Energy Efficient Clustering Based Routing Technique in WSN using Brain Storm Optimization

Sackey, Samson Hansen; Ansere, James Adu; Anajemba, Joseph Henry; Kamal, Mohsin; Iwendi, Celestine

doi:10.1109/icet48972.2019.8994740

Cited by 18 publications

(18 citation statements)

References 10 publications

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“…For a quorum-based system to have reliable data transfer, minimize energy conservation [7], [8] and maximize the lifetime of the network [9], [10], the following methods were adopted. To reduce energy conservation, some characteristics such as the passing of messages, wake-up/sleep approaches, adaptive listening design, collision prevention, and delay minimization were implemented.…”

Section: Related Workmentioning

confidence: 99%

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An Artificial Intelligence-Based Quorum System for the Improvement of the Lifespan of Sensor Networks

et al. 2021

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Artificial I ntelligence-based Q uorum s ystems a re used to solve the energy crisis in real-time wireless sensor networks. They tend to improve the coverage, connectivity, latency, and lifespan of the networks where millions of sensor nodes need to be deployed in a smart grid system. The reality is that sensors may consume more power and reduce the lifetime of the network. This paper proposes a quorum-based grid system where the number of sensors in the quorum is increased without actually increasing quorums themselves, leading to improvements in throughput and latency by 14.23%. The proposed artificial intelligence scheme reduces the network latency due to an increase in time slots over conventional algorithms previously proposed. Secondly, energy consumption is reduced by weighted load balancing, improving the network's actual lifespan. Our experimental results show that the coverage rate is increased on an average of 11% over the conventional Coverage Contribution Area (CCA), Partial Coverage with Learning Automata (PCLA), and Probabilistic Coverage Protocol (PCP) protocols respectively.

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Section: Related Workmentioning

confidence: 99%

“…The created ODEV clique has four intersections (5,6,10,14) with the exclusion of rows and columns. Then we have calculated the quorum incremental time slots for the ODEV clique.…”

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confidence: 99%

An Artificial Intelligence-Based Quorum System for the Improvement of the Lifespan of Sensor Networks

et al. 2021

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“…To analyze the performance of our proposed method BSO-TLBO based algorithm for the Energy-efficient weighted clustering method for WSN is compared with recently presented methods known as WOA based EECH method [23], BSO based EECH method [24], BOA-ACO based EECH method [25].…”

Section: Simulation and Outcomesmentioning

confidence: 99%

“…The performance analysis in terms of active nodes are conducted for our proposed work with the existing WOA based EECH method [23], BSO based EECH method [24], and BOA-ACO based EECH method [25] works. The simulations are carried for 350 sensor nodes at three above mentioned scenarios and are illustrated in…”

Section: Performance Analysis Based On Active Nodesmentioning

confidence: 99%

Energy-Efficient Cluster-Based Routing Protocol for WSN Based on Hybrid BSO–TLBO Optimization Model

Krishnan¹,

Yamini

Alenazy

et al. 2021

The Computer Journal

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The most famous wireless sensor networks is one of the cheapest and rapidly evolving networks in modern communication. It can be used to sense various substantial and environmental specifications by providing cost-effective sensor devices. The development of these sensor networks is exploited to provide an energy-efficient weighted clustering method to increase the lifespan of the network. We propose a novel energy-efficient method, which utilizes the brainstorm algorithm in order to adopt the ideal cluster head (CH) to reduce energy draining. Furthermore, the effectiveness of the BrainStorm Optimization (BSO) algorithm is enhanced with the incorporation of the modified teacher–learner optimized (MTLBO) algorithm with it. The modified BSO–MTLBO algorithm can be used to attain an improved throughput, network lifetime, and to reduce the energy consumption by nodes and CH, death of sensor nodes, routing overhead. The performance of our proposed work is analyzed with other existing approaches and inferred that our approach performs better than all the other approaches.

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“…A large number of SNs increases the network topological complexity, which can be reduced using long-range SNs and a larger number of BSs. However, it still suffers from the network routing complexity, the increased energy requirement for the repeater nodes introducing heterogeneity, and the requirement for various optimization algorithms [48] or a layered protocol [49]. Considering the above limitations and complexity of the available WSN technologies, this paper proposes a lightweight, dynamic, and auto-reconfigurable WSN protocol (LDAP) for the resource and energy-constrained SNs.…”

Section: Problem Formulationmentioning

confidence: 99%

LDAP: Lightweight Dynamic Auto-Reconfigurable Protocol in an IoT-Enabled WSN for Wide-Area Remote Monitoring

Rahman

Wahid

2020

Remote Sensing

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IoT (Internet of Things)-based remote monitoring and controlling applications are increasing in dimensions and domains day by day. Sensor-based remote monitoring using a Wireless Sensor Network (WSN) becomes challenging for applications when both temporal and spatial data from widely spread sources are acquired in real time. In applications such as environmental, agricultural, and water quality monitoring, the data sources are geographically distributed, and have little or no cellular connectivity. These applications require long-distance wireless or satellite connections for IoT connectivity. Present WSNs are better suited for densely populated applications and require a large number of sensor nodes and base stations for wider coverage but at the cost of added complexity in routing and network organization. As a result, real time data acquisition using an IoT connected WSN is a challenge in terms of coverage, network lifetime, and wireless connectivity. This paper proposes a lightweight, dynamic, and auto-reconfigurable communication protocol (LDAP) for Wide-Area Remote Monitoring (WARM) applications. It has a mobile data sink for wider WSN coverage, and auto-reconfiguration capability to cope with the dynamic network topology required for device mobility. The WSN coverage and lifetime are further improved by using a Long-Range (LoRa) wireless interface. We evaluated the performance of the proposed LDAP in the field in terms of the data delivery rate, Received Signal Strength (RSS), and Signal to Noise Ratio (SNR). All experiments were conducted in a field trial for a water quality monitoring application as a case study. We have used both static and mobile data sinks with static sensor nodes in an IoT-connected environment. The experimental results show a significant reduction (up to 80%) of the number of data sinks while using the proposed LDAP. We also evaluated the energy consumption to determine the lifetime of the WSN using the LDAP algorithm.

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Energy Efficient Clustering Based Routing Technique in WSN using Brain Storm Optimization

Cited by 18 publications

References 10 publications

An Artificial Intelligence-Based Quorum System for the Improvement of the Lifespan of Sensor Networks

An Artificial Intelligence-Based Quorum System for the Improvement of the Lifespan of Sensor Networks

Energy-Efficient Cluster-Based Routing Protocol for WSN Based on Hybrid BSO–TLBO Optimization Model

LDAP: Lightweight Dynamic Auto-Reconfigurable Protocol in an IoT-Enabled WSN for Wide-Area Remote Monitoring

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