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Geo-information processing service composition for concurrent tasks: A QoS-aware game theory approach

机译:并发任务的地理信息处理服务组合:一种基于QoS的博弈论方法

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摘要

Typical characteristics of remote sensing applications are concurrent tasks, such as those found in disaster rapid response. The existing composition approach to geographical information processing service chain, searches for an optimisation solution and is what can be deemed a "selfish" way. This way leads to problems of conflict amongst concurrent tasks and decreases the performance of all service chains. In this study, a non-cooperative game-based mathematical model to analyse the competitive relationships between tasks, is proposed. A best response function is used, to assure each task maintains utility optimisation by considering composition strategies of other tasks and quantifying conflicts between tasks. Based on this, an iterative algorithm that converges to Nash equilibrium is presented, the aim being to provide good convergence and maximise the utilisation of all tasks under concurrent task conditions. Theoretical analyses and experiments showed that the newly proposed method, when compared to existing service composition methods, has better practical utility in all tasks.
机译:遥感应用程序的典型特征是并发任务,例如灾难快速响应中发现的那些任务。地理信息处理服务链的现有组合方法正在寻找优化解决方案,这可被视为“自私”的方式。这种方式导致并发任务之间的冲突问题,并降低了所有服务链的性能。在这项研究中,提出了一种基于非合作博弈的数学模型来分析任务之间的竞争关系。使用最佳响应函数,通过考虑其他任务的组成策略并量化任务之间的冲突来确保每个任务维持效用优化。在此基础上,提出了一种收敛到纳什均衡的迭代算法,其目的是在并发任务条件下提供良好的收敛性并最大化所有任务的利用率。理论分析和实验表明,与现有的服务组合方法相比,新提出的方法在所有任务中具有更好的实用性。

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