Load Balancing Techniques in Cloud Computing: Extensive Review

Alkhatib, Ahmad Aa; Alsabbagh, Abeer; Maraqa, Randa; AlZu’bi, Shadi

doi:10.25046/aj060299

Cited by 25 publications

(11 citation statements)

References 32 publications

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“…Load balancing algorithms could solve the issues of the workload but may suffer from some challenges in the cloud [24,25]. These challenges can make a negative impact on the cloud environment [7]. Scalability is one of the most critical issues that should be solved to improve the response time belongs to storage and power.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Load balancing algorithms are classified according to (i) their system which is static, dynamic, and hybrid load balancing algorithms [7,32]. (ii) the features of data so the load balancing algorithms are divided into schedule or allocation tasks.…”

Section: Load Balancing Algorithm Types and Classificationmentioning

confidence: 99%

“…(iv) the methods of load balancing (hardware or application) [29,33]. (v) the techniques that are used in the environment [7]. There are some proper algorithms classified as follows:…”

Section: Load Balancing Algorithm Types and Classificationmentioning

confidence: 99%

“…• Round Robin (RR) load-balancing algorithm: it is a static algorithm and is considered the easiest method that could deal with Virtual Machines (VM) [7]. In this method, all tasks assigned to VM are equal.…”

Section: Load Balancing Algorithm Types and Classificationmentioning

confidence: 99%

“…Cloud computing is used in demand so users should pay for services to get access easily and flexibly [5,6]. Users face many challenges and issues to deal with cloud computing technology because of workload so CC technology requires many experiments to improve and develop its usability of this technology [7,8]. Load balancing algorithms become the key factor to achieve maximum performance for the cloud environment.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Load Balancing Based on Multi-Agent Framework to Enhance Cloud燛nvironment

Hessen¹,

Abdul-Kader²,

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et al. 2023

Computers, Materials &Amp; Continua

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According to the advances in users' service requirements, physical hardware accessibility, and speed of resource delivery, Cloud Computing (CC) is an essential technology to be used in many fields. Moreover, the Internet of Things (IoT) is employed for more communication flexibility and richness that are required to obtain fruitful services. A multi-agent system might be a proper solution to control the load balancing of interaction and communication among agents. This paper proposes a multi-agent load balancing framework that consists of two phases to optimize the workload among different servers with large-scale CC power with various utilities and a significant number of IoT devices with low resources. Different agents are integrated based on relevant features of behavioral interaction using classification techniques to balance the workload. A load balancing algorithm is developed to serve users' requests to improve the solution of workload problems with an efficient distribution. The activity task from IoT devices has been classified by feature selection methods in the preparatory phase to optimize the scalability of CC. Then, the server's availability is checked and the classified task is assigned to its suitable server in the main phase to enhance the cloud environment performance. Multi-agent load balancing framework is succeeded to cope with the importance of using large-scale requirements of CC and (low resources and large number) of IoT.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Load Balancing Algorithm Types and Classificationmentioning

confidence: 99%

“…(iv) the methods of load balancing (hardware or application) [29,33]. (v) the techniques that are used in the environment [7]. There are some proper algorithms classified as follows:…”

Section: Load Balancing Algorithm Types and Classificationmentioning

confidence: 99%

Section: Load Balancing Algorithm Types and Classificationmentioning

confidence: 99%