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Smart community edge platform providing stream content analysis, service migration, and service chaining (本文)

Wickramaarachchi A., Shanaka P. Abeysiriwardhana 慶應義塾大学

2021.03.23

概要

A smart community utilizes information technology to interconnect and manage community infrastructures. These networks consist of many Internet of Things(IoT) devices that provide different services to the end-users. In conventional networks, these sensor data send to cloud services for processing and management. However, cloud-based data processing introduces latency to the services. Fog computing techniques have been introduced to support these services at the network edge reducing the network latency. Smart community networks should support latency-sensitive services such as smart grid systems at the edge. In addition, Smart community services require service migration and service chaining to manage and distribute multiple services. For example, the current smart community edge(SCE) supports smart energy management services where data anonymization and data aggregation services should be chained, and the services should be migrated depending on the network’s location and network traffic.

SCE services can leverage generic hardware devices and network virtualization technologies to deploy the services without proprietary middleware devices. The current network virtualization methods mainly consider only core network applications. In contrast, smart community services operate on application layer data and process in-transit data to capture sensor data at the edge. Therefore, data extraction edge nodes that support sensor data processing are required to support these smart community services. A service-oriented container-based solution that processes data streams from sensors using conventional hardware will improve the applicability, compatibility, and latency of smart community services.

To this end, a software-based edge node, namely, the SCE platform, was proposed to support smart community services. SCE supports data-tapping applications, especially for IoT devices, and has a stream processing feature with a comparatively shorter processing delay. This tapping and processing function on in-transit data was named stream content analysis(SCA). SCA captures in-transit data through zero copy stream reconstruction and string matching process. Afterward, SCE proposes a distributed rule application method to manage multiple services and distribute matched data to the services. SCE supports services through Docker containers to provide remote deployment, service migration, and service isolation. The real world SCE platform implementation allows SCE services to operate on 10Gbps links and apply 100 accumulated rules while maintaining less than 1ms latency using commodity hardware devices.

To support SCE service migration, SCE proposes a consistently guaranteed migration method to support service migration to distribute the services depending on the nodes’ availability. The proposed migration technique is designed to guarantee network consistency while migrating between nodes.

Compared to existing container migration methods, the proposed migration reduces the migration data transfer through container layers and migrating only the streams affected by the migration application through SCA. The proposed container migration methods reduced the network downtime by more than 10% compared to conventional methods for containers with image sizes larger than 400MBs. Furthermore, SCE services require chaining to distribute sensor data efficiently to the edge nodes to apply multiple network services for a given traffic flow. To this end, SCE introduces a service function chaining-based request distribution method that utilizes proactive data collection and heuristics to analyze the network traffic and to select optimal SCE nodes. The SCE request distribution method reduces the end-to-end service latency by 10% compared to the available algorithms. The SCE platform provides commodity hardware-based SCA, distributed rule change application, service migration, and service chaining to support SCE services.

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参考文献

[1] “History of ICT - CS1105 Group Reports 2008 - Wiki.nus.” https://wiki.nus.edu.sg/display/cs1105groupreports/History+of+ICT (accessed Nov. 18, 2020).

[2] “A Brief History of the Internet.” https://www.usg.edu/galileo/skills/unit07/internet07_02.phtml (accessed Nov. 18, 2020).

[3] “Who Coined 'Cloud Computing'?,” MIT Technology Review. https://www.technologyreview.com/2011/10/31/257406/who-coined-cloud-computing/ (accessed Nov. 18, 2020).

[4] “What is REST - REST API Tutorial.” https://restfulapi.net/ (accessed Nov. 18, 2020).

[5] “ETSI - Standards for NFV - Network Functions Virtualisation | NFV Solutions.” https://www.etsi.org/technologies/nfv (accessed Nov. 18, 2020).

[6] “Number of IoT devices 2015-2025,” Statista. https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/ (accessed Nov. 18, 2020).

[7] gk, “Open Fog Computing and Mobile Edge Cloud Gain Momentum | Y.I Readings.” http://yucianga.info/?p=938 (accessed Jul. 07, 2017).

[8] “Home - JSCA Japan Smart Community Alliance.” https://www.smart- japan.org/english/ (accessed Nov. 18, 2020).

