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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 劉邦鋒 | |
| dc.contributor.author | Ming-Jing Lin | en |
| dc.contributor.author | 林明璟 | zh_TW |
| dc.date.accessioned | 2021-06-08T02:38:55Z | - |
| dc.date.copyright | 2018-07-19 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-07-10 | |
| dc.identifier.citation | [1] Aws auto scaling. https://aws.amazon.com/autoscaling/. Accessed: 2018-05-02.
[2] List of the most popular social vr platforms. https://www.vrandfun.com/popular-social-vr-platform-list/. Accessed: 2018-04-22. [3] Microsoft azure. https://azure.microsoft.com/en-us/features/autoscale/. Accessed: 2018-05-02. [4] Vrchat. https://www.vrchat.net/. Accessed: 2018-04-22. [5] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia. A view of cloud computing. Commun. ACM, 53(4):50–58, Apr. 2010. [6] A. Bar-Noy, I. Kessler, and M. Sidi. Mobile users: To update or not to update? Wireless Networks, 1(2):175–185, Jun 1995. [7] S. Basagni, I. Chlamtac, V. R. Syrotiuk, and B. A. Woodward. A distance routing effect algorithm for mobility (dream). In Proceedings of the 4th Annual ACM/IEEE International Conference on Mobile Computing and Networking, MobiCom ’98, pages 76–84, New York, NY, USA, 1998. ACM. [8] T. Camp, J. Boleng, and V. Davies. A survey of mobility models for ad hoc network research. 2, 08 2002. [9] J. S. Chase, D. C. Anderson, P. N. Thakar, A. M. Vahdat, and R. P. Doyle. Managing energy and server resources in hosting centers. In Proceedings of the Eighteenth ACM Symposium on Operating Systems Principles, SOSP ’01, pages 103–116, New York, NY, USA, 2001. ACM. [10] Y. L. Cheng, C. C. Lin, P. Liu, and J. J. Wu. High resource utilization auto-scaling algorithms for heterogeneous container configurations. In 2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS), pages 143–150, Dec 2017. [11] H. T. Dinh, C. Lee, D. Niyato, and P. Wang. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing, 13(18):1587–1611. [12] C. Gao, H. Wang, L. Zhai, Y. Gao, and S. Yi. An energy-aware ant colony algorithm for network-aware virtual machine placement in cloud computing. In 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS), pages 669–676, Dec 2016. [13] J. J. Garcia-Luna-Aceves and E. L. Madruga. A multicast routing protocol for adhoc networks. In INFOCOM ’99. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, volume 2, pages 784–792 vol.2, Mar 1999. [14] J. Jiang, J. Lu, G. Zhang, and G. Long. Optimal cloud resource auto-scaling for web applications. In 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, pages 58–65, May 2013. [15] X. Li, J. Wu, S. Tang, and S. Lu. Let’s stay together: Towards traffic aware virtual machine placement in data centers. In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, pages 1842–1850, April 2014. [16] C.-C. Lin, J.-J. Wu, P. Liu, J.-A. Lin, and L.-C. Song. Automatic resource scaling for web applications in the cloud. In J. J. J. H. Park, H. R. Arabnia, C. Kim, W. Shi, and J.-M. Gil, editors, Grid and Pervasive Computing, pages 81–90, Berlin, Heidelberg, 2013. Springer Berlin Heidelberg. [17] D. Meiländer, A. Ploss, F. Glinka, and S. Gorlatch. A dynamic resource management system for real-time online applications on clouds. In M. Alexander, P. D’Ambra, A. Belloum, G. Bosilca, M. Cannataro, M. Danelutto, B. Di Martino, M. Gerndt, E. Jeannot, R. Namyst, J. Roman, S. L. Scott, J. L. Traff, G. Vallée, and J. Wei-dendorfer, editors, Euro-Par 2011: Parallel Processing Workshops, pages 149–158, Berlin, Heidelberg, 2012. Springer Berlin Heidelberg. [18] X. Meng, V. Pappas, and L. Zhang. Improving the scalability of data center networks with traffic-aware virtual machine placement. In Proceedings of the 29th Conference on Information Communications, INFOCOM’10, pages 1154–1162, Piscataway, NJ, USA, 2010. IEEE Press. [19] I. Rubin and C. W. Choi. Impact of the location area structure on the performance of signaling channels in wireless cellular networks. IEEE Communications Magazine, 35(2):108–115, Feb 1997. [20] M. A. Rupp, J. Kozachuk, J. R. Michaelis, K. L. Odette, J. A. Smither, and D. S. McConnell. The effects of immersiveness and future vr expectations on subjec-tive- experiences during an educational 360° video. