Optimizing Multi-Cloud CDN Deployment and Scheduling Strategies Using Big Data Analysis

Wang, Congjie; Lu, Zhihui; Wu, Ziyan; Wu, Jie; Huang, Shalin

doi:10.1109/scc.2017.42

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…By analyzing the big data of content distribution network (CDN) operation, Wang et al [101] adopted the long-term resource deployment algorithm to satisfy the needs of users with the lowest resources and proposed a resource allocation and scheduling optimization strategy supported by the multi-cloud architecture. At the same time, the multi-cloud scaling algorithm can further schedule cloud resources from other cloud providers to address the overload problem of the cloud system.…”

Section: Independent Task Scheduling Methodsmentioning

confidence: 99%

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Zhang¹,

Geng²,

Cai³

2023

Computer Modeling in Engineering &Amp; Sciences

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Cloud computing technology is favored by users because of its strong computing power and convenient services. At the same time, scheduling performance has an extremely efficient impact on promoting carbon neutrality. Currently, scheduling research in the multi-cloud environment aims to address the challenges brought by business demands to cloud data centers during peak hours. Therefore, the scheduling problem has promising application prospects under the multi-cloud environment. This paper points out that the currently studied scheduling problems in the multi-cloud environment mainly include independent task scheduling and workflow task scheduling based on the dependencies between tasks. This paper reviews the concepts, types, objectives, advantages, challenges, and research status of task scheduling in the multi-cloud environment. Task scheduling strategies proposed in the existing related references are analyzed, discussed, and summarized, including research motivation, optimization algorithm, and related objectives. Finally, the research status of the two kinds of task scheduling is compared, and several future important research directions of multi-cloud task scheduling are proposed.

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Section: Independent Task Scheduling Methodsmentioning

confidence: 99%

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Zhang¹,

Geng²,

Cai³

2023

Computer Modeling in Engineering &Amp; Sciences

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“…The Genetic Algorithm is better suited for scheduling. The proposed algorithm in this survey paper is used to mapping independent task to virtual machine of multicloud such that each task is executed having minimum makespan time, completion time, and response time respectively [3]. One of the primary objectives of the scheduler is the utilization of CPU to facilitate the process of the completion and response time, waiting and turnaround time, priority and system throughput.…”

Section: Proposed Methodologymentioning

confidence: 99%

“…The main components in cloud computing are users, resource providers, and task/job scheduling which contains the user request and scheduling strategy. The concept of scheduling means the particular amount of time a resource is assign to the task or job [3]. The various scheduling algorithm are available which is responsible for assign the resources to the requested task in a multicloud environment based on quality of services.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Study on Task Scheduling Strategies in Multicloud Environment

Patil¹,

Gade²,

Rewatkar³

2019

JESA

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The task scheduling in multicloud computing environment is complicated task. The cloud computing has increase tremendous popularity both in academia and business because of its on demand service over internet to the various customer. The task scheduling problem is N-P (Non deterministic polynomial) completeness problem. Task scheduling in cloud computing is a best-known problem that has been paid attention. This is again more challenging, specially for multicloud computing environment. This survey paper presents the Shortest Job First algorithm, Round Robin algorithm and Genetic Algorithm for task scheduling in multicloud computing. The round robin algorithm provides the fair allocation and square allocation of resource to the task. It provides the accurate result in finding solutions to large scale optimization problems, by Genetic algorithms such as task scheduling and it is also helpful. A good task and resource scheduling mechanism must satisfy the QoS requirement of the user and at the same time make an efficient utilization of resources. This survey paper presents an algorithm which tries to achieve application high availability, and minimum makespan, minimum response time and completion time.

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“…Balachandran et al [20] observe several user access patterns, regional interests and how such information have important implications to two trending CDN architectures (designs): federated telco-CDNs and hybrid P2P-CDNs, using the dataset from two large Internet video providers. Wang et al [21] exploits the use of Spark to largely analyze CDN log files to help content distributors make better decisions in how to improve QoS with minimum cost by utilizing multi-cloud CDN to serve users. Specifically, the authors present a multi-cloud architecture optimized for resource allocation and scheduling through big data analysis.…”

Section: ) Overall Performancementioning

confidence: 99%

A use case of Content Delivery Network raw log file analysis

Tran

et al. 2020

2020 International Conference on Advanced Computing and Applications (ACOMP)

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The growth of video streaming has stretched the Internet to its limitation. In other words, the Internet was originally devised to connect a limited number of computers so that they can share network resources, so the Internet cannot handle a large amount of traffic at a time, which leads to network congestion. To overcome this, CDNs are built on top of the Internet as an overlay to efficiently store and swiftly disseminate contents to users by placing many servers and data centers around the globe. The topic of CDNs has been extensively studied in the last several decades. However, there is still a certain gap between theories in academia and current technologies in industry. In this paper, we take a close look at the design, implementation, solution, and performance of a CDN system by analyzing its raw log files. Specifically, its infrastructure and system design are first presented, and then we conduct a tracebased study to understand user access patterns, the sources of requests, system performance, and how such information can be used to improve the whole CDN system.

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Optimizing Multi-Cloud CDN Deployment and Scheduling Strategies Using Big Data Analysis

Cited by 10 publications

References 12 publications

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Survey on Task Scheduling Optimization Strategy under Multi-Cloud Environment

Comprehensive Study on Task Scheduling Strategies in Multicloud Environment

A use case of Content Delivery Network raw log file analysis

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