[9] “OSA | PON Roadmap [Invited].” https://www.osapublishing.org/jocn/abstract.cfm?URI=jocn-9-1-a71 (accessed Jul. 18, 2019).

[10] K. Tanaka, A. Agata, and Y. Horiuchi, “IEEE 802.3av 10G-EPON Standardization and Its Research and Development Status,” J. Light. Technol., vol. 28, no. 4, pp. 651–661, Feb. 2010, doi: 10.1109/JLT.2009.2038722.

[11] S. Gallenmüller, P. Emmerich, R. Schönberger, D. Raumer, and G. Carle, “Building Fast but Flexible Software Routers,” in Proceedings of the Symposium on Architectures for Networking and Communications Systems, Piscataway, NJ, USA, 2017, pp. 101–102, doi: 10.1109/ANCS.2017.21.

[12] Y. Ohara, Y. Yamagishi, S. Sakai, A. D. Banik, and S. Miyakawa, “Revealing the Necessary Conditions to Achieve 80Gbps High-Speed PC Router,” in Proceedings of the Asian Internet Engineering Conference, New York, NY, USA, 2015, pp. 25–31, doi: 10.1145/2837030.2837034.

[13] J. Kim, S. Huh, K. Jang, K. Park, and S. Moon, “The Power of Batching in the Click Modular Router,” in Proceedings of the Asia-Pacific Workshop on Systems, New York, NY, USA, 2012, p. 14:1-14:6, doi: 10.1145/2349896.2349910.

[14] L. Rizzo, L. Deri, and A. Cardigliano, “10 Gbit/s Line Rate Packet Processing Using Commodity Hardware: Survey and new Proposals,” p. 8.

[15] “netmap: A Novel Framework for Fast Packet I/O | USENIX.” https://www.usenix.org/node/168897 (accessed Feb. 27, 2018).

[16] S. Higginbotham, “In a distributed world cache is king. Why routers are becoming the new server.,” Jan. 31, 2014. https://gigaom.com/2014/01/31/in-a-distributed-world-cache-is-king-why-routers-are-becoming-the-new-server/ (accessed Jul. 07, 2017).

[17] A. Panda, S. Han, K. Jang, M. Walls, S. Ratnasamy, and S. Shenker, “NetBricks: Taking the V out of NFV,” in Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation, Berkeley, CA, USA, 2016, pp. 203– 216, Accessed: Apr. 04, 2017. [Online]. Available: http://dl.acm.org/citation.cfm?id=3026877.3026894.

[18] J. Soares, M. Dias, J. Carapinha, B. Parreira, and S. Sargento, “Cloud4NFV: A platform for Virtual Network Functions,” in 2014 IEEE 3rd International Conference on Cloud Networking (CloudNet), Oct. 2014, pp. 288–293, doi: 10.1109/CloudNet.2014.6969010.

[19] G. A. Gibson and R. Van Meter, “Network attached storage architecture,” Commun. ACM, vol. 43, no. 11, pp. 37–45, 2000.

[20] S. Nadgowda, S. Suneja, N. Bila, and C. Isci, “Voyager: Complete Container State Migration,” in 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Jun. 2017, pp. 2137–2142, doi: 10.1109/ICDCS.2017.91.

[21] M. R. Islam, M. M. S. Pahalovim, T. Adhikary, M. A. Razzaque, M. M. Hassan, and A. Alsanad, “Optimal Execution of Virtualized Network Functions for Applications in Cyber-Physical-Social-Systems,” IEEE Access, vol. 6, pp. 8755– 8767, 2018, doi: 10.1109/ACCESS.2018.2805890.

[22] G. P. Hancke, B. de Carvalho e Silva, and G. P. Hancke, “The Role of Advanced Sensing in Smart Cities,” Sensors, vol. 13, no. 1, pp. 393–425, Dec. 2012, doi: 10.3390/s130100393.

[23] Smart Communities Guidebook: Building Smart Communities, how California’s Communities Can Thrive in the Digital Age. International Center for Communications, College of Professional Studies and Fine Arts, San Diego State University, 1997.

[24] X. Li, R. Lu, X. Liang, X. Shen, J. Chen, and X. Lin, “Smart community: an internet of things application,” IEEE Commun. Mag., vol. 49, no. 11, pp. 68–75, Nov. 2011, doi: 10.1109/MCOM.2011.6069711.

