Load management is an essential and important factor for distributed simulations running on shared resources due to load imbalances that can caused considerable performance loss. High Level Architecture (HLA) -based simulation is a framework that works to facilitate the design and management of distributed simulations. HLA coordinates the interaction between simulation entities (federates). However, HLA-based simulation standards do not present the ability to manage resources or help detect load imbalances that could directly cause decrease of performance. Focusing on this constraint, a migration-aware dynamic balancing system has been designed for HLA simulations to offer an efficient load-balancing scheme that works in large-scale environments. This system presents some limitations on estimating costs and benefits, so we propose an enhancement to this existing load balancing system, which improves the accuracy of estimating the number of migrations for the next load redistribution. The proposed scheme detects the load imbalances by evaluating the recourses overhead. The scheme classifies the recourses based on the overhead as overloaded and underloaded, followed by matching the highest overloaded recourses with the lowest underloaded recourses. Furthermore, the proposed scheme aims to precisely estimate the number of migrations by evaluating and analyzing the recourses to obtain the best number of migrations. Therefore, certain migrations that do not contribute to an improvement in the simulation performance are avoided. This avoidance is based on comparing time delay and time gain. Moreover, to be considered for migration, the overall sum of the time gains should be larger than the overall sum of the time delays. The proposed scheme has shown an improvement on decreasing the execution time.
Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/32558 |
Date | January 2015 |
Creators | Alghamdi, Turki |
Contributors | Boukerche, Azzedine |
Publisher | Université d'Ottawa / University of Ottawa |
Source Sets | Université d’Ottawa |
Language | English |
Detected Language | English |
Type | Thesis |
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