Enhancing Load Balancing Efficiency in Distributed Systems through Linear Programming Techniques in WSCLB DOI Open Access

Paul Sheeba Ranjini,

Tulasiram Hemamalini,

A.N. Senthilvel

и другие.

International Journal of Computational and Experimental Science and Engineering, Год журнала: 2025, Номер 11(2)

Опубликована: Апрель 1, 2025

Optimizing network performance and resource allocation fairness in distributed systems requires load balancing efficiency. The main goal is to design deploy Linear Programming (LP) methods Weighted Server Cluster Load Balancer (WSCLB) accomplish this goal. These reallocate jobs between nodes reduce distribution discrepancies, avoiding bottlenecks boosting system performance. purpose balance load, so each node runs at optimum capacity, lowering latency improving resilience. solution uses LP optimize WSCLB, creating a more robust efficient that can handle variable demand without deterioration. study emphasizes mathematical optimization's role current balancing. first instance of Load_Distribution_Pre-Optimization showed 5 levels for nodes. In level 1, the top lower values are 93 15, 2, 87 21, 3, 88 24, 4, 75 10, 5, 89 44. Load_Distribution_Post-Optimization were observed. 29, 96 72 49, 94 42, 91 14.

Язык: Английский

Enhancing Load Balancing Efficiency in Distributed Systems through Linear Programming Techniques in WSCLB DOI Open Access

Paul Sheeba Ranjini,

Tulasiram Hemamalini,

A.N. Senthilvel

и другие.

International Journal of Computational and Experimental Science and Engineering, Год журнала: 2025, Номер 11(2)

Опубликована: Апрель 1, 2025

Optimizing network performance and resource allocation fairness in distributed systems requires load balancing efficiency. The main goal is to design deploy Linear Programming (LP) methods Weighted Server Cluster Load Balancer (WSCLB) accomplish this goal. These reallocate jobs between nodes reduce distribution discrepancies, avoiding bottlenecks boosting system performance. purpose balance load, so each node runs at optimum capacity, lowering latency improving resilience. solution uses LP optimize WSCLB, creating a more robust efficient that can handle variable demand without deterioration. study emphasizes mathematical optimization's role current balancing. first instance of Load_Distribution_Pre-Optimization showed 5 levels for nodes. In level 1, the top lower values are 93 15, 2, 87 21, 3, 88 24, 4, 75 10, 5, 89 44. Load_Distribution_Post-Optimization were observed. 29, 96 72 49, 94 42, 91 14.

Язык: Английский

Процитировано

0