[25] J. Bryzek, “Trillion sensors: Foundation for abundance, exponential organizations, Internet of Everything and mHealth,” Sens. Mag., 2014.

[26] J. Biswas et al., “Processing of wearable sensor data on the cloud - a step towards scaling of continuous monitoring of health and well-being,” in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Aug. 2010, pp. 3860–3863, doi: 10.1109/IEMBS.2010.5627906.

[27] C. Ji, Y. Li, W. Qiu, U. Awada, and K. Li, “Big Data Processing in Cloud Computing Environments,” in 2012 12th International Symposium on Pervasive Systems, Algorithms and Networks, Dec. 2012, pp. 17–23, doi: 10.1109/I- SPAN.2012.9.

[28] R. Hummen, M. Henze, D. Catrein, and K. Wehrle, “A Cloud design for user- controlled storage and processing of sensor data,” in 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings, Dec. 2012, pp. 232–240, doi: 10.1109/CloudCom.2012.6427523.

[29] H. Nishi, “Information and communication platform for providing smart community services: System implementation and use case in Saitama city,” in 2018 IEEE International Conference on Industrial Technology (ICIT), Feb. 2018, pp. 1375– 1380, doi: 10.1109/ICIT.2018.8352380.

[30] M. A. Lema et al., “Business Case and Technology Analysis for 5G Low Latency Applications,” IEEE Access, vol. 5, pp. 5917–5935, 2017, doi: 10.1109/ACCESS.2017.2685687.

[31] “OpenFog Consortium.” https://www.openfogconsortium.org/#fog-computing (accessed Jul. 27, 2017).

[32] F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, “Fog Computing and Its Role in the Internet of Things,” in Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, New York, NY, USA, 2012, pp. 13–16, doi: 10.1145/2342509.2342513.

[33] F. Bonomi, R. Milito, P. Natarajan, and J. Zhu, “Fog Computing: A Platform for Internet of Things and Analytics,” in Big Data and Internet of Things: A Roadmap for Smart Environments, Springer, Cham, 2014, pp. 169–186.

[34] S. Yi, C. Li, and Q. Li, “A Survey of Fog Computing: Concepts, Applications and Issues,” in Proceedings of the 2015 Workshop on Mobile Big Data, New York, NY, USA, 2015, pp. 37–42, doi: 10.1145/2757384.2757397.

[35] J. Wijekoon, E. Harahap, and H. Nishi, “Service-oriented Router Simulation Module Implementation in NS2 Simulator,” Procedia Comput. Sci., vol. 19, pp. 478–485, Jan. 2013, doi: 10.1016/j.procs.2013.06.064.

[36] J.-S. Sung, S.-M. Kang, Y. Lee, T.-G. Kwon, and B.-T. Kim, “A multi-gigabit rate deep packet inspection algorithm using TCAM,” in GLOBECOM ’05. IEEE Global Telecommunications Conference, 2005., Dec. 2005, vol. 1, p. 5 pp.-, doi: 10.1109/GLOCOM.2005.1577667.

[37] “NFV – Network Functions Virtualization,” Cisco. http://www.cisco.com/c/en/us/solutions/service-provider/network-functions- virtualization-nfv/index.html (accessed Jul. 07, 2017).

[38] “U.S. vs. Japan: Residential Internet Service Provision Pricing,” New America. https://www.newamerica.org/oti/policy-papers/us-vs-japan-residential-internet- service-provision-pricing/ (accessed Apr. 03, 2018).

[39] L. Deri, M. Martinelli, T. Bujlow, and A. Cardigliano, “nDPI: Open-source high- speed deep packet inspection,” in 2014 International Wireless Communications and Mobile Computing Conference (IWCMC), Aug. 2014, pp. 617–622, doi: 10.1109/IWCMC.2014.6906427.

[40] “Wireshark · Go Deep.” https://www.wireshark.org/ (accessed Jul. 07, 2017).

[41] K. Ikeuchi, J. Wijekoon, S. Ishida, and H. Nishi, “GPU-based multi-stream analyzer on application layer for service-oriented router,” presented at the 2013 IEEE 7th International Symposium on Embedded Multicore/Manycore System-on- Chip, MCSoC 2013, 2013, doi: 10.1109/MCSoC.2013.34.