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 60(1):2108–2112, 2016. [21] C. Tang, M. Steinder, M. Spreitzer, and G. Pacifici. A scalable application placement controller for enterprise data centers. In Proceedings of the 16th International Conference on World Wide Web, WWW ’07, pages 331–340, New York, NY, USA, 2007. ACM. [22] S. Wang and S. Dey. Rendering adaptation to address communication and computation constraints in cloud mobile gaming. In 2010 IEEE Global Telecommunications Conference GLOBECOM 2010, pages 1–6, Dec 2010. [23] M. M. Zonoozi and P. Dassanayake. User mobility modeling and characterization of mobility patterns. IEEE Journal on Selected Areas in Communications, 15(7):1239–1252, Sep 1997. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/20024 | - |
| dc.description.abstract | In this paper we present a bandwidth management framework that determines a proper bandwidth for each instance in order to get higher user experience, then dynamically allocate bandwidth based on network requirement of each instance. We propose a way to quantify user experience, and propose a dynamic programming method to find optimal allocation so as to maximize the total quantified users experience. We also propose a greedy method that can determine proper bandwidth for each instance according to near future demand prediction. Our experiment confirms that the greedy method is both effective and efficient. We also confirm that our bandwidth requirement prediction method is effective. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T02:38:55Z (GMT). No. of bitstreams: 1 ntu-107-R05922114-1.pdf: 862173 bytes, checksum: 062dac1a98cca661e1fe1bfdda3388fd (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 誌謝 ii
摘要 iii Abstract iv 1 Introduction 1 2 Related Work 4 2.1 Resource Allocation by Virtual Machine Placement . . . . . . . . . . . . 4 2.2 Dynamic Resource Allocation by Auto Scaling . . . . . . . . . . . . . . 5 2.3 Dynamic Resource Allocation at the Application Level . . . . . . . . . . 5 3 Problem Definition 7 3.1 Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2 Quantify the User Experience . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.3.1 NP Completeness . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.4 Dynamic Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.4.1 Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.5 Greedy Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 System Architecture 14 4.1 Master . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.2 Scheduler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4.3 Slave Manager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 5 Experiments 16 5.1 Random Walk Mobility Model . . . . . . . . . . . . . . . . . . . . . . . 16 5.2 Prediction Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 5.3 Greedy Method Performance . . . . . . . . . . . . . . . . . . . . . . . . 18 5.4 Overloading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 5.5 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 6 Conclusion 23 Bibliography 24 | |
| dc.language.iso | en | |
| dc.title | 伺服器中對於行動裝置社交型虛擬實境應用的動態頻寬分配 | zh_TW |
| dc.title | Local and Dynamic Bandwidth Allocation for
Mobile Social VR Applications on a Server | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 徐慰中,吳真貞 | |
| dc.subject.keyword | 行動雲端計算,社交型虛擬實境應用,網路頻頸,動態頻寬分配, | zh_TW |
| dc.subject.keyword | Mobile Cloud Computing,SocialVR Application,Network Bottleneck,Dynamic Bandwidth Allocation, | en |
| dc.relation.page | 26 | |
| dc.identifier.doi | 10.6342/NTU201801404 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2018-07-11 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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