A study of subdividing hexagon-clustered WSN for power saving: Analysis and simulation

Wang, Dajin; Lin, Li; Xu, Li

doi:10.1016/j.adhoc.2011.03.001

Cited by 39 publications

(26 citation statements)

References 8 publications

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“…It has been proved in [8] that Proposition 2. There are totally an equivalent of n 2 subhexagons in a R n -subdivision.…”

Section: C1 Intra-cluster Powermentioning

confidence: 94%

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Cluster subdivision towards power savings for randomly deployed WSNs — An analysis using 2-D spatial poisson process

Wang

2016

2016 7th International Conference on Information and Communication Systems (ICICS)

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We propose to use a 2-dimensional (2-D for short) spatial Poisson process to model a WSN with randomly deployed sensors, and use the model to analyze a scheme that subdivides the clusters of a WSN to achieve an overall power savings. We assume no knowledge of how the sensors are spread in the sensing area, and hence need a statistical process to describe the distribution of all sensors. Assuming the 2-D spatial Poisson distribution, a comprehensive analysis is performed to estimate the power savings brought about by the proposed subdivision. Using hexagon as the shape of the cluster, the analysis shows that the subdivision scheme can yield significant savings in overall power consumption of sensors in the cluster.

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“…It has been proved in [8] that Proposition 2. There are totally an equivalent of n 2 subhexagons in a R n -subdivision.…”

Section: C1 Intra-cluster Powermentioning

confidence: 94%

“…Also proved in [8], for a R n subdivision, assuming that every sub-clusterhead aggregates all collected data and transmits one aggregated packet to the clusterhead, the total transmission power by all sub-clusterheads can be expressed by:…”

Section: C2 Inter-cluster Powermentioning

confidence: 99%

Cluster subdivision towards power savings for randomly deployed WSNs — An analysis using 2-D spatial poisson process

Wang

2016

2016 7th International Conference on Information and Communication Systems (ICICS)

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“…It's proved in [12] that hexagon is the ideal shape for clustering in wsn to extend the network lifetime and efficiently utilizing the energy of the sensors. For that we choose to divide the target field to many regular hexagons, the nodes in the same hexagon form the cluster and for better performance we subdivide every cluster into cells (Fig.…”

Section: The Architecture and The Design Of Our Protocolmentioning

confidence: 99%

Energy consumption balancing in wireless sensors networks

Amine

Bouragba

Elhoussaine

et al. 2014

2014 International Conference on Multimedia Computing and Systems (ICMCS)

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The management of energy in wireless sensors networks (wsn) is the main factor that can influence the lifespan of the network. To reduce the energy consumption, the transmission of data between sensor nodes must be reduced in order to preserve the remaining energy in every node. The nodes closest to the sink are critical nodes, they perform far more tasks than other nodes in wsn and consume a big amount of energy. Therefore, the resources of these nodes determine the lifetime of the whole network. To reduce the network traffic overhead and prolong the lifespan of the network we propose a new energy balancing architecture based on hexagonal clusters. In addition, the use of a mobile agent for each and every cluster and several sinks for the whole network can solve the problem of uneven energy consumption of both inter-and intra-cluster environments.

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“…The proposed approach was evaluated against different layouts using clustered hierarchical WSNs (CSW) and traditional hexagonal cell (TXC)-based WSNs 27,29 with UAVs acting as a sink. The proposed work, to the best of authors' knowledge, differs from the previous in its novel approach towards the use of available charge alongside an SDN controller for logical topology formation, system layout, and backoff intervals.…”

Section: Introductionmentioning

confidence: 99%

“…LEACH, PACT, HEED, and PEGASIS are examples of hierarchical WSN architectures. [24][25][26][27][28] Generally, many systems used one of the two or both of them combined together. Hexagonal topology formation of WSN nodes is efficient in a way that it increases the capacity of the network by forming nonoverlapping sections with a base station in the middle of the topology.…”

Section: Introductionmentioning

confidence: 99%

Efficient data management and control over WSNs using SDN‐enabled aerial networks

Sayeed

Kumar

Sharma

2019

Int J Communication

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The recent developments in collaborative search, acquisition, and tracking have hoisted the geographical barrier. The network between unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) is one such collaboration, which comprises battery-powered static sensor nodes that act as sources and sinks and UAVs that act as relays. This collaborative network presents with opportunities and advantages, but at the same time, configuration of such networks is an arduous task. The WSN nodes are characterized by constant depleting power. Their network itself requires constant management and reconfiguration. These requisites can be slaked through the formation of an efficient data dissemination algorithm, which acclimates according to the network state. Considering this, a data dissemination approach is presented in this paper, which constructs a virtual topology predicated on the charge of WSN nodes utilizing software-defined networks (SDNs) through UAVs. The topology is constantly monitored and reconfigured when required. The aerial nodes are equipped with multiple-input multiple-output (MIMO) antennas in order to facilitate simultaneous communication with the ground nodes, the base station, and the SDN controller. An efficient sleep timer and backoff counter strategies are also utilized by the proposed approach. The SDN controller facilitates the topology formation and maintenance of a sleep timer and a backoff counter. The proposed model is compared with clustered hierarchical layouts and hexagonal cell layouts through the network simulations. The results suggest significant improvements in the proposed model for various metrics, such as lifetime, delay, latency, delivery ratio, and throughput in comparison with the existing solutions.High radio frequency (RF) coverage, high altitude, high throughput, heavy payload, less operating time, ease of use, and low cost are the basic requirements of UAV-CONOPS. Chemical, Biological, Radiological, and Nuclear Reconnaissance (CBRN)-CONOPS whose major purpose is the containment of hazards are also turning towards UAV networks. Cellular network-based air-to-ground links and unmanned aircraft system (UAS)-backbone systems, communication aware sensor distribution, etc are some of the promising aspects of the UAV systems. 2,3 The crucial step towards UAV networks is the development of sustainable multi-UAV environments. National regulations, routing, path planning, quality of service (QoS), integration with Global Information Grid (GIG), mobility control, coordination, and standardization are the steps required for efficient migration towards flying networks (multi-UAV). 4,5 The complexity of the multi-UAV ad hoc networks makes data dissemination also a challenging prospect. Latency, delay, antenna type, timing, etc come into play when we are talking about a network that is so fast moving and dynamic. 6 Multi-UAVs collaborate to achieve common objectives. It is evident that the collaborative UAV and the ground networks together can perform complex tasks. Some of these tasks...

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A study of subdividing hexagon-clustered WSN for power saving: Analysis and simulation

Cited by 39 publications

References 8 publications

Cluster subdivision towards power savings for randomly deployed WSNs — An analysis using 2-D spatial poisson process

Cluster subdivision towards power savings for randomly deployed WSNs — An analysis using 2-D spatial poisson process

Energy consumption balancing in wireless sensors networks

Efficient data management and control over WSNs using SDN‐enabled aerial networks

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