[42] “DPDK.” https://dpdk.org/ (accessed Apr. 25, 2018).

[43] Red Hat, Inc, “about DPDK.” http://dpdk.org/about (accessed Jul. 07, 2017).

[44] “Introducing PF_RING ZC (Zero Copy),” ntop, Apr. 14, 2014. https://www.ntop.org/pf_ring/introducing-pf_ring-zc-zero-copy/ (accessed Feb. 27, 2018).

[45] L. Rizzo and G. Lettieri, “VALE, a switched ethernet for virtual machines,” in Proceedings of the 8th international conference on Emerging networking experiments and technologies, Nice, France, Dec. 2012, pp. 61–72, doi: 10.1145/2413176.2413185.

[46] S. Gallenmüller, P. Emmerich, F. Wohlfart, D. Raumer, and G. Carle, “Comparison of Frameworks for High-Performance Packet IO,” in Proceedings of the Eleventh ACM/IEEE Symposium on Architectures for Networking and Communications Systems, Washington, DC, USA, 2015, pp. 29–38, Accessed: Feb. 27, 2018. [Online]. Available: http://dl.acm.org/citation.cfmid=2772722.2772729.

[47] “PF_RING,” ntop, Aug. 04, 2011. https://www.ntop.org/products/packet-capture/pf_ring/ (accessed Apr. 25, 2018).

[48] T. Konstantina, Betreuer, W. Florian, and R. Daniel G, “A Survey of Trends in Fast Packet Processing,” in Proceedings of the Seminars Future Internet (FI) and Innovative Internet Technologies and Mobile Communications (IITM), 2014, pp. 41–48.

[49] D. Luca, “DPDK Summit North America 2018: Using nDPI over DPDK to Classify and Block Unwanted Traffic.” https://dpdksummitnorthamerica2018.sched.com/event/IhhK/using-ndpi-over-dpdk-to- classify-and-block-unwanted-network-traffic-luca-deri-ntop (accessed May 30, 2019).

[50] “DPDK PRC Summit 2018: Multiple vDPI Functions using DPDK and H...” https://dpdkprcsummit2018.sched.com/event/EsPY/multiple-vdpi-functions-using- dpdk-and-hyperscan-on-ovs-dpdk-platform (accessed May 30, 2019).

[51] “The Design and Implementation of Open vSwitch | USENIX.” https://www.usenix.org/node/188961 (accessed Feb. 27, 2018).

[52] B. Han, V. Gopalakrishnan, L. Ji, and S. Lee, “Network function virtualization: Challenges and opportunities for innovations,” IEEE Commun. Mag., vol. 53, no. 2, pp. 90–97, Feb. 2015, doi: 10.1109/MCOM.2015.7045396.

[53] F. Callegati, W. Cerroni, C. Contoli, R. Cardone, M. Nocentini, and A. Manzalini, “SDN for dynamic NFV deployment,” IEEE Commun. Mag., vol. 54, no. 10, pp. 89–95, Oct. 2016, doi: 10.1109/MCOM.2016.7588275.

[54] “Enterprise Network Functions Virtualization (NFV),” Cisco. https://www.cisco.com/c/en/us/solutions/enterprise-networks/enterprise-network- functions-virtualization-nfv/index.html (accessed Apr. 25, 2018).

[55] “NFV (Network Functions Virtualization) Solution - Juniper Networks.” https://www.juniper.net/us/en/solutions/nfv/ (accessed Apr. 25, 2018).

[56] Y. Dong, X. Yang, J. Li, G. Liao, K. Tian, and H. Guan, “High performance network virtualization with SR-IOV,” J. Parallel Distrib. Comput., vol. 72, no. 11, pp. 1471–1480, Nov. 2012, doi: 10.1016/j.jpdc.2012.01.020.

[57] R. Mijumbi, J. Serrat, J. L. Gorricho, N. Bouten, F. D. Turck, and R. Boutaba, “Network Function Virtualization: State-of-the-Art and Research Challenges,” IEEE Commun. Surv. Tutor., vol. 18, no. 1, pp. 236–262, Firstquarter 2016, doi: 10.1109/COMST.2015.2477041.

