EBDHR: Energy Balancing and Dynamic Hierarchical Routing algorithm for wireless sensor networks

Heikalabad, Saeed Rasouli; Navin, Ahmad Habibizad; Mirnia, Mir Kamal; Ebadi, Saeed; Golesorkhtabar, Mehdi

doi:10.1587/elex.7.1112

Cited by 16 publications

(5 citation statements)

References 12 publications

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“…The DEEC algorithm considers the remaining energy of nodes when selecting CHs, preventing the quick deaths of low-energy nodes because they serve as CHs for a long time. Since then, many scholars [ 10 , 11 , 12 , 13 , 14 , 15 ] have proposed various methods entailing WSNs, such as SEP, PEGASIS, and HEED, to save energy and handle greater workloads; these methods extend the lives of sensor nodes and achieve the best operating efficiency in an environment with limited energy. In addition, some researchers [ 16 , 17 , 18 ] have surveyed and compared the aforementioned methods.…”

Section: Literature Reviewmentioning

confidence: 99%

A Byzantine Sensing Network Based on Majority-Consensus Data Aggregation Mechanism

Chang

Liu

2021

Sensors

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In the current Internet of Things era, digital devices form complex interconnections. The statuses of objects of interest are monitored using sensors, and distributed wireless sensor networks are formed from numerous sensor nodes. Many Byzantine fault tolerance mechanisms in wireless sensor networks (WSNs) were proposed from Byzantine agreement which even with a few faulty nodes in a sensor network, most healthy nodes can reach a consensus, perform data transmission tasks, and maintain network operation. In this study, this mechanism was utilized together with the majority function technique; in particular, the proposed method uses original sensor signals to define a threshold to assert a binary value of one or zero, thereby performing data judgment and aggregation. This approach reduces node energy consumption and enables the nodes to quickly reach a consensus. Moreover, the operating performance of the network can be maintained even when problems such as node failure and faults occur within the fault tolerance range. Compared with existing algorithms, the proposed data aggregation mechanism exhibits a better network life cycle and can effectively extend the flexibility of network operations.

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Section: Literature Reviewmentioning

confidence: 99%

A Byzantine Sensing Network Based on Majority-Consensus Data Aggregation Mechanism

Chang

Liu

2021

Sensors

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“…Where k x − x i is the distance between nodes x and x i , A x − x i is the attenuation for the distance the signal travels, and α(α ∈ [2,5] ) is the path loss exponent.…”

Section: Cluster Formation Based On Cluster Member Boundsmentioning

confidence: 99%

“…In order to obtain an objective scalability of network, gathering sensor nodes into clusters has been greatly pursued by the research community [1,2]. Each cluster would have a head, in many cases referred to the clusterhead (CH).…”

Section: Introductionmentioning

confidence: 99%

HCABS: The hierarchical clustering algorithm based on soft threshold and cluster member bounds for wireless sensor networks

Golsorkhtabaramiri

Hosseinzadeh

Golsorkhtabaramiri

et al. 2012

IEICE Electron. Express

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Wireless Sensor Networks (WSNs) for reducing energy consumption and increasing sensors lifetime can use the clustering algorithms. We propose a new energy-efficient hierarchical clustering algorithm based on soft threshold cluster-head election and cluster member bounds for WSNs which called HCABS. Our simulation studies suggest that HCABS achieves longer lifespan and reduce energy consumption in WSNs as well as low latency and moderate overhead across the network.

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“…In cluster formation phase, the all nodes calculate the confidence value of primary cluster heads that are on their radio transmission range by (7) [10]. Then they join to the primary cluster head that its confidence value is greater than other.…”

Section: Cat Protocolmentioning

confidence: 99%

“…One of the techniques that use the data aggregation to reduce energy consumption in WSNs is called clustering based routing algorithm [1][2][3][4]. In [5][6][7][8][9][10] there are protocols that use the clustering technique in the network.…”

Section: Introductionmentioning

confidence: 99%

CAT: The New Clustering Algorithm Based on Two-Tier Network Topology for Energy Balancing in Wireless Sensor Networks

Rahmani

Kousha

Darougaran

et al. 2010

2010 International Conference on Computational Intelligence and Communication Networks

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Since the energy constraint is one of the most important restrictions in wireless sensor networks so the issue of energy balancing is essential for prolonging the network lifetime. Hence this problem has been considered as a main challenge in the research of scientific communities. In the recent papers many algorithms have been proposed for clustering on wireless sensor network to balance the energy consumption such as multi-tier clustering protocol. In this work we propose the new clustering algorithm based on twotier network topology namely CAT. The cluster head selection algorithm in CAT is done in two stages. So there will be two cluster head in a cluster. This algorithm selects a best sensor node as a cluster head in two phases by different methods. Simulation Results show that the CAT prolongs the network lifetime about 45% and 19% compared to the LEACH and HEED, respectively.

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EBDHR: Energy Balancing and Dynamic Hierarchical Routing algorithm for wireless sensor networks

Cited by 16 publications

References 12 publications

A Byzantine Sensing Network Based on Majority-Consensus Data Aggregation Mechanism

A Byzantine Sensing Network Based on Majority-Consensus Data Aggregation Mechanism

HCABS: The hierarchical clustering algorithm based on soft threshold and cluster member bounds for wireless sensor networks

CAT: The New Clustering Algorithm Based on Two-Tier Network Topology for Energy Balancing in Wireless Sensor Networks

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