Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

SEPCS: Prolonging Stability Period of Wireless Sensor Networks using Compressive Sensing

Compressive sensing (CS) is an emerging theory thatis based on the fact that a small number of linear projections of asparse data contains enough information for reconstruction. CScan break through the asymmetry between the data acquisitionand information processing that makes a great challenge to therestriction energy and computation consumption of the sensornodes. In this paper, we propose a routing protocol called SEPCSfor clustered wireless sensor networks (WSNs) using CS. SEPCScombines a new clustering strategy with CS theory for prolongingstability period and network lifetime in WSNs. Our simulationresults show that the proposed protocol can effectively prolongthe stability period and network lifetime compared with existingprotocols

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Wireless Sensor Networks (WSN) acquired a lotof attention due to their widespread use in monitoring hostileenvironments, critical surveillance and security applications. Inthese applications, usage of wireless terminals also has grownsignificantly. Grouping of Sensor Nodes (SN) is called clusteringand these sensor nodes are burdened by the exchange of messagescaused due to successive and recurring re-clustering, whichresults in power loss. Since most of the SNs are fitted with nonrechargeablebatteries, currently researchers have been concentratingtheir efforts on enhancing the longevity of these nodes. Forbattery constrained WSN concerns, the clustering mechanism hasemerged as a desirable subject since it is predominantly good atconserving the resources especially energy for network activities.This proposed work addresses the problem of load balancingand Cluster Head (CH) selection in cluster with minimum energyexpenditure. So here, we propose hybrid method in which clusterformation is done using unsupervised machine learning based kmeansalgorithm and Fuzzy-logic approach for CH selection

K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Wireless Sensor Networks (WSN) acquired a lotof attention due to their widespread use in monitoring hostileenvironments, critical surveillance and security applications. Inthese applications, usage of wireless terminals also has grownsignificantly. Grouping of Sensor Nodes (SN) is called clusteringand these sensor nodes are burdened by the exchange of messagescaused due to successive and recurring re-clustering, whichresults in power loss. Since most of the SNs are fitted with nonrechargeablebatteries, currently researchers have been concentratingtheir efforts on enhancing the longevity of these nodes. Forbattery constrained WSN concerns, the clustering mechanism hasemerged as a desirable subject since it is predominantly good atconserving the resources especially energy for network activities.This proposed work addresses the problem of load balancingand Cluster Head (CH) selection in cluster with minimum energyexpenditure. So here, we propose hybrid method in which clusterformation is done using unsupervised machine learning based kmeansalgorithm and Fuzzy-logic approach for CH selection

Privacy in wireless sensor networks using ring signature

AbstractThe veracity of a message from a sensor node must be verified in order to avoid a false reaction by the sink. This verification requires the authentication of the source node. The authentication process must also preserve the privacy such that the node and the sensed object are not endangered. In this work, a ring signature was proposed to authenticate the source node while preserving its spatial privacy. However, other nodes as signers and their numbers must be chosen to preclude the possibility of a traffic analysis attack by an adversary. The spatial uncertainty increases with the number of signers but requires larger memory size and communication overhead. This requirement can breach the privacy of the sensed object. To determine the effectiveness of the proposed scheme, the location estimate of a sensor node by an adversary and enhancement in the location uncertainty with a ring signature was evaluated. Using simulation studies, the ring signature was estimated to require approximately four members from the same neighbor region of the source node to sustain the privacy of the node. Furthermore, the ring signature was also determined to have a small overhead and not to adversely affect the performance of the sensor network