[58] F-stack, “F-Stack | High Performance Network Framework Based On DPDK.” http://www.f-stack.org/ (accessed Jan. 21, 2019).

[59] L. Rizzo, M. Carbone, and G. Catalli, “Transparent acceleration of software packet forwarding using netmap,” in 2012 Proceedings IEEE INFOCOM, Mar. 2012, pp. 2471–2479, doi: 10.1109/INFCOM.2012.6195638.

[60] N. ISG, “Network Functions Virtualisation (NFV)-Network Operator Perspectives on Industry Progress,”,” ETSI Tech, 2013.

[61] S. Sreekanth, “VMware vSphere 5.1 vMotion Architecture, Performance and Best Practices,” White Pap. VMware Inc Palo Alto CA USA, 2012.

[62] V. Medina and J. M. García, “A Survey of Migration Mechanisms of Virtual Machines,” ACM Comput Surv, vol. 46, no. 3, p. 30:1-30:33, Jan. 2014, doi: 10.1145/2492705.

[63] F. Romero and T. J. Hacker, “Live Migration of Parallel Applications with OpenVZ,” in 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications, Mar. 2011, pp. 526–531, doi: 10.1109/WAINA.2011.156.

[64] D. Bernstein, “Containers and Cloud: From LXC to Docker to Kubernetes,” IEEE Cloud Comput., vol. 1, no. 3, pp. 81–84, Sep. 2014, doi: 10.1109/MCC.2014.51.

[65] opencontainers, opencontainers/runc. Open Container Initiative, 2019.

[66] S. Pickartz, N. Eiling, S. Lankes, L. Razik, and A. Monti, “Migrating LinuX Containers Using CRIU,” in High Performance Computing, 2016, pp. 674–684.

[67] C. Dupont, R. Giaffreda, and L. Capra, “Edge computing in IoT context: Horizontal and vertical Linux container migration,” in 2017 Global Internet of Things Summit (GIoTS), Jun. 2017, pp. 1–4, doi: 10.1109/GIOTS.2017.8016218.

[68] “What is Docker,” Docker, May 14, 2015. https://www.docker.com/what-docker (accessed Apr. 07, 2017).

[69] The Kubernetes Authors, “Production-Grade Container Orchestration,” Sep. 19, 2019. https://kubernetes.io/ (accessed Sep. 19, 2019).

[70] L. Ma, S. Yi, and Q. Li, “Efficient Service Handoff Across Edge Servers via Docker Container Migration,” in Proceedings of the Second ACM/IEEE Symposium on Edge Computing, New York, NY, USA, 2017, p. 11:1-11:13, doi: 10.1145/3132211.3134460.

[71] A. Machen, S. Wang, K. K. Leung, B. J. Ko, and T. Salonidis, “Live Service Migration in Mobile Edge Clouds,” IEEE Wirel. Commun., vol. 25, no. 1, pp. 140– 147, Feb. 2018, doi: 10.1109/MWC.2017.1700011.

[72] A. Gember-Jacobson et al., “OpenNF: Enabling Innovation in Network Function Control,” in Proceedings of the 2014 ACM Conference on SIGCOMM, New York, NY, USA, 2014, pp. 163–174, doi: 10.1145/2619239.2626313.

[73] M. Peuster, H. Küttner, and H. Karl, “Let the state follow its flows: An SDN- based flow handover protocol to support state migration,” in 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft), Jun. 2018, pp. 97– 104, doi: 10.1109/NETSOFT.2018.8460007.

[74] L. Nobach, I. Rimac, V. Hilt, and D. Hausheer, “SliM: Enabling efficient, seamless NFV state migration,” in 2016 IEEE 24th International Conference on Network Protocols (ICNP), Nov. 2016, pp. 1–2, doi: 10.1109/ICNP.2016.7784459.

[75] J. Halpern and C. Pignataro, “Service function chaining (sfc) architecture,” 2015.

[76] J. Medved, R. Varga, A. Tkacik, and K. Gray, “OpenDaylight: Towards a Model- Driven SDN Controller architecture,” in 2014 IEEE 15th International Symposium on “A World of Wireless, Mobile and Multimedia Networks” (WoWMoM)(WOWMOM), Jun. 2014, pp. 1–6, doi: 10.1109/WoWMoM.2014.6918985.

