

It [4] proposes a K-set based scheduling for the creation of the sensor network with increasing network lifetime. Instead of choosing a group of sensor nodes for activating randomly, it chooses those nodes, which are having most low coverage points. An area, which is covered by minimum number of nodes called low coverage points. This will reduce the overlap in network coverage as well as energy usage of the network. It provides highest average coverage rate than other scheduling algorithms and balance the coverage rate of the sensor sets.

2.2.3 Minimum Perimeter Coverage of Queried Regions in a heterogeneous Wireless Sensor Network (MPCQR):

It [5] encompasses two approaches for determining minimum number of Sensor Nodes (SNs) which provides the guaranteed perimeter coverage for the queried region. In the first approach, a node is declared as a Co-ordinate Node (CNode) which receives a query request for the interested region from the user. Similar to the sink node, CNode collects all the information about the region from the selected SNs in that queried region which ensures perimeter coverage. In the second approach, instead of CNode each SNs in the queried region selects the next neighbours to form the coverage neighbour set and then minimum perimeter coverage set is formed based on the sensing overlap of the nodes in the queried region. This approach provides more energy consumption, network lifetime and perimeter coverage lifetime than the other approaches used in Wireless Sensor Network.

2.2.4 Distributed Coverage Hole Detection Protocol (DCHD):

This [8] is proposed for finding the gap in coverage in WSNs. It is achieved by means of two stages that is neighbour discovery and hole detection stage. In neighbour discovery stage, a node in the network is randomly chosen as a reference node, which broadcasts its location information to the nearest nodes. The receiving nodes calculate the distance (d1) between them and the reference node. If distance is less than the communication range (Rc), it is elected as a one-hop neighbour of reference node and the one-hop neighbour broadcasts reference node's location to its neighbours then they calculate distance (d2) between them and the reference node. If d2≤ Rc, the node its elected as a two-hop neighbour of reference node. Neighbour list is formed with one-hop and two-hop neighbours in the neighbour discovery phase. After forming the neighbour list, any node in the network executes an algorithm for detection of gap in which 1-hop and 2-hop neighbours form a triangle by using this radius (r) and centre (z) is calculated. If R ≤ Rs (Sensing range) algorithm declares no hole in coverage, otherwise hole is existed. This algorithm is used to discover the hole in coverage effectively than other algorithms.

2.2.5 Layered Diffusion-Based Coverage Control (LDCC):

It is a new distance and location free coverage control protocol for providing the guaranteed coverage in Wireless Sensor Networks along with minimum energy consumption. It uses the hop count information for the node's activation in the network instead of node's location information. Initially every nodes are in the state of active and they broadcast the hop count between them and the Base station (BS). A node with smaller hop count will be chosen as an active node and the BS will start coverage control process. The node itself will decide its state; it reduces overall computation cost of the network. It attains maximum coverage ratio together with minimum amount of nodes.

2.2.6 Energy-Efficient Coverage and Connectivity Preserving Routing Algorithm (ECCRA):

It [14] focuses network connectivity along with complete coverage of to form effective sensor network. It divides the sensor nodes into multiple subsets, which are mutually exclusive and among the subsets, limited subset only kept to be active. Minimum hop count is to be calculated for each node at the routing phase which ensures the connectivity among the subsets. During the transmission stage, every subset forwards its gathered information to gateway. Thus, ECCRA reduces energy consumption by activating limited subsets and increase the coverage lifetime of the fully connected network.


In recent times, using evolutionary algorithms for Efficient Coverage Control in WSN is increasing. Mostly when coverage control is used with the increasing of Lifetime of the network, evolutionary algorithms works best because of its global best solutions.

2.3.1 MultiObjective Evolutionary algorithm (MOEA):

This [10] is proposed for improve coverage as well as network lifetime. It is achieved by means of non-dominated solutions. Performance of this algorithm is evaluated by three metrics. Fuzzy mechanism is used along with MOEA for discovering the finest solution. Connectivity of the nodes in the network is an important metric for reducing the deployment cost and time of the sensor network.

2.3.2 Multi-Objective Genetic Algorithm (MOGA):

It [11] selects lesser amount of nodes from the dense area for providing full coverage to achieve Energy Efficient Coverage Control in Wireless Sensor Networks. It is based on some parameters. MOGA uses Elitism Non-Dominated Sorting Genetic Algorithm (NSGAII) for discovering the finest solutions to resolve the coverage problem along with fast Non-Dominated Sorting (NDA) approach. NDA is used to discover the non-dominated fronts in the network. The cluster head executes Energy Efficient Coverage Control Algorithm (ECCA) to schedule the sensor nodes and broadcasts scheduling list to the nodes in the clusters. It reduces the energy usage of the computation process, which is carried out by each node.




Energy consumption and network coverage are related to each other and more important criteria for an efficient wireless sensor network. In the existing system, for balancing these two issues, either clusters or sets are formed.

Network clustering divides the sensor network into group of clusters based on the geographical proximity of the sensor nodes (distance between the nodes) clusters are to be formed. Though network clustering is the approach to reduce the energy consumption the area within the network is redundantly covered by the group of nodes. In this approach cluster head selects the nodes which are closest and activate the entire nodes in the cluster which leads to the redundancy in coverage.

