BAT algorithm used for load balancing purpose in cloud computing: an overview

Ullah, Arif; Nawi, Nazri Mohd; Khan, Mubashir Hayat

doi:10.1504/ijhpcn.2020.110258

Cited by 24 publications

(11 citation statements)

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“…To balance between the local and global search capability in Bat algorithm, a new search equation is proposed for each Bat based on the history optimal position that it memorized; to avoid falling into a local optimal solution, an abandoned mechanism is adopted for each Bat based on the number of its position has not been improved, to enhance the local search ability, a dynamic adaptive search equation is presented [ 36 ]. Table 2 present the different modified section of Bat algporithm.…”

Section: Recent Workmentioning

confidence: 99%

Improvement for tasks allocation system in VM for cloud datacenter using modified bat algorithm

Ullah

Chakir

2022

Multimed Tools Appl

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Since its inception, cloud computing has greatly transformed our lives by connecting the entire world through shared computational resources over the internet. The COVID-19 pandemic has also disrupted the traditional learning and businesses and led us towards an era of cloud-based activities. Virtual machine is one of the main elements of virtualization in cloud computing that represents physical server into the virtual machine. The utilizations of these VM’s are important to achieved effective task scheduling mechanism in cloud environment. This paper focuses on improvment of the task distribution system in VM for cloud computing using load balancing technique. For that reason modification took place at Bat algorithm fitness function value this section used in load balancer section. When algorithm iteration are complete then time to distribute the task among different VM therefore in this section of algorithm was modified. The second modification took place at the search process of Bat at dimension section. The proposed algorithm is known as modified Bat algorithm. Four parameter are used to check the performance of the system which are throughput, makespan, degree of imbalance and processing time. The proposed algorithm provides efficient result as compaire to other standard technique. Hence the proposed algorithm improved cloud data center accuracy and efficiency.

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Section: Recent Workmentioning

confidence: 99%

Improvement for tasks allocation system in VM for cloud datacenter using modified bat algorithm

Ullah

Chakir

2022

Multimed Tools Appl

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“…Arif Ullah and Nazri Mohd Nawi [85] applied the BAT algorithm in VM to verify that this idea improves load balancing in cloud environments. The idea is that whenever there is a need to entertain a task, an optimal VM among all the available VMs is first searched for.…”

Section: Bat Algorithmmentioning

confidence: 99%

A Survey of Swarm Intelligence Based Load Balancing Techniques in Cloud Computing Environment

Elmagzoub¹,

Syed²,

Shaikh³

et al. 2021

Electronics

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Cloud computing offers flexible, interactive, and observable access to shared resources on the Internet. It frees users from the requirements of managing computing on their hardware. It enables users to not only store their data and computing over the internet but also can access it whenever and wherever it is required. The frequent use of smart devices has helped cloud computing to realize the need for its rapid growth. As more users are adapting to the cloud environment, the focus has been placed on load balancing. Load balancing allocates tasks or resources to different devices. In cloud computing, and load balancing has played a major role in the efficient usage of resources for the highest performance. This requirement results in the development of algorithms that can optimally assign resources while managing load and improving quality of service (QoS). This paper provides a survey of load balancing algorithms inspired by swarm intelligence (SI). The algorithms considered in the discussion are Genetic Algorithm, BAT Algorithm, Ant Colony, Grey Wolf, Artificial Bee Colony, Particle Swarm, Whale, Social Spider, Dragonfly, and Raven roosting Optimization. An analysis of the main objectives, area of applications, and targeted issues of each algorithm (with advancements) is presented. In addition, performance analysis has been performed based on average response time, data center processing time, and other quality parameters.

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“…Load balance among various VMs was also not considered by them. The work [25] proposes to use the Bat algorithm to balance the load on the various VMs, where authors tried to improve the resource allocation for VMs.…”

Section: Literature Reviewmentioning

confidence: 99%

Nature-inspired metaheuristic scheduling algorithms in cloud: a systematic review

Bothra¹,

Singhal²

2021

Naučno-teh. vestn. inf. tehnol. meh. opt.

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Complex huge-scale scientific applications are simplified by workflow to execute in the cloud environment. The cloud is an emerging concept that effectively executes workflows, but it has a range of issues that must be addressed for it to progress. Workflow scheduling using a nature-inspired metaheuristic algorithm is a recent central theme in the cloud computing paradigm. It is an NP-complete problem that fascinates researchers to explore the optimum solution using swarm intelligence. This is a wide area where researchers work for a long time to find an optimum solution but due to the lack of actual research direction, their objectives become faint. Our systematic and extensive analysis of scheduling approaches involves recently high-cited metaheuristic algorithms like Genetic Algorithms (GA), Whale Search Algorithm (WSA), Ant Colony Optimization (ACO), Bat Algorithm, Artificial Bee Colony (ABC), Cuckoo Algorithm, Firefly Algorithm and Particle Swarm Optimization (PSO). Based on various parameters, we do not only classify them but also furnish a comprehensive striking comparison among them with the hope that our efforts will assist recent researchers to select an appropriate technique for further undiscovered issues. We also draw the attention of present researchers towards some open issues to dig out unexplored areas like energy consumption, reliability and security for considering them as future research work.

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BAT algorithm used for load balancing purpose in cloud computing: an overview

Cited by 24 publications

References 0 publications

Improvement for tasks allocation system in VM for cloud datacenter using modified bat algorithm

Improvement for tasks allocation system in VM for cloud datacenter using modified bat algorithm

A Survey of Swarm Intelligence Based Load Balancing Techniques in Cloud Computing Environment

Nature-inspired metaheuristic scheduling algorithms in cloud: a systematic review

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