Metaheuristic Optimization for Dynamic Task Scheduling in Cloud Computing Environments DOI Open Access

Longyang Du,

Qingxuan Wang

International Journal of Advanced Computer Science and Applications, Journal Year: 2024, Volume and Issue: 15(7)

Published: Jan. 1, 2024

Cloud computing enables the sharing of resources across Internet in a highly adaptable and quantifiable way. This technology allows users to access customizable distributed offers various services for resource allocation, scientific operations, service via virtualization. Effectively allocating tasks available is essential providing reliable consumer performance. Task scheduling cloud models presents substantial challenges as it necessitates an efficient scheduler map multiple from numerous sources dynamically distribute based on their requirements. study metaheuristic optimization methodology that integrates load balancing by distributing current conditions. ensures even distribution workloads, preventing bottlenecks enhancing overall system The suggested method suitable both constant variable activities. Our technique was compared with established methods, including HDD-PLB, HG-GSA, CAAH. proposed demonstrated superior performance due its adaptive mechanism utilization, reducing task completion times improving throughput.

Language: Английский

Context-aware IoT search engine through fuzzy clustering: Search space restructuring and query resolution mechanisms DOI
Santosh Pattar, Veena Badiger, Yash Madhav Kangralkar

et al.

Internet of Things, Journal Year: 2025, Volume and Issue: unknown, P. 101494 - 101494

Published: Jan. 1, 2025

Language: Английский

Citations

0
Hybrid Optimization Method for Social Internet of Things Service Provision Based on Community Detection DOI Creative Commons

Bahar Allakaram Tawfeeq,

Amir Masoud Rahmani, Abbas Koochari

et al.

Engineering Reports, Journal Year: 2025, Volume and Issue: 7(4)

Published: March 29, 2025

ABSTRACT The Internet of things (IoT) and social networks integrate into a new area called the (SIoT). SIoT is characterized as network that has enhanced intelligence awareness. Essential criteria for both IoT involve effective service provisioning determination device methods. discovery services selecting optimal solution to composite them are challenges environment. Addressing these requires efficient optimization Traditional algorithms have strengths weaknesses. For example, genetic algorithm (GA) can find global optima but suffer from diversity disappearing prematurely, whereas backtracking search (BSA) offers better exploration converges more slowly. This article proposes hybrid improved based on community detection (IGBSA‐CD) overview limitations. approach improves GA's ability integrates with advantages BSA identify suitable devices fulfill user requirements by applying optimized provision (discovery, selection, composition) in detected communities. It reduce space discovery. experimental results show suggested surpasses current clustering techniques execution time cluster quality. IGBSA‐CD rapidly produces solutions near‐optimal average success rates over 96.3% different sample sizes. fitness values each size task also exhibit similar convergence, which stabilizes at 0.2–0.3 after multiple generations. response presents it all three tasks 0.04 s. consistently lower time, even when complex. Furthermore, outperforms other approaches superior quality adaptability within

Language: Английский

Citations

0
The Influence of Three Parent Crossbreeding on the Dual Population Genetic Algortihm DOI Creative Commons
Esra’a Alkafaween,

Obada Alhabashneh,

Maram M. Al-Mjali

et al.

Communications - Scientific letters of the University of Zilina, Journal Year: 2025, Volume and Issue: unknown

Published: April 16, 2025

Language: Английский

Citations

0
Trusted Web Service Discovery Based on a Swarm Intelligence Algorithm DOI Creative Commons
Zhengwang Ye,

H. Y. Sheng,

Haiyang Zou

et al.

Mathematics, Journal Year: 2025, Volume and Issue: 13(9), P. 1402 - 1402

Published: April 25, 2025

The number of services on the internet has experienced explosive growth, and rapid accurate discovery required among a vast array similarly functioning with differing degrees quality become critical challenging aspect service computing. In this paper, we propose trusted algorithm based an ant colony system (TSDA-ACS). integrates credibility-based trust model search to facilitate web services. During evaluation process, employs pseudo-stochastic proportion select nodes, where nodes higher reputation have greater probability being chosen. uses voting method calculate credibility factoring in both non-credibility from query node’s perspective. information acquisition strategy, merging routing random wave strategy guide search. To evaluate effectiveness TSDA-ACS, paper introduces walk (RW), classic max–min (MMAS), trustworthy modified (TSDMACS) for comparison TSDA-ACS algorithm. experiments demonstrate that can achieve high recall precision rates. Finally, efficacy proposed is validated through across various network environments.

Language: Английский

Citations

0
Towards Efficient Information Retrieval in Internet of Things Environments Via Machine Learning Approaches DOI
Qin Yuan,

Yuping Lai

Journal of The Institution of Engineers (India) Series B, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 17, 2024

Language: Английский

Citations

1
Metaheuristic Optimization for Dynamic Task Scheduling in Cloud Computing Environments DOI Open Access

Longyang Du,

Qingxuan Wang

International Journal of Advanced Computer Science and Applications, Journal Year: 2024, Volume and Issue: 15(7)

Published: Jan. 1, 2024

Cloud computing enables the sharing of resources across Internet in a highly adaptable and quantifiable way. This technology allows users to access customizable distributed offers various services for resource allocation, scientific operations, service via virtualization. Effectively allocating tasks available is essential providing reliable consumer performance. Task scheduling cloud models presents substantial challenges as it necessitates an efficient scheduler map multiple from numerous sources dynamically distribute based on their requirements. study metaheuristic optimization methodology that integrates load balancing by distributing current conditions. ensures even distribution workloads, preventing bottlenecks enhancing overall system The suggested method suitable both constant variable activities. Our technique was compared with established methods, including HDD-PLB, HG-GSA, CAAH. proposed demonstrated superior performance due its adaptive mechanism utilization, reducing task completion times improving throughput.

Language: Английский

Citations

0