Trust Based Target Coverage Protocol for Wireless Sensor Networks Using Fuzzy Logic

Among important issues in the current energy-efficient routing protocols for wireless sensor networks (WSNs) based on clustering approaches are how to determine the optimal number of clusters, how to generate clusters and how select cluster-heads to improve WSNs performance. These approaches aim to reduce energy consumption of the WSN nodes and to extend the network lifetime. This paper reviews and compares the performance of three clustering techniques for determining number of clusters: rule of thumb, elbow, and silhouette. Each of these techniques involves a distributed K-means approach to generate clusters. Moreover, we compare these three clustering methods with low energy adaptive clustering hierarchy (LEACH), Imp LEACH and MODLEACH in terms of network lifetime, energy consumption and the number of packets sent to the base station (BS). The results obtained indicate that rule of thumb method provides better performance compared to other clustering techniques in terms of energy consumption and network lifetime.

QoSNET: An integrated QoS network for routing protocols in large scale wireless sensor networks

Achieving optimal field coverage is a significant challenge in various sensor network applications. In some specific situations, the sensor field (target) may have coverage gaps due to the random deployment of sensors; hence, the optimized level of target coverage cannot be obtained. Given a set of sensors in the plane, the target coverage problem is to separate the sensor into different groups and provide them specific time intervals, so that the coverage lifetime can be maximized. Here, the constraint is that the network should be connected. Presently, target coverage problem is widely studied due to its lot of practical application in Wireless Sensor Network (WSN). This paper focuses on target coverage problem along with the minimum energy usage of the network so that the lifetime of the whole network can be increased. Since constructing a minimum connected target coverage problem is known to be NP-Complete, so several heuristics, as well as approximation algorithms, have been proposed. Here, we propose a heuristic for connected target coverage problem in WSN. We compare the performance of our heuristic with the existing heuristic, which states that our algorithm performs better than the existing algorithm for connected target coverage problem. Again, we have implemented the 2-connected target coverage properties for the network which provide fault tolerance as well as robustness to the network. So, we propose one algorithm which gives the target coverage along with 2-connectivity.

Wireless sensor networks congestion occurs easily due to its centralized traffic pattern. Normally, mono-sync wireless sensor network experiences multiple traffic flow congestion in the dense environment of the network, which leads to excess energy consumption and severe packet loss. To overcome these issues, a congestion detection and alleviation mechanism using cluster based heuristic optimized hierarchical routing protocol is proposed in this paper. Here, congestion detection and alleviation utilize the features of sensor nodes. The congestion is categorized into two types: (i) node level congestion and (ii) link level congestion. The node level congestion is detected by assessing the buffer utilization and the interval amid the consecutive data packets. The link level congestion is considered with computing link usage utilizing back-off step of round robin carrier sense multi-access with collision avoidance. Congestion detection and alleviation reactively affected node/link through cuckoo hosted rider search multi-hop routing algorithm. It has two phases: the cluster head selection and multi-path routing. Cluster head selection is performed through Taylor multiple random forest kernel fuzzy C-means clustering algorithm and multi-path routing is performed through cuckoo hosted rider search multi-hop routing algorithm. The simulation of the proposed method is done in network simulator tool. Here, the performance metrics, like packet delivery ratio, delay, energy consumption, packet drop, overhead, network lifetime and throughput are calculated. The experimental outcomes of the proposed technique shows 11.6%, 18.4% and 28.1% lower delay, 78.2%, 65.4% and 52.6% higher packet delivery ratio, and 29.2%, 37.4% and 40.8% lower packet drop compared with the existing methods, like congestion detection and alleviation using multi-attribute decision-making in optimization-based hybrid congestion alleviation routing protocol in wireless sensor networks, congestion detection and alleviation using hybrid K-means with greedy best first search algorithms in packet rate reduction utilizing adaptive weight firefly algorithm ant colony optimization based routing protocol in wireless sensor networks and congestion detection and alleviation using multi-input time on task optimization algorithm for altered gravitational search algorithm routing protocol in wireless sensor networks.

