Journal Article10.1007/S12083-016-0468-X
Towards an efficient distributed cloud computing architecture
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TL;DR: This work proposes using multi-valued distributed hash tables for efficient resource discovery using Nash equilibrium and shows that Nash equilibrium can be achieved and how the problem of free riders in the distributed cloud can be avoided.
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Abstract: Cloud computing is an emerging field in computer science. Users are utilizing less of their own existing resources, while increasing usage of cloud resources. There are many advantages of distributed computing over centralized architecture. With increase in number of unused storage and computing resources and advantages of distributed computing resulted in distributed cloud computing. In the distributed cloud environment that we propose, resource providers (RP) compete to provide resources to the users. In the distributed cloud all the cloud computing and storage services are offered by distributed resources. In this architecture resources are used and provided by the users in a peer to peer fashion. We propose using multi-valued distributed hash tables for efficient resource discovery. Leveraging the fact that there are many users providing resources such as CPU and memory, we define these resources under one key to easily locate devices with equivalent resources. We have evaluated the performance of resource discovery mechanisms for the distributed cloud and distributed cloud storage and compared the results with existing DHTs, peer to peer clients such as VUZE [1] and explored the feasibility and efficiency of the proposed schemes in terms of resource/service discovery and allocation. We use a simultaneous Auction mechanism and select a set of winners once we receive all contributions or bids. In a real world scenario, users request resources with multiple capabilities, and in order to find such resources we use a contribution mechanism where service providers will provide a contribution price to users for providing a resource. Users use our proposed auction mechanism to select the resources from the set of resource providers. We show that Nash equilibrium can be achieved and how we can avoid the problem of free riders in the distributed cloud.
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Citations
An efficient clustering and load balancing of distributed cloud data centers using graph theory
Abstract: The prime focus of the Cloud Service Providers is enhancing the service delivery performance of the distributed cloud data centers. The clustering and load balancing of distributed cloud data centers have significant impact on its service delivery performance. Hence, this paper models distributed cloud data center environment as a network graph and proposes a two‐phase cluster‐based load balancing (CLB) algorithm based on a graph model. The first phase proposes a Cloud Data Center Clustering algorithm to cluster the distributed cloud data centers based on their proximity. The second phase proposes a Client‐Cluster Assignment algorithm to perform uniform distribution of the client requests across the clusters to enable load balancing. To assess the performance, the proposed algorithms are compared with other K‐constrained graph‐based clustering algorithms namely, graph‐based K‐means and K‐spanning tree algorithms on a simulated distributed cloud data center environment. The experimental results reveal that the proposed CLB algorithm outperforms the compared algorithms in terms of the average clustering time, load distribution, and fairness index and hence improves the service delivery performance of the distributed cloud data centers.
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Enhanced semantic similarity measure based on two‐level retrieval model
TL;DR: A Cloud service discovery crawler that employs a two‐level semantic similarity measure based on both TF‐IDF and LDA models is proposed and a Cloud Service Ontology (CSOnt) that contains a set of concepts defining Cloud service categories is presented.
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EDCrammer: An Efficient Caching Rate-Control Algorithm for Streaming Data on Resource-Limited Edge Nodes
Yunkon Kim,Eui-Nam Huh +1 more
TL;DR: A lightweight, agile caching algorithm, EDCrammer (Efficient Data Crammer), which performs agile operations to control caching rate for streaming data by using the enhanced PID (Proportional-Integral-Differential) controller to help distribute the streaming data traffic to the edge nodes, mitigate the uplink load on the central cloud, and ultimately provide users with high-quality video services.
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Distributed Cloud Computing and Mobile Cloud Computing: A Review
26 Jun 2022
TL;DR: In this paper , the authors provide an overview of cloud computing and mobile cloud computing in terms of delivery and deployment models and the main features of mobile Cloud Computing, which is a relatively new concept in computer science.
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KeyPIn – mitigating the free rider problem in the distributed cloud based on Key, Participation, and Incentive
TL;DR: In this paper , the authors proposed a three-pronged solution KeyPIn, a key-based, participation-based and incentive-based scheme to mitigate the free rider problem in a distributed cloud environment.
References
The NIST Definition of Cloud Computing
Peter Mell,Timothy Grance +1 more
- 28 Sep 2011
TL;DR: This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.
17.6K
•Journal Article
Above the Clouds: A Berkeley View of Cloud Computing
Michael Armbrust,Armando Fox,Rean Griffith,Anthony D. Joseph,Randy H. Katz,Andy Konwinski,Gunho Lee,David A. Patterson,Ariel Rabkin,Ion Stoica,Matei Zaharia +10 more
TL;DR: This work focuses on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SAAS Users, and uses the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.
Xen and the art of virtualization
Paul Barham,Boris Dragovic,Keir Fraser,Steven Hand,Tim Harris,Alex Ho,Rolf Neugebauer,Ian Pratt,Andrew Warfield +8 more
- 19 Oct 2003
TL;DR: Xen, an x86 virtual machine monitor which allows multiple commodity operating systems to share conventional hardware in a safe and resource managed fashion, but without sacrificing either performance or functionality, considerably outperform competing commercial and freely available solutions.
Chord: a scalable peer-to-peer lookup protocol for Internet applications
Ion Stoica,Robert Morris,David Liben-Nowell,David R. Karger,M. Frans Kaashoek,Frank Dabek,Hari Balakrishnan +6 more
TL;DR: Results from theoretical analysis and simulations show that Chord is scalable: Communication cost and the state maintained by each node scale logarithmically with the number of Chord nodes.
Kademlia: A Peer-to-Peer Information System Based on the XOR Metric
Petar Maymounkov,David Mazières +1 more
- 07 Mar 2002
TL;DR: In this paper, the authors describe a peer-to-peer distributed hash table with provable consistency and performance in a fault-prone environment, which routes queries and locates nodes using a novel XOR-based metric topology.