In mobile crowd computing (MCC), smart mobile devices (SMDs) are utilized as computing resources. To achieve satisfactory performance and quality of service, selecting the most suitable resources (SMDs) is crucial. The selection is generally made based on the computing capability of an SMD, which is defined by its various fixed and variable resource parameters. As the selection is made on different criteria of varying significance, the resource selection problem can be duly represented as an MCDM problem. However, for the real-time implementation of MCC and considering its dynamicity, the resource selection algorithm should be time-efficient. In this paper, we aim to find out a suitable MCDM method for resource selection in such a dynamic and time-constraint environment. For this, we present a comparative analysis of various MCDM methods under asymmetric conditions with varying selection criteria and alternative sets. Various datasets of different sizes are used for evaluation. We execute each program on a Windows-based laptop and also on an Android-based smartphone to assess average runtimes. Besides time complexity analysis, we perform sensitivity analysis and ranking order comparison to check the correctness, stability, and reliability of the rankings generated by each method.

中文翻译：

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移动人群计算中资源选择的多准则决策方法比较分析

在移动人群计算（MCC）中，智能移动设备（SMD）被用作计算资源。要获得令人满意的性能和服务质量，选择最合适的资源 (SMD) 至关重要。选择一般是根据 SMD 的计算能力进行的，计算能力由其各种固定和可变资源参数定义。由于选择是根据不同重要性的不同标准进行的，因此资源选择问题可以适当地表示为 MCDM 问题。然而，对于MCC的实时实现并考虑到其动态性，资源选择算法应该是省时的。在本文中，我们的目标是在这样一个动态和时间约束的环境中找到一种合适的 MCDM 方法来进行资源选择。为了这，我们在具有不同选择标准和替代集的不对称条件下对各种 MCDM 方法进行了比较分析。使用不同大小的各种数据集进行评估。我们在基于 Windows 的笔记本电脑和基于 Android 的智能手机上执行每个程序以评估平均运行时间。除了时间复杂度分析，我们还进行了敏感性分析和排名顺序比较，以检查每种方法生成的排名的正确性、稳定性和可靠性。