PDC: Prediction-based data-aware clustering in wireless sensor networks

Ashouri, Majid; Yousefi, Hamed; Basiri, Javad; Hemmatyar, Ali Mohammad Afshin; Movaghar, Ali

doi:10.1016/j.jpdc.2015.02.004

Cited by 21 publications

(8 citation statements)

References 23 publications

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“…In (14), sigðv kþ1 id Þ is the threshold function that converts the velocity to a value between [0, 1], which is defined as…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

“…In recent years, the research on WSN topology control algorithm mainly focuses on power control and hierarchical topology construction algorithms [12,13]. In terms of power controlbased topology construction method, the typical algorithms that have been proposed are node-based local mean algorithm and local mean neighbors algorithm [14], relative neighborhood graph algorithm based on neighbor graphs [15], etc. In terms of hierarchical topology construction method, typical algorithms include topological control algorithms based on uniform clustering, such as the low-energy adaptive clustering hierarchy algorithm and hybrid energy-efficient distributed clustering approach, etc.…”

Section: Introductionmentioning

confidence: 99%

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Cluster tree topology construction method based on PSO algorithm to prolong the lifetime of ZigBee wireless sensor networks

Xue

Chen

et al. 2019

J Wireless Com Network

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For wireless sensor networks (WSNs) based on ZigBee technology, the network topology plays an important role for improving the energy efficiency and the network lifetime. An appropriate construction method of network topology should be designed for saving the energy of the battery in each network node so as to prolong the lifetime of ZigBee WSNs. In this paper, a novel cluster tree topology construction method based on particle swarm optimization (PSO) algorithm is proposed. In order to transform the network topology construction problem into an energy consumption optimization problem, an evaluation function reflecting the network energy consumption is designed, and the network topology is mapped into a particle population individual suitable for the PSO algorithm. In order to prolong the network lifetime as long as possible, two network topology reconstruction methods with the PSO algorithm based on fixed and variable energy thresholds are further proposed, respectively. The simulation results show that the proposed methods can prolong the lifetime of ZigBee WSNs effectively.

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“…In (14), sigðv kþ1 id Þ is the threshold function that converts the velocity to a value between [0, 1], which is defined as…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cluster tree topology construction method based on PSO algorithm to prolong the lifetime of ZigBee wireless sensor networks

Xue

Chen

et al. 2019

J Wireless Com Network

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“…The conditions on the transmission powers of CHs and non-CHs that ensure the connectivity of the inter-cluster topology are established. Paper [20] focuses on designing a predictionbased approach. It exploits both spatial and temporal correlations to form highly stable clusters of nodes sensing similar values.…”

Section: Literature Surveymentioning

confidence: 99%

A Distributed Energy Efficient Clustering Algorithm for Data Aggregation in Wireless Sensor Networks

Shirazi¹,

Sabet²,

Pajoohan³

2018

IIUMEJ

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Wireless sensor networks (WSNs) are a new generation of networks typically consisting of a large number of inexpensive nodes with wireless communications. The main purpose of these networks is to collect information from the environment for further processing. Nodes in the network have been equipped with limited battery lifetime, so energy saving is one of the major issues in WSNs. If we balance the load among cluster heads and prevent having an extra load on just a few nodes in the network, we can reach longer network lifetime. One solution to control energy consumption and balance the load among nodes is to use clustering techniques. In this paper, we propose a new distributed energy-efficient clustering algorithm for data aggregation in wireless sensor networks, called Distributed Clustering for Data Aggregation (DCDA). In our new approach, an optimal transmission tree is constructed among sensor nodes with a new greedy method. Base station (BS) is the root, cluster heads (CHs) and relay nodes are intermediate nodes, and other nodes (cluster member nodes) are the leaves of this transmission tree. DCDA balances load among CHs in intra-cluster and inter-cluster data communications using different cluster sizes. For efficient inter-cluster communications, some relay nodes will transfer data between CHs. Energy consumption, distance to the base station, and cluster headsâ€™ centric metric are three main adjustment parameters for the cluster heads election. Simulation results show that the proposed protocol leads to the reduction of individual sensor nodesâ€™ energy consumption and prolongs network lifetime, in comparison with other known methods. ABSTRAK: Rangkaian sensor wayarles (WSN) adalah rangkaian generasi baru yang terdiri daripada nod-nod murah komunikasi wayarles. Tujuan rangkaian-rangkaian ini adalah bagi mengumpul maklumat sekeliling untuk proses seterusnya. Nod dalam rangkaian ini dilengkapi bateri kurang jangka hayat, jadi simpanan tenaga adalah satu isu besar dalam WSN. Jika beban diimbang antara induk kelompok dan lebihan beban dihalang pada setiap rangkaian iaitu hanya sebilangan kecil nod pada tiap-tiap kelompok,Â jangka hayat dapat dipanjangkan pada sesebuah rangkaian. Satu penyelesaian adalah dengan mengawal penggunaan tenaga dan mengimbangi beban antara nod menggunakan teknik berkelompok. Kajian ini mencadangkan kaedah baru pembahagian tenaga berkesan secara algoritma berkelompok bagi pembahagian data dalam WSN, dikenali sebagai Pembahagian Kelompok Kumpulan Data (DCDA). Melalui pendekatan baru ini, pokok transmisi optimum dibina antara nod sensor melalui kaedah baru. Stesen utama (BS) ialah akar, induk kelompok-kelompok (CHs) dan nod penyiar ialah nod perantara, dan nod-nod lain (nod-nod ahli kelompok) ialah daun bagi pokok trasmisi. DCDA mengimbangi beban CHs antara-kelompok dan dalam-kelompok komunikasi data daripada kelompok berbeza saiz. Bagi komunikasi berkesan dalam-kelompok, sebahagian nod penyampai akan memindahkan data antara CHs. Penggunaan tenaga, jarak ke stesen utama dan induk kelompok metrik sentrik adalah tiga parameter pelaras bagi pemilihan induk kelompok. Keputusan simulasi protokol yang dicadang menunjukkan pengurangan penggunaan tenaga pada nod-nod sensor individu dan memanjangkan jangka hayat rangkaian, berbanding kaedah-kaedah lain yang diketahui.

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“…In [2] authors generalized the multi-parent method to support a multi-cluster model for the network where they assumed that the network had multiple central points called cluster-head (CH) those were in charge of scheduling the nodes in the network. In [3] authors proposed a prediction-based data-aware clustering in wireless sensor networks. They formed steady clusters and so significantly reduced the amount of communication required to report the final results to the sink.…”

Section: Clusteringmentioning

confidence: 99%

“…The data is forwarded, via multiple hops to a sink which uses it locally or is connected to other networks (e.g., the Internet) through a gateway [2][3][4]. The wireless sensor networks have issues related to latency, speed, security and more energy usage.…”

mentioning

confidence: 99%

Improved APAC algorithm for minimizing delay in wireless sensor network with mobile sink

Upadhyay¹,

Mehta²

2016

IJACR

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PDC: Prediction-based data-aware clustering in wireless sensor networks

Cited by 21 publications

References 23 publications

Cluster tree topology construction method based on PSO algorithm to prolong the lifetime of ZigBee wireless sensor networks

Cluster tree topology construction method based on PSO algorithm to prolong the lifetime of ZigBee wireless sensor networks

A Distributed Energy Efficient Clustering Algorithm for Data Aggregation in Wireless Sensor Networks

Improved APAC algorithm for minimizing delay in wireless sensor network with mobile sink

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