Rather than clustering approach, sets are formed based on the distance between the nodes in the network. Instead of selecting a particular node as a head, in the set approach all the nodes are having equal sensing and processing capabilities. Similar to clustering technique in set also distance places a vital role for creating the sets which causes the redundant coverage.

However, Sensor activity scheduling is implemented complete coverage without redundancy along with limited energy utilization is not yet to be achieved. Mostly these techniques increase the energy consumption and reduce the network coverage lifetime.


In the proposed system, instead of considering distance as a main criterion for the formation and activation of sensor nodes coverage is to be taken.

First of all, Clusters are formed similar to the existing techniques. That is, Cluster heads are elected from the network based on which nodes are having more number of overlapping nodes (number of neighbouring nodes). Cluster heads select the cluster members which are closest to themselves.

After formation of clusters, Combination of sensor nodes are formed from them based on their coverage. Cluster head selects a node, which is not being overlapped with other nodes in the remaining clusters. Instead of activating the entire cluster member nodes, only one node from each cluster is activated at a time. This avoids the redundant or unwanted coverage of the sensor nodes, which helps to prolong the network coverage lifetime with minimum energy consumption.

Significant Features:

Set of non-overlapped nodes only activated instead of the entire nodes in the sensor network.

Due to the activation of minimum number of nodes for a particular period, energy consumption rate is highly reduced compared with clustering approach.

By means of non-overlapped nodes activation, redundancy in coverage is extremely reduced.

Energy consumption and redundancy in coverage are both balanced or reduced by means of non-overlapping technique which leads to the improvement of complete network coverage lifetime.




To avoid the redundant coverage, group of non-overlapping nodes are selected and activated for prolonging network coverage lifetime with the limited energy utilization. First of all, sensor nodes are deployed in a field which is to be monitored by the nodes. Based on the distance between the nodes in the sensor network, Clusters are formed with the same cluster size.

After formation of the clusters, non-overlapped combinations of nodes are constructed. Each cluster heads picked up one node from its clusters which is not overlapped with the other sensor nodes in the remaining clusters. From the group of non-overlapped combinations, only one group is to be scheduled for sensing the area of the sensor network which avoids the redundancy in coverage.

Not only the coverage but also energy consumption for transmitting and receiving the sensed data is to be minimized in terms of activating minimum number of sensor nodes. Energy consumption rate of the clusters and the non-overlapped nodes combination are to be calculated in the data collection phase and compared with each other for analyzing the efficiency of the approach. Finally, how much area should be redundantly covered in the clustering approach and in the non-overlapped nodes combinations are to be found out.


Redundancy in coverage is to be avoided by means of the following modules.


Sensor Node Deployment

Cluster Formation

Non-overlapping Combination of Nodes Activation

Data Collection

Coverage Control

Module 1 - Sensor Node Deployment:

In this module, sensor nodes are deployed by randomly scattered manner within a sensor field. Deployment of sensor nodes is not a fixed one. Randomly scattered nodes only provide the flexibility to the wireless sensor network. In the particular time interval, sensor nodes are changed their position within the same network for achieving the complete coverage.

After deployment of sensor nodes, distance between the each and every node in the network is to be calculated by means of Euclidean distance.

Euclidean Distance =

Where px - x coordinate of sensor node 1

py - y coordinate of sensor node 1

dx - x coordinate of sensor node 2

dy - y coordinate of sensor node 2

Module 2 - Cluster Formation:

In the second module, clusters are formed based on the Euclidean distance which is calculated in the first module.

Cluster Head Selection:

Among the sensor nodes in the network, some nodes are elected as Cluster heads. A node which is having more overlapped nodes considered as a Cluster head.

Overlapping of a node is to be found out by means of the sensing range and the distance between the two nodes. If the distance is greater than the sensing range means two nodes are separated each other. If the distance between the two nodes is less than the sensing range of them there are two possibilities either two nodes are overlapped with each other or one node is fully contained in the other node.

From this calculation, Cluster heads are elected from the sensor network which is having more responsibility for processing of sensed data from the sensor nodes.

Cluster Members Selection:

Remaining nodes in the network that is other than the cluster heads forms the clusters by combining with the cluster heads. Cluster members are allotted to the cluster heads based on the priority which is having more overlapped nodes. Nodes which are closest to the cluster heads elected as cluster members. If the first cluster head selects its cluster members from their overlapped nodes then second cluster head starts its selection process. Likewise clusters are constructed with cluster heads and the cluster members.

Module 3 - Non-overlapping Combination of Nodes Activation:

In this module, some group of non-overlapping nodes are formed. After formation of the cluster, each cluster head selects one particular node from its own clusters which is not getting overlapped with other nodes in the remaining clusters.

First of all, cluster head picks one node and compared with other nodes in the remaining clusters by means of distance between them. If the node's distance is greater than the sensing range of the two nodes that node is considered as a non-overlapped node. This process is taken by each cluster head in the network at the same time. After this process one set of non-overlapping nodes combination is to be constructed. Then, this process is to be continued until all the nodes in the clusters are allotted in a particular non-overlapping nodes combination.