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. Recent advances in wireless networks have led to many new protocols specifically designed for WSNs where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. Minimizing energy dissipation and maximizing network lifetime are important issues in the design of routing protocols for WSNs. In this paper, the low-energy adaptive clustering hierarchy (LEACH) routing protocol is considered and improved. We propose a clustering routing protocol named intra-balanced LEACH (IBLEACH), which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that IBLEACH outperforms LEACH and the existing improvements of LEACH in terms of network lifetime and energy consumption minimization.

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper we propose a enhance adaptive re-clustering protocol (EARP) for wireless sensor network. In EARP the cluster heads and next heads are elected based on residual energy of each node, transfer power, sleep and awake scheme and the average energy of each cluster. The simulation results show that EARP achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks.

Sensor deployment is a fundamental issue in Wireless Sensor Networks (WSNs). Studies on the coverage problem are concentrated on deploying sensors to cover determined areas or a set of determined points (targets). On the other hand, the sensor network should have a lifetime long enough to fulfill the application requirements. Therefore, prolonging the network lifetime must be taken into account in designing a solution for a WSN that covers determined points. The problem of determining the location of sensor nodes such that the targets are covered and the network lifetime is maximized is called the sensor deployment problem. So far, various approaches, such as heuristics and approximation algorithms, have been used to solve the sensor deployment problem in WSNs. In this paper, we use two improved versions of the Particle Swarm Optimization (PSO) algorithm to solve the sensor deployment problem. The first one is cooperative PSO and the second one is improved cooperative PSO using fuzzy logic. The simulation results show that the algorithms proposed in this paper solve the target coverage problem with a longer network lifetime compared to the other similar algorithms.

SummaryIn energy‐constrained military wireless sensor networks, minimizing the bit error rate (BER) with little compromise on network lifetime is one of the most challenging issues. This paper presents a new relay selection based on fuzzy logic (RSFL) scheme which provides balance between these parameters. The proposed scheme considers node's residual energy and path loss of the relay‐destination link as the input parameters for the selection of the relay node. The relay node selection by fuzzy logic is based on prioritizing higher residual energy and minimum path loss. To evaluate the performance on wireless sensor network, we compare the proposed scheme with the three existing relay selection strategies, ie, random, maximum residual energy based relay selection (MaxRes), and minimum energy consumption based relay selection (MinEnCon). The simulation results of the proposed scheme in terms of network lifetime, BER, Network Survivability Index (NSI), and average energy of network nodes have been presented and compared with different relay selection schemes. The simulation results show that the proposed RSFL scheme has the lowest BER, moderate network lifetime, average energy, and NSI.

Target coverage is an important issue in wireless sensor networks (WSNs). This work copes with the target coverage problem which detaches a set of mobile sensors to targets efficiently. Given a set of disconnected targets with different quality of monitoring (QoM) and a set of mobile sensors which are distributed randomly in the networks, this paper develops two efficient algorithms for detaching mobile sensors to the targets such that the QoM of each target is satisfied. Performance study reveals that the proposed mechanisms outperform known mechanisms in terms of the satisfied QoMs of all targets and the movement cost of all mobile sensors as well as the life time of the wireless mobile sensor networks (WMSNs).

Wireless Sensor Network (WSN) has become one of the most common techniques in different applications such as agriculture, factory monitoring, health care and fire track. WSN has many advantages such as low cost, small size, multifunctional, self-organized and able to be routed by WSN protocols. On the other hand, WSN has some backward which obstructs some applications such as low battery, short lifetime, area of sensor deployed and sensor energy consumption. In this paper, we propose a new approach to achieve better enhancement of WSN in terms of network lifetime and data transmission time represented by reducing the packet delay time. Then, we compare the simulated result of the proposed algorithm with the basic LEACH protocol with fixing parameters. The proposed algorithm achieved 128.80% improvement compared with the basic LEACH in the concept of network lifetime.

