In the contemporary technological landscape, the process of developing and distributing software that fulfills the objectives of both creators and users while remaining economically viable and technically manageable presents significant challenges. This work examines the potential of cloud computing and the serverless paradigm as third-party infrastructure solutions to address these challenges. Specifically, it proposes a methodology for evaluating and selecting serverless platforms using a multicriteria decision-making approach. The criteria employed in this model were derived from two primary sources: serverless service providers and analyses of benchmarking reports on serverless providers. To assess the efficacy of this approach, experiments were conducted to evaluate both the accuracy and performance of the proposed solution. Additionally, a comparison was made with an existing implementation of the multicriteria method available in a software library. The results of these experiments demonstrated that both the proposed implementation and the existing library implementation of the decision-making multicriteria method achieved 100% accuracy in a controlled environment. However, the algorithm developed in this study exhibited superior performance in terms of runtime when applied to scenarios involving more than 500 serverless providers.

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Scoring and Ranking Serverless Providers Using Multicriteria Decision Method

  • Leandro Ribeiro Rittes,
  • Adriano Fiorese

摘要

In the contemporary technological landscape, the process of developing and distributing software that fulfills the objectives of both creators and users while remaining economically viable and technically manageable presents significant challenges. This work examines the potential of cloud computing and the serverless paradigm as third-party infrastructure solutions to address these challenges. Specifically, it proposes a methodology for evaluating and selecting serverless platforms using a multicriteria decision-making approach. The criteria employed in this model were derived from two primary sources: serverless service providers and analyses of benchmarking reports on serverless providers. To assess the efficacy of this approach, experiments were conducted to evaluate both the accuracy and performance of the proposed solution. Additionally, a comparison was made with an existing implementation of the multicriteria method available in a software library. The results of these experiments demonstrated that both the proposed implementation and the existing library implementation of the decision-making multicriteria method achieved 100% accuracy in a controlled environment. However, the algorithm developed in this study exhibited superior performance in terms of runtime when applied to scenarios involving more than 500 serverless providers.