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Research on dynamic and static load balancing algorithm based on improved Ant colony algorithm

Published: 28 June 2024 Publication History

Abstract

With the popularity and rapid development of the Internet, software applications have increasingly high requirements for concurrency and quality of service. However, the traditional single server architecture is limited by factors such as hardware and network bandwidth, which cannot cope with a large number of concurrent business requests. In order to improve this situation and enhance the efficiency of load balancing, this paper proposes a load balancing algorithm that combines dynamic and static load balancing with an improved ant colony algorithm. The algorithm integrates the features of static load balancing algorithm and dynamic load balancing algorithm. First, the calculation is performed based on the ratio of the current server node's weight to the weight assigned to the server node. When the weight ratio is less than the set factor, the cluster uses static polling algorithm. When the weight ratio of a server in the cluster is detected to be higher than the set factor, the minimum number of connections algorithm in the dynamic load balancing algorithm is used and combined with the improved ant colony algorithm (Im-ACO) to recalculate the load situation of each node. This algorithm quickly finds the best path to the minimum load server dynamically, so that the load of this node is reasonably distributed to other nodes, thus achieving the overall balanced load effect. To evaluate the performance of the algorithm, comparative experiments are conducted in this paper and compared with the static weighted polling algorithm, the dynamic probabilistic meritocratic algorithm and the minimum connection number algorithm. The experimental results show that the proposed algorithm can effectively improve the response time and the actual number of concurrent connections of the server and has better performance. Under the condition of guaranteed load balancing, the algorithm can shorten the task completion time as much as possible and show better scalability effect.

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ICRSA '23: Proceedings of the 2023 6th International Conference on Robot Systems and Applications
September 2023
335 pages
ISBN:9798400708039
DOI:10.1145/3655532
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 28 June 2024

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Author Tags

  1. Dynamic static load balancing algorithm
  2. High concurrency
  3. Improved ant colony algorithm
  4. Load Balancing

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