Popular Sequence Clustering Approaches

O SLOTS é um trabalho que está em andamento e, à luz dos resultados promissores dos trabalhos publicados, pretende-se melhorar significativamente o modelo de computa- ção estatística de recursos para aprimorar a abordagem solidária do SLOTS em trabalhos futuros. Além disso, pretende-se desenvolver um modelo de elasticidade horizontal para integrar ao mecanismo de elasticidade vertical existente. Assim, desenvolvendo um meca- nismo que aborde tanto a elasticidade vertical e horizontal de forma coordenada.

Outro ponto importante a ser analisado e avaliado em trabalhos futuros consiste em realizar comparações do mecanismo do SLOTS juntamente com outras técnicas de elasticidade, como aprendizagem por reforço, análise de séries temporais, teoria das filas e teoria dos controles. Apesar de existirem muitos tipos de mecanismos para a elasticidade, é necessário que uma avaliação profunda seja realizada com os tipos de mecanismos citados. Diante disso, surge a necessidade de comparar a abordagem do SLOTS com outros tipos de algoritmos da literatura atual, levando como principal ponto de análise a atuação destes mecanismos em cenários com insuficiência de recursos.

Pretende-se tratar da elasticidade horizontal de forma mais específica, buscando de- senvolver uma solução completa de gerenciamento de recursos que englobe a elasticidade vertical e horizontal, destacando-se assim das principais soluções existentes, uma vez que estas não tratam dos dois tipos de elasticidade. Portanto, aspectos da elasticidade ho- rizontal serão avaliados de forma mais precisa, incluindo a configuração do tesbed e a avaliação da performance do mecanismo de elasticidade horizontal.

O trabalho desenvolvido nesta dissertação será incorporado ao projeto NECOS, sendo que o mecanismo de elasticidade vertical é uma das contribuições no escopo de gerencia- mento de recursos do projeto. Assim, o SLOTS oferece a elasticidade vertical para sistemas cloud-network definidos por slices e futuramente fornecerá a elasticidade horizontal para estes sistemas.

Por fim, almeja-se dar continuidade as publicações relacionadas a este trabalho, tanto em pontos relacionados a elasticidade vertical quando aos trabalhos futuros levando em consideração a elasticidade horizontal, pois existe grande necessidade do desenvolvimento e aperfeiçoamento de novos mecanismos para a gerência de recursos no cenário 5G.

Referências

3GPP. Study on Architecture for Next Generation System. 2016. Disponível em: <http://www.tech-invite.com/3m23/tinv-3gpp-23-799.html>. Acesso em: 21 nov. 2018. 5GEX. EU H2020 - 5G Multi-Domain Exchange (5GEx) project. 2015. Disponível em: <https://5g-ppp.eu/5GEx/>. Acesso em: 21 dez. 2018.

AFOLABI, I. et al. Towards 5g network slicing over multiple-domains. IEICE Transactions on Communications, The Institute of Electronics, Information and Communication Engineers, v. 100, n. 11, p. 1992–2006, 2017.

AFOLABI, I. et al. Network slicing & softwarization: A survey on principles, enabling technologies & solutions. IEEE Communications Surveys & Tutorials, IEEE, 2018. AL-DHURAIBI, Y. et al. Autonomic vertical elasticity of docker containers with elasticdocker. In: IEEE. 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). [S.l.], 2017. p. 472–479.

AL-DHURAIBI, Y. et al. Elasticity in cloud computing: state of the art and research challenges. IEEE Transactions on Services Computing, IEEE, v. 11, n. 2, p. 430–447, 2018.

AL-SHARIF, Z. A. et al. Accrs: autonomic based cloud computing resource scaling. Cluster Computing, Springer, v. 20, n. 3, p. 2479–2488, 2017.

ALEX GALIS, KIRAN MAKHIJANI, DELEI YU AND BING LIU. Autonomic Slice Networking. 2018. Disponível em: <https://tools.ietf.org/html/draft-galis-anima- autonomic-slice-networking-03>. Acesso em: 2 dez. 2018.

ALLIANCE, N. 5g white paper. Next generation mobile networks, white paper, p. 1–125, 2015.

ALLIANCE, N. Description of network slicing concept. NGMN 5G P, v. 1, 2016.

AMAZON. Amazon Web Services. 2018. Disponível em: <https://aws.amazon.com/pt/>. Acesso em: 27 jan. 2019.

AMAZON AWS. Amazon Target Tracking Scaling. 2018. Disponível em: <http://docs.aws.amazon.com/autoscaling/latest/userguide/as-scaling-target- tracking.html>. Acesso em: 26 fev. 2019.

