A Comparative Analysis of Multi-Criteria Decision-Making Methods for Resource Selection in Mobile Crowd Computing

Abstract

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.

A multi-criteria framework for comparing dividend pay capabilities: Evidence from Indian FMCG and consumer durable sector

“…Table 10 presents the decision matrix used for obtaining the overall ranking of the alternatives. We apply Simple Additive Weighting (SAW) method for deriving the overall ranks as followed in many past research (for instance, Biswas, 2020b, Pramanik et al, 2021. 11 exhibits the overall ranking of the alternatives using the BC method.…”

“…The alternative, which has higher PDA and/or lower NDA, is considered as the best alternative among the others (Keshavarz Ghorabaee et al, 2015). EDAS has been applied in various real-life problems concerned with selection of best possible alternatives subject to influence of a set of criteria, for example, performance based selection of mutual funds (Karmakar et al, 2018), carpenter manufacturer selection (Stević et al, 2018), resource selection under dynamic environment for crowd computing for smartphones (Pramanik et al, 2021), green supplier selection (Wei et al, 2021), strategic decision for international market selection (Zolfani et al, 2021), 3D printer selection in digital manufacturing (Lei et al, 2022), and green financing (Su et al, 2022) among others. In what follows are the advantages of the EDAS method:…”

A New Spherical Fuzzy LBWA-MULTIMOOSRAL Framework: Application in Evaluation of Leanness of MSMEs in India

“…e results obtained by using multi-criteria decision-making (MCDM) methods, especially in a group decision-making setup, are vulnerable to the changes in the given conditions such as changes in the criteria values, alternative and criteria set, exclusion or inclusion of the criteria and alternatives, and changes in the weights, among others [90][91][92]. erefore, it is essential to examine the validity testing and checking of stability in the results.…”

A Cross-Sectional Study on Mental Health of School Students during the COVID-19 Pandemic in India

“…Therefore, sensitivity analysis is of paramount importance here. Sensitivity analysis is carried out to check the stability of the result, obtained by using a MCDM algorithm under the influence of changes in the given conditions, for example, calculation of the criteria weights, changes in the criteria and alternative sets, interplay among the alternatives and criteria among the others [62][63][64][65][66][67][68]. In our paper, we change the values of the coefficient of elasticity and examine the changes in the criteria weights.…”