Study on Distributed Cloud Computing Environment with Composition Model and Graph Model

The conventional centralized cloud has some issues related to timeliness and network congestion. To solve correspondent issues, the conventional cloud is extended in close proximity to a cloud service customer. The researches regarding network edge side are widely studied and still on-going toward the next-generation cloud. Accordingly, this paper illustrates a geographically distributed cloud environment namely the distributed cloud. First, an overview of the distributed cloud is described conceptually and respectfully. Second, composition model and graph model are used to illustrate the distributed cloud. Third, numerical evaluations are performed to verify necessities of the distributed cloud. Lastly, this paper will show possibilities of this research on the conclusion and future works.

[1]  Tom H. Luan,et al.  Fog Computing: Focusing on Mobile Users at the Edge , 2015, ArXiv.

[2]  F. Richard Yu,et al.  Dynamic Operations of Cloud Radio Access Networks (C-RAN) for Mobile Cloud Computing Systems , 2016, IEEE Transactions on Vehicular Technology.

[3]  Shantanu Sharma,et al.  A survey on 5G: The next generation of mobile communication , 2015, Phys. Commun..

[4]  Dazhong Wu,et al.  Democratizing digital design and manufacturing using high performance cloud computing: Performance evaluation and benchmarking , 2017 .

[5]  Albert G. Greenberg,et al.  Measuring and Evaluating TCP Splitting for Cloud Services , 2010, PAM.

[6]  Jiang Zhu,et al.  Fog Computing: A Platform for Internet of Things and Analytics , 2014, Big Data and Internet of Things.

[7]  Wenzhong Li,et al.  Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing , 2015, IEEE/ACM Transactions on Networking.

[8]  Peter Corcoran,et al.  Mobile-Edge Computing and the Internet of Things for Consumers: Extending cloud computing and services to the edge of the network , 2016, IEEE Consumer Electronics Magazine.

[9]  Sonam Srivastava,et al.  A Survey on Latency Reduction Approaches for Performance Optimization in Cloud Computing , 2016, 2016 Second International Conference on Computational Intelligence & Communication Technology (CICT).

[10]  Choong Seon Hong,et al.  An architecture of IPTV service based on PVR-Micro data center and PMIPv6 in cloud computing , 2016, Multimedia Tools and Applications.

[11]  Haibo He,et al.  A Hierarchical Distributed Fog Computing Architecture for Big Data Analysis in Smart Cities , 2015, ASE BD&SI.

[12]  Eui-Nam Huh,et al.  Framework of N-Screen services based on PVR-micro data center and PMIPv6 in cloud computing , 2015, 2015 Seventh International Conference on Ubiquitous and Future Networks.

[13]  Manuel Díaz,et al.  State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing , 2016, J. Netw. Comput. Appl..

[14]  Xuemin Shen,et al.  Peer-to-Peer Networking and Applications , 2007 .

[15]  Peter Kilpatrick,et al.  Challenges and Opportunities in Edge Computing , 2016, 2016 IEEE International Conference on Smart Cloud (SmartCloud).

[16]  Qun Li,et al.  Fog Computing: Platform and Applications , 2015, 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb).

[17]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[18]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

[19]  Teruo Higashino,et al.  Edge-centric Computing: Vision and Challenges , 2015, CCRV.

[20]  Fang Hao,et al.  Application-aware data plane processing in SDN , 2014, HotSDN.

[21]  Jeng-Farn Lee,et al.  FH-PMIPv6: A fast handoff scheme in Proxy Mobile IPv6 networks , 2011, 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet).

[22]  Antti Ylä-Jääski,et al.  Distributed Cloud Infrastructure , 2014 .

[23]  Rajkumar Buyya,et al.  Fog Computing: Principles, Architectures, and Applications , 2016, ArXiv.

[24]  Marco Maier,et al.  Mobile Edge Computing: Challenges for Future Virtual Network Embedding Algorithms , 2014 .

[25]  Hai Zhao,et al.  An Efficient PMIPv6-Based Handoff Scheme for Urban Vehicular Networks , 2016, IEEE Transactions on Intelligent Transportation Systems.

[26]  Johnson P. Thomas,et al.  Towards an efficient distributed cloud computing architecture , 2017, Peer Peer Netw. Appl..