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

Elmagzoub, M. A.; Syed, Darakhshan; Shaikh, Asadullah; Islam, Noman; Alghamdi, Abdullah; Rizwan, Syed

doi:10.3390/electronics10212718

Cited by 24 publications

(14 citation statements)

References 112 publications

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“…To automate defenses and enforce data governance principles, invest in cloud cyber security platforms that use automation and AI ( [1], [16]). Organizations can more easily identify and classify potential threats by automating the process using behavioral analytics ( [17], [4]).…”

Section: Discussionmentioning

confidence: 99%

Major Security Threats and Attacks that Facing Cloud Computing with the Main Defence Strategies

2022

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Cloud Computing (Cloud) enables ubiquitous network access to a pool of shared and configurable resources. It is based on shared services and infrastructure convergence. Cloud computing offers a slew of advantages, including the ability to store large amounts of data and a variety of services, as well as addressing the issue of scarce resources and lowering service costs. Regardless of its benefits, the shift from local to remote computing has created a slew of security concerns and challenges for both consumer and provider. Addressing and evaluating cloud computing challenges is critical. Thus, by discussing cloud computing challenges alongside available and potential solutions, users, developers, and businesses can identify pertinent and timely responses to specific threats, resulting in the best possible cloud computing-based services. The purpose of this article is to discuss the inherent difficulties associated with cloud computing and some critical solutions for overcoming them. This article extracted and analyzed seminal papers in order to contribute to the corpus of literature by highlighting several critical challenges in the cloud computing domain and shedding light on how these challenges affect a variety of domains, including users, sites, and business. The most frequently mentioned challenges include data loss, data breaches, account or service hijacking, insecure interfaces and APIs, malicious insiders, insufficient due diligence, abusive cloud service use, shared technology issues, unknown risk profile, identity theft, business model changes, lock-in, cryptography, cloud data recycling, malware, and untrusted computing. This paper addressed these issues by incorporating previously discovered solutions. There has been discussion of the implications for both researchers and practitioners

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Section: Discussionmentioning

confidence: 99%

Major Security Threats and Attacks that Facing Cloud Computing with the Main Defence Strategies

2022

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“…Traditional research methods can't keep pace with the fast-changing technological world. 5G also lowered the network data use requirement thus under the presence of 5 G cloud-based application testing is achievable S. Afzal and G. Kavitha, [42] concerned about load balancing during the load balancing period, the supplier must carry additional costs when accomplishing a migration that equates to a reduction in profit due to decline in resources. it is linked to load balancing by the cloud service (CLS) An improved load balancing (IMB) algorithm is developed to lower migration costs The IMB migration expense indicates that.…”

Section: Software As a Service (Saas)mentioning

confidence: 99%

Performance Analysis of Enterprise Cloud Computing: A Review

Malallah¹,

Qashi²,

Abdulrahman³

et al. 2023

JASTT

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Cloud computing has swiftly established itself as the norm in its field as a result of the advantages described above. In an attempt to reduce the amount of time spent on infrastructure upkeep, an increasing number of businesses are moving their operations to the cloud. As a result, maintaining a cloud environment has proved to be exceedingly difficult. It is necessary to have an efficient cloud monitoring system in order to reduce the workload associated with administration and improve cloud operation. The cloud monitoring service is beneficial since it has the potential to improve performance and make administration easier. The administration of Quality of Service (QoS) parameters for cloud-hosted, virtualized, and physical services and applications is one of the most important responsibilities of cloud monitoring. As a result, cloud management software retains a record of both actions and services, and it also conducts dynamic setups of the cloud in order to increase operational effectiveness. The performance of businesses and businesses as a whole was examined in this article, as was the influence that cloud-ready programs and tools have on that performance, as well as the advantages that may be obtained from adopting such programs and products.

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“…Future research could look into new meta-heuristic evolutionary techniques for balancing load in terms of energy consumption, and quality of service [39]. Social Spider Algorithm (SSA) is also used for task scheduling which is an efficient approach to adapting the global best match, but when the number of VMs increases, it shows slow convergence [40].…”

Section: Related Workmentioning

confidence: 99%

A Fast Converging and Globally Optimized Approach for Load Balancing in Cloud Computing

et al. 2023

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Cloud Computing is the dynamic provisioning of resources to provide services to end-users over the internet. The realization of cloud computing requires addressing several challenges, such as resource discovery, security, scheduling, and load balancing. Among these research issues, load balancing is the most challenging one. Therefore, in the past few years, research into various static and dynamic algorithms to achieve optimal results is gaining importance. This research proposes Swarm Intelligence (SI) as a loadbalancing solution for cloud computing. Several alternatives in the literature (like genetic algorithm, ACO, PSO, BAT, GWO, and many others) are investigated, but none consider the load balancing convergence time with global optimization. Among these algorithms, this research emphasizes Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). A combined approach of GWO-PSO that capitalizes on the benefits of fast convergence and global optimization is proposed in this paper. These two techniques enhance system efficiency and resource allocation, working together to solve the load-balancing challenge. Compared to other traditional approaches, the findings of this research are promising while achieving globally optimized fast convergence and reducing overall response time. On average, the overall response time of the proposed technique is reduced to 12% as compared to other algorithms. Furthermore, the best optimal value obtained from the objective function of the proposed GWO-PSO algorithm improves PSO to 97.253% in terms of convergence.

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

Cited by 24 publications

References 112 publications

Major Security Threats and Attacks that Facing Cloud Computing with the Main Defence Strategies

Major Security Threats and Attacks that Facing Cloud Computing with the Main Defence Strategies

Performance Analysis of Enterprise Cloud Computing: A Review

A Fast Converging and Globally Optimized Approach for Load Balancing in Cloud Computing

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