A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network

A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network

A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network

 

Abstract—

Wireless sensor network consists of hundreds to thousands of sensor nodes gathering various data including temperature, sound, location, etc. They have been applied to
numerous fields such as healthcare, monitoring system, military, and so forth. It is usually difficult to recharge or replace the sensor nodes which have limited battery capacity.
Energy efficiency is thus a primary issue in maintaining the network. In this paper we propose an efficient cluster head selection method using K-means algorithm to maximize the
energy efficiency of wireless sensor network. It is based on the concept of finding the cluster head minimizing the sum of Euclidean distances between the head and member nodes.
Computer simulation shows that the proposed approach allows better performance than the existing hierarchical routing protocols such as LEACH and HEED in terms of network
lifetime.the cooperation with other nodes. Each sensor node transmits the sensed data to other sensor nodes or Base Station(BS).Here direct communication to the BS is impractical if the number of sensor nodes is large as a few hundreds or thousands.

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Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm for enhanced network lifetime in wireless sensor network

Energy efficient clustering protocol based on K-means (EECPK-means)- Midpoint algorithm for enhanced network lifetime in wireless sensor network

Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm for enhanced network lifetime in wireless sensor network

 

Abstract:

Wireless sensor networks (WSNs) consist of an enormous number of tiny sensor nodes deployed in huge numbers which are able to sense, process and transmit environmental information to the base station (BS) for a Nvariety of applications. Energy efficiency is one of the primary concerns for maintaining WSN in operation. In this study, an energy efficient clustering protocol based on K-means algorithm named EECPK-means has been proposed for WSN where midpoint algorithm is used to improve initial centroid selection procedure. The proposed approach produces balanced clusters to ultimately balance the load of cluster heads (CHs) and prolong the network lifetime. It considers residual energy as the parameter in addition to Euclidean distance used in basic K-means algorithm for appropriate CH selection. Multi-hop communication from CH nodes to BS takes place depending on their distances from BS. Simulation result shows that the proposed approach outperforms LEACH-B, balanced parallel K-means (BPK means), Park’s approach and Mk-means with respect to network lifetime and energy efficiency. Simulation result also demonstrates that the proposed approach can reduce the energy consumption at most 50% compared to LEACH-B, 14% compared to BPK-means protocol, 10% compared to Park’s approach and 6% compared to Mk-means.

 

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An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks

An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks

An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks

 

Abstract:

In wireless sensor networks (WSNs), certain areas of the monitoring region may have coverage holes and serious coverage overlapping due to the random deployment of sensors. The failure of electronic components, software bugs and destructive agents could lead to the random death of the nodes. Sensors may be dead due to exhaustion of battery power, which may cause the network to be uncovered and disconnected. Based on the deployment nature of the nodes in remote or hostile environments, such as a battlefield or desert, it is impossible to recharge or replace the battery. However, the data gathered by the sensors are highly essential for the analysis, and therefore, the collaborative detection of coverage holes has strategic importance in WSNs. In this paper, distributed coverage hole detection algorithms are designed, where nodes can collaborate to detect the coverage holes autonomously. The performance evaluation of our protocols suggests that our protocols outperform in terms of hole detection time, limited power consumption and control
packet overhead to detect holes as compared to other similar protocols.

 

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Deployment strategy of WSN based on minimizing cost per unit area

Deployment strategy of WSN based on minimizing cost per unit area

Deployment strategy of WSN based on minimizing cost per unit area

 

abstract

Unbalance energy consumption is an inherent problem in wireless sensor networks characterized by multi-hop routing and many-to-one traffic pattern. Uneven energy dissipation can waste a lot of energy and cost. In this paper, a new deployment strategy of WSN that gathers several means is proposed to minimize cost. The regular hexagonal cell architecture is employed to build network that satisfies the constraints of coverage and connectivity. Based on the analysis of energy consumption of sensors and sink and cost of network, an energy allocation theorem and an integer programming model are presented to minimize the cost per unit area. The key issue is to determine the number of layers of network when
other parameters are fixed. Furthermore, a scheme of multi-sink network is proposed for large monitored area. In order to balance the energy consumption of sensors on the identical layer, a uniform load routing algorithm is presented. The numerical analysis and simulation results show that the waste of energy and cost of WSN can be effectively reduced with the strategy.

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Coverage hole detection and restoration algorithm for wireless sensor networks

Coverage hole detection and restoration algorithm for wireless sensor networks

Coverage hole detection and restoration algorithm for wireless sensor networks

 

Abstract

In wireless sensor networks (WSNs), preserving coverage of the target area by the sensor nodes is crucial to deliver certain services. However, a few sensor nodes die during the network operation due to energy constraints which may break the coverage of the target area. We refer this as a coverage hole problem. In this paper, we propose a new algorithm called CHD-CR which attempts to restore the coverage after detecting a coverage hole in the target area. The proposed algorithm mainly consists of coverage hole detection (CHD) and coverage restoration (CR) phases. We design an efficient local mechanism for coverage hole detection and energy efficient technique for its restoration. We test the performance of the proposed algorithm through simulation and the results are compared with the existing algorithms. Simulation results show that the proposed CHD-CR algorithm outperforms the existing algorithms in terms of coverage preservation for longer time.

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Coding-based storage design for continuous data collection in wireless sensor networks

Coding-based storage design for continuous data collection in wireless sensor networks

Coding-based storage design for continuous data collection in wireless sensor networks

Abstract:

In-network storage is an effective technique for avoiding network congestion and reducing power consumption in continuous data collection in wireless sensor networks. In recent years, network coding based storage design has been proposed as a means to achieving ubiquitous access that permits any query to be satisfied by a few random (nearby) storage nodes. To maintain data consistency in continuous data collection applications, the readings of a sensor over time must be sent to the same set of storage nodes. In this paper, we present an efficient approach to updating data at storage nodes to maintain data consistency at the storage nodes without decoding out the old data and re-encoding with new data. We studied a transmission strategy that identifies a set of storage nodes for each source sensor that minimizes the transmission cost and achieves ubiquitous access by transmitting sparsely using the sparse matrix theory. We demonstrate that the problem of minimizing the cost of transmission with coding is NPhard. We present an approximation algorithm based on regarding every storage node with memory size B as B tiny nodes that can store only one packet. We analyzed the approximation ratio of the proposed approximation solution, and compared the performance of the proposed coding approach with other coding schemes presented in the literature. The simulation results confirm that significant performance improvement can be achieved with the proposed transmission strategy.
Published in: Journal of Communications and Networks ( Volume: 18, Issue: 3, June 2016 )
Date of Publication: 27 September 2016
Print ISSN: 1229-2370
INSPEC Accession Number: 16337621
Publisher: IEEE

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