A Novel Load Balancing Scheduling Algorithm for Wireless Sensor Networks

Gherbi, Chirihane; Aliouat, Zibouda; Bahaj, Mohamed

doi:10.1007/s10922-018-9473-0

Cited by 30 publications

(17 citation statements)

References 26 publications

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“…In order to reduce the discarding problem caused by the overflow of data queue in CH, Gherbi et al 7 proposed a hierarchical energy balanced multipath (HEBM) routing protocol, which balances the energy dissipation between sensor nodes and prolongs the lifetime of the network. Gherbi et al 8 also proposed a distributed energy efficient adaptive clustering protocol (DEACP), which has the characteristics of load balancing and self-adaptation. It can reduce the energy consumption of the whole network, balance the energy consumption between sensors, and prolong the lifetime of the network.…”

Section: Related Workmentioning

confidence: 99%

Lightweight load-balanced and authentication scheme for a cluster-based wireless sensor network

Zhou

Lin

2021

International Journal of Distributed Sensor Networks

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Clustering technology is one of the crucial technologies to prolong the lifetime in wireless sensor networks. However, most cluster schemes choose cluster head randomly to send data without considering load balancing and security. In addition, some cluster heads in the highly active area may be overloaded, while others in the low active area may be overloaded, which may easily lead to extreme imbalance in task allocation. Our research on relevant literature shows that the existing authentication schemes do not fully consider the load balancing of cluster heads, while the load balancing schemes ignore the security authentication of cluster heads. Therefore, this article effectively combines load balancing and security verification, and proposes a lightweight load balancing and verification scheme (secure load and energy balancing) based on clustered wireless sensor networks. Secure load and energy balancing implements cluster head’s authentication and confidentiality and integrity of all messages in load balancing. This scheme not only effectively maintains the energy balance of the whole network but also successfully improves the security overhead, thus prolonging the network lifetime. The simulation results show that compared with other similar schemes, this scheme has higher packet forwarding rate, longer network life, and lower overhead. This further proves that the scheme is energy-saving, safe, dynamic, stable, and sustainable.

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Section: Related Workmentioning

confidence: 99%

Lightweight load-balanced and authentication scheme for a cluster-based wireless sensor network

Zhou

Lin

2021

International Journal of Distributed Sensor Networks

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“…Nevertheless, all modification in LEACH is based on hierarchical clustering while in WSNs hierarchy is not the optimum solution. Hybrid LEACH [24,25] is used for better selection of CH depends on remaining energy. Using threshold condition for each round, CH is elected between high and low energy levels.…”

Section: A Cluster Based Modelsmentioning

confidence: 99%

Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in Wireless Sensor Networks

Khan¹,

Rahman²,

Almaiah³

et al. 2020

IEEE Access

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Wireless Sensor Networks (WSNs) have revolutionized the era of conventional computing into a digitized world, commonly known as "The Internet of Things". WSN consists of tiny low-cost sensing devices, having computation, communication and sensing capabilities. These networks are always debatable for their limited resources and the most arguable and critical issue in WSNs is energy efficiency. Sensors utilize energy in broadcasting, routing, clustering, on-board calculations, localization, and maintenance, etc. However, primary domains of energy consumption at node level are three i.e. sensing by sensing-module, processing by microprocessor and communication by radio link. Extensive sensing, over-costs processing and frequent communication not only minimize the network lifetime , but also affects the availability of these resources for other tasks. To increase lifetime and provide an energy-efficient WSN, here we have proposed a new scheme called "A Content-based Adaptive and Dynamic Scheduling (CADS) using two ways communication model in WSNs". CADS dynamically changes a node states during data aggregation and each node adapts a new state based on contents of the sensed data packets. Analyzer module at the Base-Station investigates contents of sensed data packets and regulates functions of a node by transmitting control messages in a backward direction. CADS minimizes energy consumption by reducing unnecessary network traffic and avoid redundant message-forwarding. Simulation results have been shown that it increases energy-efficiency in terms of network lifetime by 9.65% in 100 nodes-network, 11.36% in 150 nodes-network and 0.94% in 300 nodes. The proposed scheme is also showing stability in terms of increasing cluster life by 87.5% for a network of 100 nodes, 94.73% for 150 nodes and 53.9% in 300 nodes.

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“…Mixreclustering tends to increase CH workload; therefore, it consumes a larger amount of energy. A Distributed Energy-efficient Adaptive Clustering Protocol (DEACP) was addressed for balancing the energy dissipation of sensor nodes (Gherbi et al, 2019). Sleeping control rules were applied to mitigating the consumption of energy.…”

Section: Related Workmentioning

confidence: 99%

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

Sinde

Begum

Njau³

et al. 2020

Cogent Engineering

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Network lifetime remains as a significant requirement in Wireless Sensor Network (WSN) exploited to prolong network processing. Deployment of low power sensor nodes in WSN is essential to utilize the energy efficiently. Clustering and sleep scheduling are the two major processes involved in improving network lifetime. However, abrupt and energy unaware selection of cluster head (CH) is nonoptimal in WSN which reflects in the drop of energy among sensor nodes. This paper addresses the twofold as utilization of sensor nodes to prolong the node's energy and network lifetime by LEACH-based cluster formation and Time Division Multiple Access scheduling (TDMA). Clusters are constructed by the design of an Enhanced-Low-Energy adaptive Clustering Hierarchy protocol (E-LEACH) that uses parallel operating optimization (Grey Wolf Optimization (GWO) and Discrete Particle Swarm Optimization (D-PSO)) for selecting an optimal CH and helper CH. The fitness values estimation from GWO and D-PSO is concatenated to prefer the best optimal CH. E-LEACH also manages the cluster size which is one of the conventional disadvantages in LEACH. CHs are responsible to perform energy-aware TDMA scheduling which segregates the coverage area into 24 sectors. Alternate sectors are assigned Ramadhani Sinde ABOUT THE AUTHOR Ramadhani Sinde works as an assistant lecturer in the School of Computational and Communication Sciences and Engineering at Nelson Mandela African Institution of Science and Technology (NM-AIST). Currently, he under Doctoral Environmental Management Information System project undertaking PhD studies in the field of Information and Communication of Science and Engineering. His research interests include Internet of Things (IoT) network, embedded systems, mobile computing, modelling and performance evaluation of wireless sensor networks, wireless and mobile communication. Mr. Sinde has co-authored more than 10 papers in internationally refereed journals and conferences. He is a Queen Elizabeth Scholarship -Advanced Scholars Program alumni.

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A Novel Load Balancing Scheduling Algorithm for Wireless Sensor Networks

Cited by 30 publications

References 26 publications

Lightweight load-balanced and authentication scheme for a cluster-based wireless sensor network

Lightweight load-balanced and authentication scheme for a cluster-based wireless sensor network

Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in Wireless Sensor Networks

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

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