[77] A. M. Medhat, G. Carella, C. Lück, M. I. Corici, and T. Magedanz, “Near optimal service function path instantiation in a multi-datacenter environment,” in 2015 11th International Conference on Network and Service Management (CNSM), Nov. 2015, pp. 336–341, doi: 10.1109/CNSM.2015.7367379.

[78] M. M. S. Pahalovi, M. R. Islam, T. Adhikary, and M. A. Razzaque, “Optimal execution of virtualized network functions in a multi-data-center cloud,” in 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), Dec. 2017, pp. 602–605, doi: 10.1109/R10-HTC.2017.8289032.

[79] R. Fielding et al., “Hypertext Transfer Protocol -- HTTP/1.1,” 1999, Accessed: Jul. 07, 2017. [Online]. Available: http://www.rfc-editor.org/info/rfc2616.

[80] “Manpage of PCAP.” http://www.tcpdump.org/manpages/pcap.3pcap.html (accessed Jul. 07, 2017).

[81] “Boyer-Moore algorithm.” http://www-igm.univ-mlv.fr/~lecroq/string/node14.html (accessed Jul. 27, 2017).

[82] “MySQL :: MySQL Community Edition.” https://www.mysql.com/products/community/ (accessed Jul. 07, 2017).

[83] “POSIX Threads Programming.” https://computing.llnl.gov/tutorials/pthreads/ (accessed Jul. 07, 2017).

[84] INTEL CORPORATION, “Hyperscan,” 01.org, Sep. 17, 2015. https://01.org/hyperscan (accessed Jul. 07, 2017).

[85] “Regex Set Scanning with Hyperscan and RE2::Set,” 01.org, Jun. 20, 2017. https://01.org/hyperscan/blogs/jpviiret/2017/regex-set-scanning-hyperscan-and- re2set (accessed Apr. 25, 2018).

[86] “IEEE 1888-2014 - IEEE Standard for Ubiquitous Green Community Control Network Protocol.” https://standards.ieee.org/standard/1888-2014.html (accessed Jul. 18, 2019).

[87] C. McParland, “OpenADR open source toolkit: Developing open source software for the Smart Grid,” in 2011 IEEE Power and Energy Society General Meeting, Jul. 2011, pp. 1–7, doi: 10.1109/PES.2011.6039816.

[88] “What is Docker,” Docker, May 14, 2015. https://www.docker.com/what-docker (accessed Apr. 07, 2017).

[89] Intel technologies, “Accelerating Snort* IPS Throughput Performance Using Hyperscan Pattern-Matching Software.” Intel technologies, 2017, Accessed: Jul. 27, 2017. [Online]. Available: https://www.intel.com/content/dam/www/public/us/en/documents/solution- briefs/hyperscan-scalability-solution-brief.pdf.

[90] “Containers vs VMs: Which is better for Cloud Deployments?,” SDxCentral. https://www.sdxcentral.com/cloud/containers/definitions/containers-vs-vms/ (accessed Sep. 28, 2017).

[91] C. Puliafito, C. Vallati, E. Mingozzi, G. Merlino, F. Longo, and A. Puliafito, “Container Migration in the Fog: A Performance Evaluation,” Sensors, vol. 19, no. 7, Art. no. 7, Jan. 2019, doi: 10.3390/s19071488.

[92] P. Quinn and J. Guichard, “Service Function Chaining: Creating a Service Plane via Network Service Headers,” Computer, vol. 47, no. 11, pp. 38–44, Nov. 2014, doi: 10.1109/MC.2014.328.

[93] “Why distribution matters in NFV.” Collaborative White Paper between Alcatel- Lucent and Telefonica, Aug. 2014.

[94] “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms - Calheiros - 2011 - Software: Practice and Experience - Wiley Online Library.” https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.995 (accessed Jul. 18, 2018).

[95] “共通プラットフォームさいたま版の開発・実証｜プロジェクト｜UDCMi｜アーバンデザインセンターみその,” UDCMi｜アーバンデザインセンターみその. http://www.misono- tm.org/udcmi/projects/61.html (accessed Jan. 24, 2019).

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