A Preliminary Systematic Review of Computer Science Literature on Cloud Computing Research using Open Source Simulation Platforms

Lynn, Theo; Gourinovitch, Anna; Byrne, James; Byrne, Peter; Svorobej, Sergej; Giannoutakis, Konstantinos M.; Kenny, David J.; Morrison, John P.

doi:10.5220/0006351805650573

Cited by 10 publications

(12 citation statements)

References 5 publications

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“…To this end, a large number of simulators exists which can be used for investigating different aspects of IoT systems. To analyze the distribution and processing of tasks, there are many simulators that focus on aspects of cloud computing [26]. These simulators support, for instance, the design of architectures, virtualization management, or investigations of the system's security.…”

Section: Supported Qualities By Edge Computing Simulatorsmentioning

confidence: 99%

Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics

et al. 2019

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The deployment of Internet of Things (IoT) applications is complex since many quality characteristics should be taken into account, for example, performance, reliability, and security. In this study, we investigate to what extent the current edge computing simulators support the analysis of qualities that are relevant to IoT architects who are designing an IoT system. We first identify the quality characteristics and metrics that can be evaluated through simulation. Then, we study the available simulators in order to assess which of the identified qualities they support. The results show that while several simulation tools for edge computing have been proposed, they focus on a few qualities, such as time behavior and resource utilization. Most of the identified qualities are not considered and we suggest future directions for further investigation to provide appropriate support for IoT architects.

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Section: Supported Qualities By Edge Computing Simulatorsmentioning

confidence: 99%

Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics

et al. 2019

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“…There are many different DES frameworks that have been developed specifically for cloud computing and that provide a range of useful modelling features [13]. For this study we have chosen the CloudSim modelling framework, the most popular cloud computing simulation framework, due to its proven capability in simulating different cloud topologies and application architectures and its appropriateness for the scale envisioned in the use case [14]. CloudSim has two key features relevant to our paper.…”

Section: Background a Discrete Event Simulation: Cloudsimmentioning

confidence: 99%

Modelling and Simulation of ElasticSearch using CloudSim

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Svorobej

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et al. 2019

2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT)

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Simulation can be a powerful technique for evaluating the performance of large-scale cloud computing services in a relatively low cost, low risk and time-sensitive manner. Largescale data indexing, distribution and management is complex to analyse in a timely manner. In this paper, we extend the CloudSim cloud simulation framework to model and simulate a distributed search engine architecture and its workload characteristics. To test the simulation framework, we develop a model based on a real-world ElasticSearch deployment on Linknovate.com. An experimental evaluation of the framework, comparing simulated and actual query response time, precision and resource utilisation, suggests that the proposed framework is capable of predicting performance at different scales in a precise, accurate and efficient manner. The results can assist ElasticSearch users to manage their scalability and infrastructure requirements.

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“…More recently, the use of simulation frameworks [15,16] has come to greater prominence in cloud computing research. Service configuration and resource placement and management strategies can be simulated prior to infrastructure deployment, performance can be optimised, technical and commercial hypotheses tested, and research results validated and reproduced in a low cost, low risk and often time-sensitive manner [10].…”

Section: Introductionmentioning

confidence: 99%

“…While there are several research surveys and articles exploring the challenges of fog computing (e.g., [17,18]), edge computing (e.g., [19,20]), simulation frameworks for cloud computing (e.g., [15,16]) and IoT data analytics (e.g., [21]), there is a paucity of publications addressing the challenges in modelling and simulating fog and edge computing specifically. This paper complements existing works on fog and edge computing by presenting the challenges and design considerations for simulation frameworks of fog and edge infrastructures.…”

Section: Introductionmentioning

confidence: 99%

Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

et al. 2019

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The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous end points located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.

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A Preliminary Systematic Review of Computer Science Literature on Cloud Computing Research using Open Source Simulation Platforms

Cited by 10 publications

References 5 publications

Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics

Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics

Modelling and Simulation of ElasticSearch using CloudSim

Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

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