Survey on fault tolerance‐based clustering evolution in WSN

Mohapatra, Hitesh; Rath, Amiya Kumar

doi:10.1049/iet-net.2019.0155

Cited by 30 publications

(22 citation statements)

References 83 publications

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“…The fitness of all the salps is calculated, and the fittest one is chosen as the leader. This algorithm is best suitable for maintaining the balance between exploration and exploitation and for the faster convergence by evading through the local entrapment as well ) (Mohapatra & Rath, 2020). The principle of the SSO algorithm can be modeled to resolve the issue of balancing the load in a dynamic cloud environment.…”

Section: The Standard Salp Swarm Optimization Algorithmmentioning

confidence: 99%

Binary Self-Adaptive Salp Swarm Optimization-Based Dynamic Load Balancing in Cloud Computing

Parida

Rath

Mohapatra

2022

International Journal of Information Technology and Web Engineering

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In the recent era of cloud computing, the huge demand for virtual resource provisioning requires mitigating the challenges of uniform load distribution as well as efficient resource utilization among the virtual machines in cloud datacenters. Salp swarm optimization is one of the simplest, yet efficient metaheuristic techniques to balance the load among the VMs. The proposed methodology has incorporated self-adaptive procedures to deal with the unpredictable population of the tasks being executed in cloud datacenters. Moreover, a sigmoid transfer function has been integrated to solve the discrete problem of tasks assigned to the appropriate VMs. Thus, the proposed algorithm binary self-adaptive salp swarm optimization has been simulated and compared with some of the recent metaheuristic approaches, like BSO, MPSO, and SSO for conflicting scheduling quality of service parameters. It has been observed from the result analysis that the proposed algorithm outperforms in terms of makespan, response time, and degree of load imbalance while maximizing the resource utilization.

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Section: The Standard Salp Swarm Optimization Algorithmmentioning

confidence: 99%

Binary Self-Adaptive Salp Swarm Optimization-Based Dynamic Load Balancing in Cloud Computing

Parida

Rath

Mohapatra

2022

International Journal of Information Technology and Web Engineering

Self Cite

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“…Edge computing offers flexible resources that permit distributed computing and provide security for data from flaws often used in a centralized approach [21]. Some research, like cloudlet [22], femtoclouds [23] and edge computing, [24] have insisted on integrating resources for mobile devices. A device offloads the main parts of its processing to cloudlet when it detects edge support, rather creating parts for task completion [25].…”

Section: A Edge Node Related Group Formationmentioning

confidence: 99%

A Decentralized Edge Computing Latency-Aware Task Management Method With High Availability for IoT Applications

Bukhsh¹,

Abdullah

Bajwa

2021

IEEE Access

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Rapid growth of Internet of Things (IoT), and other intelligent devices, introduced different applications which offer real-time latency features; however, it is difficult to handle the large volumes of data produced during the computational process, to adequately complete tasks. The decentralized edge computing process handles the task at the user's end to accomplish latency applications, but recent research adopted centralized methodologies for computing in the edge network, placing additional overhead for cluster management and grouping. In this paper, we formulate an edge nodes group on task arrivals with a decentralized technique to process jobs, in a parallel mode, to complete execution. In addition, high availability will be added to promise effective processing of IoT based applications executed in the edge computing system. In the edge node environment, where resources are restricted, there is a requirement for high availability methods, which can deliver system reliability according to the local device information, without the data of network topology. In this paper, our technique is to enhance network reliability with the help of the edge node's local information, which is executed in the distributed edge computing network, while also proposing a high availability technique to enhance the overall IoT environment. Our proposed Latency Aware Algorithm for Edge Computing with High Availability (LAAECHA) detects edge nodes faults, repairs edge nodes and replaces edge nodes with backups, using a new algorithm in a decentralized mode. Our research results show that the proposed LAAECHA method is more effective than existing methods, ensuring latency-aware IoT applications achieve their deadlines, while significantly reducing network traffic as well as guaranteeing system availability and reliability of the IoT network.

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“…In 2010 consumption of the country was 581 trillion liters out of which the domestic demand is around 41 trillion liters [9][10]. With the growth of population and an increase in demand the per capita availability of water has come down and is likely to decrease further in the future [11][12]. By 2025 it is expected to lower by 36 percent and by 2050 the forecast is a decrease of 60 percent in per capita water availability.…”

Section: Water Consumption Scenario In Indiamentioning

confidence: 99%

Smart Water Solution for Monitoring of Water Usage Based on Weather Condition

2020

IJETER

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Conservation of water in urban areas is an ongoing challenge in which technology like IoT and WSN is playing a very crucial role. Studies show that 54% of India is facing absolute water scarcity or high economic water stress. To address this challenge the forecasting and monitoring of water consumption along with effective management and distribution are important. This paper implements the seasonal threshold constraint on water distribution which conserves a significant amount of water loss over uniform supply around the year by considering end-user behavior changes according to the season. The results have been confirmed through simulation of the proposed algorithm Weather-based Smart Water Monitoring (WSWM). This extensive study only suggests a possible alternative approach to design the water distribution system to conserve water. However, more work is required for achieving an optimized approach for sustainable urban water management.

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Survey on fault tolerance‐based clustering evolution in WSN

Cited by 30 publications

References 83 publications

Binary Self-Adaptive Salp Swarm Optimization-Based Dynamic Load Balancing in Cloud Computing

Binary Self-Adaptive Salp Swarm Optimization-Based Dynamic Load Balancing in Cloud Computing

A Decentralized Edge Computing Latency-Aware Task Management Method With High Availability for IoT Applications

Smart Water Solution for Monitoring of Water Usage Based on Weather Condition

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