A computational field framework for collaborative task execution in volunteer clouds
A computational field framework for collaborative task execution in volunteer clouds
复制标题
志愿者云中协作任务执行的计算领域框架
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Alberto Lluch
中科院分区：
文献类型：
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作者：
Stefano Sebastio;M. Amoretti;Alberto Lluch
云技术的日益普及为分布式和协作计算提供了新的机会。志愿者云是一个突出的例子，参与者加入和离开平台并通过共享计算资源进行协作。此类场景的高度复杂性、动态性和不可预测性需要去中心化的自我*方法。我们在本文中提出了一个用于设计和评估志愿者云中自适应协作任务执行策略的框架。作为副产品，我们提出了一种基于蚁群优化范式的新颖策略，我们通过对 Google 集群数据进行基于模拟的统计分析来验证该策略。
The increasing diffusion of cloud technologies offers new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing computational resources. The high complexity, dynamism and unpredictability of such scenarios call for decentralized self-* approaches. We present in this paper a framework for the design and evaluation of self-adaptive collaborative task execution strategies in volunteer clouds. As a byproduct, we propose a novel strategy based on the Ant Colony Optimization paradigm, that we validate through simulation-based statistical analysis over Google cluster data.