Joint Optimization of Delay and Energy in Partial Offloading Using Dual-Population Replicator Dynamics DOI

Mohammad Hassan Khoobkar,

Mehdi Dehghan Takht Fooladi,

Mohammad Hossein Rezvani

et al.

SSRN Electronic Journal, Journal Year: 2022, Volume and Issue: unknown

Published: Jan. 1, 2022

Due to the growing demand for delay-sensitive computing, partial offloading has recently attracted significant attention research community. The most appropriate mathematical tool modeling behavior of selfish agents when interacting with each other is game theory. Because solutions proposed in previous classical theory consider user as a player, they may not be scalable. Moreover, dynamic changes fog environment have been ignored almost all research. This paper presents dual-population using replicator dynamics considering interaction between and computing environment. Unlike theory, here, strategy selected offload computation viewed player. method can very efficiently model growing/shrinking two populations CPU cycles on both network sides. We obtain conditions under which latency energy consumption are jointly minimized compared full local execution modes. simulation results show superiority over baseline state-of-the-art techniques saving time energy.

Language: Английский

Link prediction in multilayer networks using weighted reliable local random walk algorithm DOI
Zhiping Luo, Jian Yin, Guangquan Lu

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 247, P. 123304 - 123304

Published: Jan. 23, 2024

Language: Английский

Citations

7

Optimal placement of applications in the fog environment: A systematic literature review DOI
Mohammad Mainul Islam, Fahimeh Ramezani, Haiyan Lu

et al.

Journal of Parallel and Distributed Computing, Journal Year: 2022, Volume and Issue: 174, P. 46 - 69

Published: Dec. 9, 2022

Language: Английский

Citations

18

IOTD: intelligent offloading of tasks with deadlines in edge-fog-cloud computing environment using hybrid approach DOI

Posham Bhargava Reddy,

Chapram Sudhakar

Cluster Computing, Journal Year: 2024, Volume and Issue: 27(7), P. 9873 - 9885

Published: April 30, 2024

Language: Английский

Citations

3

Joint optimization of delay and energy in partial offloading using Dual-population replicator dynamics DOI

Mohammad Hassan Khoobkar,

Mehdi Dehghan Takht Fooladi,

Mohammad Hossein Rezvani

et al.

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 216, P. 119417 - 119417

Published: Dec. 9, 2022

Language: Английский

Citations

14

Speech cryptography algorithms: utilizing frequency and time domain techniques merging DOI
Osama S. Faragallah,

M. Farouk,

Hala S. El‐sayed

et al.

Journal of Ambient Intelligence and Humanized Computing, Journal Year: 2024, Volume and Issue: 15(10), P. 3617 - 3649

Published: Aug. 9, 2024

Language: Английский

Citations

2

A learning automata based approach for module placement in fog computing environment DOI

Yousef Abofathi,

Babak Anari, Mohammad Masdari

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 237, P. 121607 - 121607

Published: Sept. 15, 2023

Language: Английский

Citations

5

A Distributed Resource Sharing Mechanism in Edge-Enabled IIoT Systems DOI

Huan Liu,

Shiyong Li, Wenzhe Li

et al.

IEEE Internet of Things Journal, Journal Year: 2023, Volume and Issue: 11(8), P. 14296 - 14312

Published: Dec. 13, 2023

The Industrial Internet of Things (IIoT) has revolutionized industrial processes by facilitating the seamless connectivity and communication devices systems within environments. As a critical component, edge computing provides flexible data sensing real-time processing services, which facilitates comprehensive enhancement for IIoT systems. However, due to tremendous increase in limited resources servers, ensuring efficient resource sharing while prioritizing benefits both parties would be driving force edge-enabled In this work, we propose distributed mechanism objective proposed is maximizing social welfare optimizes utility device cost server simultaneously. particular, integrate soft-defined network (SDN) technique into threelayer framework support agile management formulate optimization models multiple scenarios. Furthermore, design alternating direction method multipliers (ADMMs) algorithms appropriately decompose primal problem subproblems explore their interactive relationships requesting using characteristic ADMM. Finally, extensive performance evaluations are conducted under scenarios manifest effectiveness reliability terms convergence rate, fault tolerance.

Language: Английский

Citations

5

Enhanced Clustering MAC Protocol Based on Learning Automata for UV Networks DOI Creative Commons
Cheng Li, Zhiyong Xu, Jingyuan Wang

et al.

Photonics, Journal Year: 2024, Volume and Issue: 11(4), P. 340 - 340

Published: April 7, 2024

Ultraviolet (UV) networks are widely applied in complex electromagnetic environments. Designing an efficient multi-node medium access control (MAC) protocol for these is important. In this study, we proposed enhanced clustering time division multiple (TDMA) MAC based on and learning automata (LA). Subsequently, the effects of network topology, class service, number cluster nodes performance under were analyzed. Then, was compared with TDMA system. Results revealed that it obtained a better performance, proving its suitability UV networking.

Language: Английский

Citations

1

Federated learning inspired Antlion based orchestration for Edge computing environment DOI Creative Commons

H. S. Madhusudhan,

Punit Gupta

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(6), P. e0304067 - e0304067

Published: June 4, 2024

Edge computing is a scalable, modern, and distributed architecture that brings computational workloads closer to smart gateways or devices. This model delivers IoT (Internet of Things) computations processes the requests from network. In diverse independent environment like Fog-Edge, resource management critical issue. Hence, scheduling vital process enhance efficiency allocation resources properly tasks. The manuscript proposes an Artificial Neural Network (ANN) inspired Antlion algorithm for task orchestration environments. Its aim utilization reduce energy consumption. Comparative analysis with different algorithms shows proposed balances load on layer, which results in lower cloud, improves power consumption, CPU utilization, network reduces average waiting time requests. tested healthcare application environment. evaluation outperforms existing fuzzy logic algorithms. performance ANN based approach evaluated using metrics, respectively. It logic, round robin algorithm. technique achieves cloud consumption improvement 95.94%, 16.79%, 19.85% environment, 10.64% 23.33% decreases by 96% compared 1.4% round-robin

Language: Английский

Citations

1

Learning automaton-based energy-efficient and fault-tolerant topology evolution algorithm for underwater acoustic sensor network DOI

Mingru Dong,

Haibin Li, Yongtao Hu

et al.

Journal of Network and Computer Applications, Journal Year: 2023, Volume and Issue: 217, P. 103690 - 103690

Published: June 19, 2023

Language: Английский

Citations

3