For example, in a homogeneous network, 100 sensor nodes are deployed with same sensing range. In the cluster formation, 100 sensor nodes are divided into 10 clusters. Each cluster is having one cluster head and 9 cluster members. In the existing case, these 10 clusters (100 nodes) are activated at a time. That is, 90 cluster members are sensing the network and transmitting data to the 10 cluster heads. This approach consumes more and more energy.

For that, from the 10 clusters 9 set of non-overlapping nodes combinations are formed. Each combination is having 10 nodes in which only one node is picked out from one cluster. Likewise 10 nodes are formed from 10 clusters. In this approach, only one combination is to be activated that is only one node is to be activated at a time from one cluster. So instead of activating 90 nodes for sensing only 10 nodes are activated. In the whole, by replacing 10 clusters that is 100 nodes activation, only 10 nodes along with 10 cluster heads totally 20 nodes are activated. Non-overlapping nodes combination is consecutively sensing the network in particular time interval.

Module 4 - Data Collection and Coverage Control:

In this module, energy consumption rate and redundant coverage ratio are to be calculated for the analyzing the efficiency of this proposed approach.

Data Collection:

In the cluster formation approach, cluster members are sensing the area and transmitting the sensed data to its own cluster head at some time interval. For this process, cluster members use some energy. Cluster heads reduce their energy by receiving the data from the cluster members and transmitting the data to the base station.

Likewise, in non-overlapping nodes combination only one sensor node transmits its sensed data to its own cluster. Energy is consumed for transmitting data to the cluster head and also receiving data from the only one cluster member at a time.

Energy transmission is to be calculated by means of the following formula:

ET = n.Eelec + εd2

Where ET - Energy Transmission

Eelec - 50 NJ/bit

ε - 50 PJ/bit

n - Number of Transmission Bits (5J)

d - Distance between the Two Nodes

Receiving energy is to be calculated by the following formula:

ER = n.Eelec

Where ER - Receiving Energy

From this energy calculation, we have to conclude non-overlapping nodes combination utilizes less amount of energy than the clustering approach.

Coverage Control:

Overall redundant coverage of the entire network is to be calculated for analyzing the complete coverage without redundancy of the network.

Overlapping area between two nodes is to be found out in terms of the following formula:

Overlapping Area = r2 (q - sin (q))

Where q = 2 * acos (c/2r)

r - Common radius

c - distance between two nodes

In the clustering approach, total redundant area is to be calculated by finding the overlapping area between the nodes in the clusters and also with the nodes in the other clusters that is between the each and every node in the network.

In case of non-overlapping nodes combinations, overlapping area between a node in one cluster with the node in remaining clusters that is within the nodes combination only overlapping area will be calculated.

Finally, compare the overall redundant coverage of clustering approach and the non-overlapping nodes combination approach. The proposed system reduces the redundancy in coverage and energy consumption compared with existing one which increases the network coverage lifetime.




Unit testing performs testing at each module and finally integrate all the modules. Unit testing becomes authentication efforts on the negligible part of software plan within the module.  This is also known as 'module testing'.  The modules of the system are tested separately.  This testing is to be conceded out throughout the programming.  Within this testing, every model is found to be functioning adequately while observe to the predictable output as of the module.  There are some validation checks for the fields.  For example, field entries are worked properly and provide the accurate result. It is very easy to find error and debug the system.

Test Results: All the test cases mentioned above passed successfully. No defects encountered.


Data is capable of gone across an interface, one module can have an unfavourable consequence on the other sub function, while collective, could not produce the preferred major task.  Integrated testing is logical testing that can be done with the randomly generated data.  The need for the integrated test is to find the overall system performance.

Test Results: All the test cases mentioned above passed successfully. No defects encountered.


It is a testing that to test the data in a secured manner, and to protect the data from the unauthorized person that no one can access the data .It is an application to check whether that the data stays secret. It is very crucial to It industry that to secure the data.

Test Results: All the data values in the process are secured using some techniques. Here it preserves privacy as well as accuracy.



Coverage is one of the fundamental issues in Wireless sensor network, which reflects how much a sensor network is efficient. In most of the wireless sensor networks, sensor nodes covered the area redundantly which leads to the power lifetime of the network. This project proposes an approach in which non-overlapping combination of sensor nodes are formed from the clusters based on their coverage. Cluster head selects a node, which is not being overlapped with other nodes in the remaining clusters. Instead of activating the entire cluster member nodes, only one node from each cluster is activated at a time. This avoids the redundant or unwanted coverage of the sensor nodes, which helps to prolong the network coverage lifetime with minimum energy consumption.



Enhancing a system is also an important thing for development. A system may appear to be efficient at one time, but as time progresses the system should be enhanced to the level of the advancement in the technology.

My future work is to study how to enhance the flexibility of the sensor network by means of consecutively change the combinations of non-overlapping nodes for providing more efficiency in coverage of the network.