Geographical location based hierarchical routing strategy for wireless sensor networks

Kumar, Pramod; Chaturvedi, Ashvini; Kulkarni, Muralidhar

doi:10.1109/icdcsyst.2012.6188667

Cited by 15 publications

(14 citation statements)

References 10 publications

(5 reference statements)

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“…4) Each node has location information. There have many localization methods in WSNs [9], [10]. For example, we use the solution presented in [9] to achieve the localizat -ion.…”

Section: Network Modelmentioning

confidence: 99%

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A clustering protocol based on Virtual Area Partition Using Double Cluster Heads scheme for wireless sensor networks

Xu³

2013

2013 IEEE Third International Conference on Information Science and Technology (ICIST)

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A number of multifunction sensors deployed randomly with limited energy is one character of wireless sensor networks, so energy efficient is a critical factor in sensor network design. In this literature, we present a clustering protocol based on Virtual Area Partition using Double Cluster Heads scheme (VAP-DCH) for wireless sensor networks, which partitions the network and selects a Main Cluster Head (MCH) and a Vice Cluster Head (VCH) in each cluster adaptively. The simulation results show that the protocol we presented improves the system performance, prolongs the network lifetime and transfers more data to the base station..

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“…4) Each node has location information. There have many localization methods in WSNs [9], [10]. For example, we use the solution presented in [9] to achieve the localizat -ion.…”

Section: Network Modelmentioning

confidence: 99%

“…We run the simulations to evaluated the performance of the proposed protocol, there are 100 nodes randomly distributed in a 100 100 m m u network area with the BS located at (50,175), the energy of each node is randomly distributed in and VAP-E [9]. The number of nodes alive over time is illustrated in Fig.…”

Section: Double Cluster Heads Schemementioning

confidence: 99%

A clustering protocol based on Virtual Area Partition Using Double Cluster Heads scheme for wireless sensor networks

Xu³

2013

2013 IEEE Third International Conference on Information Science and Technology (ICIST)

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“…There are a number of existing works on localization in WSNs [14][15][16]. For example, we use the solution proposed in [16] to obtain the localization.…”

Section: Network Modelmentioning

confidence: 99%

An Energy Distance Aware Clustering Protocol with Dual Cluster Heads Using Niching Particle Swarm Optimization for Wireless Sensor Networks

2015

Journal of Control Science and Engineering

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Energy efficient utilization is an important criteria and factor that affects the design of wireless sensor networks (WSNs). In this literature, we propose an energy distance aware clustering protocol with Dual Cluster Heads using Niching Particle Swarm Optimization (DCH-NPSO). The protocol selects two cluster heads in each cluster, the Master Cluster Head (MCH) and the Slave Cluster Head (SCH), and the selection needs to consider the network state information carefully and deliberately. Simulation results show that the protocol we proposed can balance the energy dissipation and extend the network lifetime effectively.

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“…The location of each SN is represented using binary location index (BLI) frame (Kumar et al, 2012). In present work for test purposes, the service area is considered as a square shape geographical area.…”

Section: Geographical Location Addressing Scheme and Location Indexmentioning

confidence: 99%

Performance measures of fuzzy C-means algorithm in wireless sensor networks

Kumar

Chaturvedi

2017

IJCAET

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Abstract:The major issues that govern performance of wireless sensor networks (WSNs) are efficient uses of limited resources and appropriate routing decisions of network paths under the severely constrained energy scenario. In this work, to address these issues uses of k-means and fuzzy C-means algorithms are investigated for clusters formation and subsequent selection of cluster heads (CHs). For all these newly formed clusters; selection of cluster head is done based on member sensor nodes residual energy status (RES) followed by estimation of Euclidean distances. Depending upon the Euclidean distance measures between the sink node and the estimated energy-centroid (EC) of clusters these clusters are classified into five types. The RES estimation is exercised for all the CHs and sensor nodes (SNs) of the network. Outcomes of simulation results indicate superior performance of fuzzy-c means algorithm compared to k-means algorithm. Further, a case study is presented, wherein the sink is allowed to have some movements in the service area. Here, different quadrant of service area exhibits different pattern of query spatial distribution. The optimal location of sink is sought to support energy efficient operational aspects of the WSNs.

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Geographical location based hierarchical routing strategy for wireless sensor networks

Cited by 15 publications

References 10 publications

A clustering protocol based on Virtual Area Partition Using Double Cluster Heads scheme for wireless sensor networks

A clustering protocol based on Virtual Area Partition Using Double Cluster Heads scheme for wireless sensor networks

An Energy Distance Aware Clustering Protocol with Dual Cluster Heads Using Niching Particle Swarm Optimization for Wireless Sensor Networks

Performance measures of fuzzy C-means algorithm in wireless sensor networks

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