An information entropy based-clustering algorithm for heterogeneous wireless sensor networks

Osamy, Walid; Salim, Ahmed; Khedr, Ahmed M.

doi:10.1007/s11276-018-1877-y

Cited by 63 publications

(39 citation statements)

References 29 publications

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“…On the basis of the above routing protocols of homogeneous WSNs, many routing protocols of HWSNs have been proposed to further lengthen the life cycle of the network [34,35]. A SEP [21] for the HWSNs was proposed by Smaragdakis et al The different initial energy levels of nodes indicate that this network is a multi-level HWSN.…”

Section: Related Workmentioning

confidence: 99%

Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer

Zhao

Ren

Quan

et al. 2020

Sensors

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Wireless sensor network (WSN) nodes are devices with limited power, and rational utilization of node energy and prolonging the network lifetime are the main objectives of the WSN’s routing protocol. However, irrational considerations of heterogeneity of node energy will lead to an energy imbalance between nodes in heterogeneous WSNs (HWSNs). Therefore, in this paper, a routing protocol for HWSNs based on the modified grey wolf optimizer (HMGWO) is proposed. First, the protocol selects the appropriate initial clusters by defining different fitness functions for heterogeneous energy nodes; the nodes’ fitness values are then calculated and treated as initial weights in the GWO. At the same time, the weights are dynamically updated according to the distance between the wolves and their prey and coefficient vectors to improve the GWO’s optimization ability and ensure the selection of the optimal cluster heads (CHs). The experimental results indicate that the network lifecycle of the HMGWO protocol improves by 55.7%, 31.9%, 46.3%, and 27.0%, respectively, compared with the stable election protocol (SEP), distributed energy-efficient clustering algorithm (DEEC), modified SEP (M-SEP), and fitness-value-based improved GWO (FIGWO) protocols. In terms of the power consumption and network throughput, the HMGWO is also superior to other protocols.

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Section: Related Workmentioning

confidence: 99%

Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer

Zhao

Ren

Quan

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…The aforementioned steady-state equations are solved for estimating the value of steady-state stochastic value that pertains to the failure, selfish retention, and selfish into failure state as depicted in Equations (13), (14), and (15), respectively.…”

Section: Determination Of Transition Function Values Related To Thementioning

confidence: 99%

“…In addition, the existing complex security algorithms contributed for MWSNs are not potent in addressing the issue of limited potentialities of the sensor nodes' minimal power. Hence, the process of CH selection needs to concentrate on facilitating the energy effectiveness with trust maintenance in order to identify the selfishness, danger, and unauthorized nodes for sustaining lifetime of the network . The trust of the sensor nodes represents the degree of conviction about the dynamic characteristic behavior of a sensor node derived from the other cluster members of the network.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, the process of CH selection needs to concentrate on facilitating the energy effectiveness with trust maintenance in order to identify the selfishness, danger, and unauthorized nodes for sustaining lifetime of the network. 14 The trust of the sensor nodes represents the degree of conviction about the dynamic characteristic behavior of a sensor node derived from the other cluster members of the network. Most of the contributed energy-efficient and trust-based CH selection approaches concentrate on the reliability factor for quantifying the trust of the participating sensor nodes in the network.…”

Section: Introductionmentioning

confidence: 99%

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An availability predictive trust factor‐based semi‐Markov mechanism for effective cluster head selection in wireless sensor networks

Amuthan

Arulmurugan

2019

Int J Communication

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Summary The longevity of the sensor networks purely depends on the effectiveness of a cluster head selection process that attributes towards effective network management in wireless sensor networks. However, the majority of the cluster head selection schemes are considered an unrealistic condition which ponders the sensor nodes that have the possibility of being selected as cluster heads are highly energy competitive and trustworthy. In this paper, an availability predictive trust factor‐based semi‐Markov mechanism (APTFSMM) was proposed for facilitating effective cluster head selection with the view to enhance its degree of longevity degree in wireless sensor networks. This proposed APTFSMM inherited the merits of semi‐Markov process for estimating availability predictive trust factor that quantifies the maximum likelihood probability under which it is selected as the cluster head through maximized exploration of multiple transition states of the sensors in the networks. This proposed APTFSMM is determined to be predominant in enhancing the lifetime of the sensor network by 31% with a significantly reduced energy consumption rate of 38% compared with the benchmarked cluster head selection approaches considered for investigation.

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“…to process data collected from multiple sensor nodes to monitor activities and events in the observation area [1][2][3][34][35][36][37][38][39][40][41][42][43][44]. Due to presence of wind and obstacles, the actual landing positions of sensors cannot be controlled.…”

mentioning

confidence: 99%

Effective data routing using mobile sinks in disjoint mobile wireless sensor networks

Ramadan¹,

Khedr²,

Agrawal³

2019

PEN

Self Cite

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In Mobile WSNs (MWSNs) , disjoint clusters could be naturally formed in an unpredictable way that possess the nature of highly dynamic connected and disconnected schema. Many partitions of the network could happen in disjoint mobile wireless sensor networks (DMWSNs), and could last for a significant amount of time that can challenge current routing protocols in crisis-driven and geography-driven applications. We propose in this paper, two new centralized and distributed routing discovery protocols for DMWSN. In the centralized protocol, the static sink controls the motion of mobile sinks. In the distributed protocol, each mobile sink is responsible for collecting data in a specific region. In our work, the mobile sinks need to coordinate among themselves for communication with the base station (BS). The simulation results shows the advantage of our newly proposed protocols in terms of time delay, energy consumed, and the delivery ratio.

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An information entropy based-clustering algorithm for heterogeneous wireless sensor networks

Cited by 63 publications

References 29 publications

Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer

Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer

An availability predictive trust factor‐based semi‐Markov mechanism for effective cluster head selection in wireless sensor networks

Effective data routing using mobile sinks in disjoint mobile wireless sensor networks

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