Efficient resource management in the cloud: From simulation to experimental validation using a low‐cost Raspberry Pi testbed. (29th November 2018)

• Record Type: Journal Article
• Authors: Maenhaut, Pieter‐Jan; Volckaert, Bruno; Ongenae, Veerle; De Turck, Filip
• Is Part Of: Software, practice & experience. Volume 49:Number 3(2019)
• Page Start: 449
• Page End: 477
• Publication Date: 2018-11-29
• Subjects: cloud computing -- experimental validation -- Raspberry Pi testbed -- resource allocation -- simulations; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2669
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: Within the context of cloud computing, efficient resource management is of great importance as it can result in higher scalability and significant energy and cost reductions over time. Because of the high complexity and costs of cloud environments, however, newly developed resource allocation strategies are often only validated by means of simulations, for example, by using CloudSim or custom‐developed simulation tools. This article describes a general approach for the validation of cloud resource allocation strategies, illustrating the importance of experimental validation on physical testbeds. Furthermore, the design and implementation of Raspberry Pi as a Service (RPiaaS), a low‐cost embedded testbed built using Raspberry Pi nodes, is presented. RPiaaS aims to facilitate the step from simulations toward experimental evaluations on larger cloud testbeds and is designed using a microservice architecture, where experiments and all required management services are running inside containers. The performance of the RPiaaS testbed is evaluated using several benchmark experiments. The obtained results not only illustrate that the overhead of both using containers and running the required RPiaaS services is minimal but also provide useful insights for scaling up experiments between the Raspberry Pi testbed and a larger more traditional cloud testbed. The introduced validation approach is then illustrated using a case study focusing on the allocation of hierarchically structured tenant data. The results obtained through simulations are compared to the experimental results. The RPiaaS testbed proved to be a very useful tool for the initial experimental validation before moving the experiments to a large‐scale testbed.