2015 IEEE 16th International Symposium on High Assurance Systems Engineering (HASE) (2015)
Daytona Beach Shores, FL, USA
Jan. 8, 2015 to Jan. 10, 2015
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HASE.2015.19
High-Assurance applications usually require achieving fast response time and high throughput on a constant basis. To fulfil these stringent quality of service requirements, these applications are commonly deployed in clustered instances. However, how to effectively manage these clusters has become a new challenge. A common approach is to deploy a front-end load balancer to optimise the workload distribution among the clustered applications. Thus, researchers have been studying how to improve the effectiveness of a load balancer. Our previous work presented a novel load balancing strategy which improves the performance of a distributed Java system by avoiding the performance impacts of Major Garbage Collection, which is a common cause of performance degradation in Java applications. However, as that strategy used a static configuration, it could only improve the performance of a system if the strategy was configured with domain expert knowledge. This paper extends our previous work by presenting an adaptive GC-aware load balancing strategy which self-configures according to the GC characteristics of the application. Our results have shown that this adaptive strategy can achieve higher throughput and lower response time, compared to the round-robin load balancing, while also avoiding the burden of manual tuning.
Load management, Java, Memory management, Benchmark testing, Prediction algorithms, Resource management, History
A. O. Portillo-Dominguez, M. Wang, J. Murphy and D. Magoni, "Adaptive GC-Aware Load Balancing Strategy for High-Assurance Java Distributed Systems," 2015 IEEE 16th International Symposium on High Assurance Systems Engineering (HASE), Daytona Beach Shores, FL, USA, 2015, pp. 68-75.