For mobile clients, sufficient resources with the assurance of efficient performance and energy efficiency are the core concerns. This article mainly considers this need and proposes a resourceful architecture, called mRARSA that addresses the critical need in a mobile cloud environment. This architecture consists of cloud resources, mobile devices, and a set of functional components. The performance efficiency evaluates implementing the proposed context-aware multi-criteria decision offloading algorithm. This algorithm considers both device context (network parameters) and application content (task size) at run time when offloading an executable code to allocate the cloud resources. The appropriate resources select based on offloading decisions and via the wireless communication channels. The architecture’s remarkable component is the signal strength analyzer that determines the signal quality (e.g.-60 dBm) and contributes to performance efficiency. The proposed prototype model has implemented several times to monitor the performance efficiency, mobility, performance at communication barriers, and the outcomes of resource-demanding application’s execution. Results indicate performance improvement, such as the algorithm appropriately decides the cloud resources based on device network context, application content, mobility, and the signal strength quality and range. Moreover, the results also show significant improvement in achieving performance and energy efficiency. Sufficient resources and performance efficiency are the most significant features that distinguish this framework from the other existing frameworks.

中文翻译：

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高效的资源丰富的移动云架构（mRARSA），用于资源要求苛刻的应用程序

对于移动客户，核心资源是保证高效性能和能源效率的充足资源。本文主要考虑了这一需求，并提出了一个称为mRARSA的资源丰富的体系结构，该体系结构解决了移动云环境中的关键需求。此体系结构由云资源，移动设备和一组功能组件组成。性能效率评估实现所提出的上下文感知多准则决策卸载算法。当卸载可执行代码以分配云资源时，该算法在运行时同时考虑设备上下文（网络参数）和应用程序内容（任务大小）。适当的资源根据卸载决策并通过无线通信信道进行选择。该架构的杰出组成部分是信号强度分析仪，它确定信号质量（例如60 dBm）并有助于提高性能。所提出的原型模型已实施了多次，以监视性能效率，移动性，通信障碍下的性能以及对资源要求较高的应用程序执行的结果。结果表明性能有所提高，例如该算法可根据设备网络上下文，应用程序内容，移动性以及信号强度质量和范围来适当地确定云资源。此外，结果还显示出在实现性能和能源效率方面的显着改善。足够的资源和性能效率是使该框架与其他现有框架区分开的最重要特征。