Accelerated Decentralized Load Balancing in Multi-Agent Networks
Decentralized load balancers are gaining in popularity because they offer scalability, resilience, and the ability to handle high-demand workloads in distributed network systems. In practice, decentralized algorithms face such network issues as connection losses, dropped packets during data transmis...
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10738720/ |
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| author | Victoria Erofeeva Oleg Granichin Elena Volodina |
| author_facet | Victoria Erofeeva Oleg Granichin Elena Volodina |
| author_sort | Victoria Erofeeva |
| collection | DOAJ |
| description | Decentralized load balancers are gaining in popularity because they offer scalability, resilience, and the ability to handle high-demand workloads in distributed network systems. In practice, decentralized algorithms face such network issues as connection losses, dropped packets during data transmission, network latency. They should also account for the physical limitations of real systems. Existing works primarily consider different meta-heuristic approaches to carry out load balancing. Nevertheless, theoretically grounded algorithms that work under non-stationary conditions are of interest. In this paper, we improve the convergence rate of an existing decentralized load balancing protocol based on Local Voting Protocol (LVP) to obtain a solution that tends towards the optimal load balancing strategy over time. We propose a new Accelerated-LVP protocol and derive its parameters required to achieve the acceleration. The simulation demonstrates superiority of the proposed solution over the existing approaches in terms of convergence rate. In our experiments, we consider two scenarios: steady and bursty. In the first scenario, we observe that, on average, the proposed algorithm achieves the lowest error rate 15% faster than the nearest competitor. In the second scenario, on average, the proposed algorithm achieves an error rate that is 10% less than the nearest competitor. |
| format | Article |
| id | doaj-art-8f1fbb786a7345b3bfcfdac65f0edb7f |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-8f1fbb786a7345b3bfcfdac65f0edb7f2025-08-20T02:12:53ZengIEEEIEEE Access2169-35362024-01-011216195416196710.1109/ACCESS.2024.348839910738720Accelerated Decentralized Load Balancing in Multi-Agent NetworksVictoria Erofeeva0https://orcid.org/0000-0001-5107-0293Oleg Granichin1https://orcid.org/0000-0002-3631-7347Elena Volodina2https://orcid.org/0009-0005-6133-9723Centre for Artificial Intelligence and Data Science, St. Petersburg State University, Saint Petersburg, RussiaCentre for Artificial Intelligence and Data Science, St. Petersburg State University, Saint Petersburg, RussiaFaculty of Mathematics and Mechanics, St. Petersburg State University, Saint Petersburg, RussiaDecentralized load balancers are gaining in popularity because they offer scalability, resilience, and the ability to handle high-demand workloads in distributed network systems. In practice, decentralized algorithms face such network issues as connection losses, dropped packets during data transmission, network latency. They should also account for the physical limitations of real systems. Existing works primarily consider different meta-heuristic approaches to carry out load balancing. Nevertheless, theoretically grounded algorithms that work under non-stationary conditions are of interest. In this paper, we improve the convergence rate of an existing decentralized load balancing protocol based on Local Voting Protocol (LVP) to obtain a solution that tends towards the optimal load balancing strategy over time. We propose a new Accelerated-LVP protocol and derive its parameters required to achieve the acceleration. The simulation demonstrates superiority of the proposed solution over the existing approaches in terms of convergence rate. In our experiments, we consider two scenarios: steady and bursty. In the first scenario, we observe that, on average, the proposed algorithm achieves the lowest error rate 15% faster than the nearest competitor. In the second scenario, on average, the proposed algorithm achieves an error rate that is 10% less than the nearest competitor.https://ieeexplore.ieee.org/document/10738720/Load balancingdecentralized networksaccelerated algorithmsnon-stationary optimizationLocal Voting Protocolnetwork disruptions |
| spellingShingle | Victoria Erofeeva Oleg Granichin Elena Volodina Accelerated Decentralized Load Balancing in Multi-Agent Networks IEEE Access Load balancing decentralized networks accelerated algorithms non-stationary optimization Local Voting Protocol network disruptions |
| title | Accelerated Decentralized Load Balancing in Multi-Agent Networks |
| title_full | Accelerated Decentralized Load Balancing in Multi-Agent Networks |
| title_fullStr | Accelerated Decentralized Load Balancing in Multi-Agent Networks |
| title_full_unstemmed | Accelerated Decentralized Load Balancing in Multi-Agent Networks |
| title_short | Accelerated Decentralized Load Balancing in Multi-Agent Networks |
| title_sort | accelerated decentralized load balancing in multi agent networks |
| topic | Load balancing decentralized networks accelerated algorithms non-stationary optimization Local Voting Protocol network disruptions |
| url | https://ieeexplore.ieee.org/document/10738720/ |
| work_keys_str_mv | AT victoriaerofeeva accelerateddecentralizedloadbalancinginmultiagentnetworks AT oleggranichin accelerateddecentralizedloadbalancinginmultiagentnetworks AT elenavolodina accelerateddecentralizedloadbalancinginmultiagentnetworks |