Simulating large vCDN networks: A parallel approach

Filelis‐Papadopoulos, Christos K.; Giannoutakis, Konstantinos M.; Gravvanis, George A.; Endo, Patrícia Takako; Tzovaras, Dimitrios; Svorobej, Sergej; Lynn, Theo

doi:10.1016/j.simpat.2019.01.001

Cited by 6 publications

(16 citation statements)

References 8 publications

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“…The results of this simulation are presented in detail in C. K. Filelis-Papadopoulos et al (2019). In summary, we find that parallel performance (status update) is significantly increasing proportionally to the number of requests.…”

Section: Recap Dts Resultsmentioning

confidence: 82%

Simulating Across the Cloud-to-Edge Continuum

Spanopoulos-Karalexidis

Papadopoulos

Giannoutakis

et al. 2020

Palgrave Studies in Digital Business &Amp; Enabling Technologies

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their end users, while maintaining or ideally reducing costs. To do this, testing and service quality assurance are essential. Notwithstanding this, the size and complexity of modern infrastructures make real-time testing and experimentation difficult, time-consuming, and costly. The RECAP Simulation Framework offers cloud and communication service providers an alternative solution while retaining accuracy and verisimilitude. It comprises two simulation approaches, Discrete Event Simulation (DES) and Discrete Time Simulation (DTS). It provides information about optimal virtual cache placements, resource handling and remediation of the system, optimal request servicing, and finally, optimal distribution of requests and resource adjustment, with the goal to increase performance and concurrently decrease power consumption of the system.

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Section: Recap Dts Resultsmentioning

confidence: 82%

Simulating Across the Cloud-to-Edge Continuum

Spanopoulos-Karalexidis

Papadopoulos

Giannoutakis

et al. 2020

Palgrave Studies in Digital Business &Amp; Enabling Technologies

Self Cite

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“…iFogSim is used for evaluation and results compared to the existing (Edgewards) placement policy, which support the efficiency claims of the proposed approach. [66] propose a discrete-time parallel simulation framework, based on the CloudLightning DTS simulator [22] that can handle large vCDN networks. The proposed simulation framework can update, in parallel, the state of sites and their resource utilisation with respect to incoming requests at hyperscale in a significantly faster way that existing cloud simulators.…”

Section: Gupta Et Al (2017)mentioning

confidence: 99%

“…This is not wholly unsurprising given that resource allocation is the central task in resource scheduling. With respect to other resource scheduling tasks, only two papers focus on resource monitoring [35,63] and three others specifically on load balancing [65][66][67]. Five papers focus on resource mapping [41,48,50,58,68] all in relation to cloud computing rather than fog and edge computing.…”

Section: Resource Management Mechanismsmentioning

confidence: 99%

“…This suggests a significant opportunity for research in evaluating resource mapping, resource monitoring and load balancing using simulation, in all layers of the C2T continuum. With regard to resource provisioning, only nine papers [41,[48][49][50]62,[64][65][66]69] specifically addressed both detection and selection tasks; with the exception of [62,69] in fog computing and [66] in edge computing, the remainder of articles focus on the cloud layer.…”

Section: Resource Management Mechanismsmentioning

confidence: 99%

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Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions

et al. 2020

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In recent years, there has been significant advancement in resource management mechanisms for cloud computing infrastructure performance in terms of cost, quality of service (QoS) and energy consumption. The emergence of the Internet of Things has led to the development of infrastructure that extends beyond centralised data centers from the cloud to the edge, the so-called cloud-to-thing continuum (C2T). This infrastructure is characterised by extreme heterogeneity, geographic distribution, and complexity, where the key performance indicators (KPIs) for the traditional model of cloud computing may no longer apply in the same way. Existing resource management mechanisms may not be suitable for such complex environments and therefore require thorough testing, validation and evaluation before even being considered for live system implementation. Similarly, previously discounted resource management proposals may be more relevant and worthy of revisiting. Simulation is a widely used technique in the development and evaluation of resource management mechanisms for cloud computing but is a relatively nascent research area for new C2T computing paradigms such as fog and edge computing. We present a methodical literature analysis of C2T resource management research using simulation software tools to assist researchers in identifying suitable methods, algorithms, and simulation approaches for future research. We analyse 35 research articles from a total collection of 317 journal articles published from January 2009 to March 2019. We present our descriptive and synthetic analysis from a variety of perspectives including resource management, C2T layer, and simulation.

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“…DTS uses the concept of time-step to update the state of the system components, avoiding the need for pre-computation and storage of future events. This approach presents a significant reduction of the simulator's memory requirements and enhances performance while enabling parallel processing [52], and, along with reduced memory requirements, provides a mechanism for the simulation of very large networks. The state of all components involved in a simulation e.g., sites, nodes, VMs, etc, can be updated in parallel, since, there are no dependencies between components thus enhancing scalability.…”

Section: Scalabilitymentioning

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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Simulating large vCDN networks: A parallel approach

Cited by 6 publications

References 8 publications

Simulating Across the Cloud-to-Edge Continuum

Simulating Across the Cloud-to-Edge Continuum

Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions

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

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