Wireless sensor networks(WSN) are a kind of communication networks with in-dependent sensor nodes which could construct multi-hop ad hoc network to trans-fer data. The transport protocols for Wireless Sensor Network play an important role to promote the performance of the whole systems. This paper proposes a modified transport layer protocol for heterogeneous Wireless Sensor Networks(HWSN). As TCP is not suitable to use in HWSN directly, we design a modified transport protocol(named mTCP) based on TCP by a six-state finite state machine. Experimental results illustrate that our design can improve the communication capability of the transmission layer in heterogeneous wireless sensor networks significantly.

Wireless sensor networks contains small sensor node and processor which have several issues and challenges with regards to Limited Computational Capacity, Energy Efficiency, Path Planning Overhead and many more. Entire lifetime of network depends on efficient energy consumption in sensor network so it is a challenging task to design an Energy Efficient Routing Protocol for wireless sensor networks. Wireless sensor nodes dynamically self-organize themselves without utilizing preexisting infrastructure. Problem becomes more complex if some sensor node having mobility for some particular instance. In this paper we proposed an energy efficient routing protocol for WSN motivated by swarm intelligence of rummage behavior of ant and also covered mobility behavior of node. Furthermore we have combined the fuzzy logic with behavior of ant to take a better decision to find optimal path with less energy consumption. Our proposed algorithm utilize the principle of Fuzzy logic in addition of Ant Colony Optimization to develop energy efficient routing. The performance of our proposed work is evaluated on QualNet 7.4 Network Simulator. The simulation result shows that the proposed technique optimize the energy consumption, decrease RREQ packet and increase the lifetime of network as compare to existing routing protocol.

In this paper, a clustering-based energy-efficient routing protocol is designed to overcome the hotspot problem in Wireless Sensor networks (WSNs). We have divided the sensor nodes into several clusters, each cluster having a Cluster Head (CH) or a leader node and also implemented a centroid-based mobile sink. The sink moves to a location called “Energy Dependent Centroid Point” where the CHs need minimal energy to transmit data to the sink. We have defined this “Centroid Point” by an equation where the residual energies of CHs are used as a “weight factor” on a normal centroid equation. We have simulated the proposed algorithm and analyzed the results by varying the values of the energy weight factor in the centroid equation up to certain limits (α = 0, 1, 2, and 3). The simulation results are compared with WSN’s existing routing protocols having a mobile sink and a static sink. The comparison results show that our proposed centroid model with α = 0, where the mobile sink moves independent of the residual energies of CHs gives better performances in terms of network lifetime, energy loss, and total data packet transmission.

Wireless sensor networks have achieved the substantial research interest in the present time because of their unique features such as fault tolerance, autonomous operation etc. The coverage maximization while considering the resource scarcity is a crucial problem in the wireless sensor networks. The approaches which address these problems and maximize the network lifetime are considered prominent. The node scheduling is such mechanism to address this issue. The scheduling strategy which addresses the target coverage problem based on coverage probability and trust values is proposed in Energy Efficient Coverage Protocol (EECP). In this paper the optimized decision rules is obtained by using the rough set theory to determine the number of active nodes. The results show that the proposed extension results in the lesser number of decision rules to consider in determination of node states in the network, hence it improves the network efficiency by reducing the number of packets transmitted and reducing the overhead.

Wireless sensor networks (WSNs) are quickly becoming an essential part of today's modern infrastructure, and it is becoming crucial to consider time synchronisation problems in WSNs. Furthermore, one of the main design issues in WSN time synchronisation is the efficient use of energy at each sensor node to prolong the lifespan of the network. This paper describes a new energy-efficient time protocol based on the spanning tree of the network model graph in a WSN. Three major cases are discussed: 1) time synchronisation using the energy-efficient spanning tree (EST) protocol in a WSN with approximately 300 sensors; 2) an improved EST protocol in large-scale WSNs; 3) an improved EST protocol under weighted graph. Additionally, a series of practical algorithms are proposed in this paper, where both energy and time efficient can be clearly shown through a number of simulated examples along with their comparative results.