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Integrating mobile and cloud resources management using the cloud personal assistant

机译:使用云个人助手集成移动和云资源管理

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The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources. (C) 2014 Elsevier B.V. All rights reserved.
机译:移动云计算模型有望解决移动设备的资源限制,但是要有效地实现此模型是困难的。以前有关移动云计算的工作要求用户与云基础架构建立连续的高质量连接。这是不希望的,而且可能是不可行的,因为在移动设备上保持连接所需的能量很大,并且传输的数据量很大。带宽往往是相当可变的,并且在蜂窝网络上很低。云部署本身也需要有效地向用户分配可伸缩资源。在本文中,我们制定了最佳实践,以有效管理移动云模型所需的资源,即能源,带宽和云计算资源。这些做法可以通过我们的以云个人助手(CPA)为特色的移动云中间件项目来实现。我们将其与该领域的其他方法进行比较,以强调最小化这些资源的使用的重要性,从而确保最终用户成功采用该模型。基于使用移动设备执行的实验结果,我们开发了一种无开销的决策模型,用于将任务和数据卸载到用户的CPA中,从而提供对移动云资源的有效管理。 (C)2014 Elsevier B.V.保留所有权利。

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