AUJLA, G. S. et al. Data offloading in 5g-enabled software-defined vehicular networks: A stackelberg-game-based approach. IEEE Communications Magazine, IEEE, v. 55, n. 8, p. 100–108, 2017.

AZURE, M. Autoscaling. [S.l.], 2018. Disponível em: <https://docs.microsoft.com/en- us/azure/architecture/best-practices/auto-scaling>.

BERA, S.; MISRA, S.; VASILAKOS, A. V. Software-defined networking for internet of things: A survey. IEEE Internet of Things Journal, IEEE, v. 4, n. 6, p. 1994–2008, 2017. BUYYA, R.; BROBERG, J.; GOSCINSKI, A. M. Cloud computing: Principles and paradigms. [S.l.]: John Wiley & Sons, 2010.

CHARTSIAS, P.-K. et al. Sdn/nfv-based end to end network slicing for 5g multi-tenant networks. In: IEEE. 2017 European Conference on Networks and Communications (EuCNC). [S.l.], 2017. p. 1–5.

CHATRAS, B.; KWONG, U. S. T.; BIHANNIC, N. Nfv enabling network slicing for 5g. In: IEEE. Innovations in Clouds, Internet and Networks (ICIN), 2017 20th Conference on. [S.l.], 2017. p. 219–225.

CLAYMAN, S.; TUSA, F.; GALIS, A. Extending slices into data centers: the vim on-demand model. 2018.

COLMAN-MEIXNER, C. et al. A survey on resiliency techniques in cloud computing infrastructures and applications. IEEE Communications Surveys & Tutorials, IEEE, v. 18, n. 3, p. 2244–2281, 2016.

COUTINHO, E. F. et al. Elasticity in cloud computing: a survey. annals of

telecommunications-annales des télécommunications, Springer, v. 70, n. 7-8, p. 289–309, 2015.

COX, J. H. et al. Advancing software-defined networks: A survey. IEEE Access, IEEE, v. 5, p. 25487–25526, 2017.

DAVIES, N.; THOMPSON, P. Challenges of network slicing. IEEE SDN Newsletter, 2017.

ETSI, G. Network functions virtualisation (nfv): Architectural framework. ETsI Gs NFV, v. 2, n. 2, p. V1, 2013.

FAROKHI, S. et al. Self-adaptation challenges for cloud-based applications: A control theoretic perspective. In: 10th international workshop on feedback computing. [S.l.: s.n.], 2015. v. 2015.

FOUKAS, X. et al. Network slicing in 5g: Survey and challenges. IEEE Communications Magazine, IEEE, v. 55, n. 5, p. 94–100, 2017.

Freitas, L. A. et al. Slicing and allocation of transformable resources for the deployment of multiple virtualized infrastructure managers (vims). In: 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). [S.l.: s.n.], 2018. p. 424–432.

GALANTE, G.; BONA, L. C. E. d. A survey on cloud computing elasticity. In: IEEE COMPUTER SOCIETY. Proceedings of the 2012 ieee/acm fifth international conference on utility and cloud computing. [S.l.], 2012. p. 263–270.

GALIS, A. Perspectives on network slicing–towards the new ‘bread and butter’of networking and servicing. Newsletter, 2018.

GALIS, A.; CHIH-LIN, I. Towards 5g network slicing-motivations and challenges. IEEE 5G Tech Focus, v. 1, 2017.

GALIS, A.; KUKLIŃSKI, S. Network slicing-revised problem statement. Working Draft, IETF Secretariat, Internet-Draft draft-galis-netslices-revised-problem-statement-01, 2017. GARG, S. K.; VERSTEEG, S.; BUYYA, R. A framework for ranking of cloud computing services. Future Generation Computer Systems, Elsevier, v. 29, n. 4, p. 1012–1023, 2013. GOOGLE. Autoscaling Groups of Instances. [S.l.], 2018. Disponível em:

<https://cloud.google.com/compute/docs/autoscaler/>.

GOOGLE. Google Cloud Platform. 2018. Disponível em: <https://cloud.google.com/>. Acesso em: 27 jan. 2019.

GOOGLE. Google Multiple Policies Scaling. 2018. Disponível em:

<https://cloud.google.com/compute/docs/autoscaler/multiple-policies>. Acesso em: 26 fev. 2019.

GOOGLE. Kubernetes Horizontal Pod Auto-scaling. 2019. Disponível em: <https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/>. Acesso em: 23 fev. 2019.

GRAMAGLIA, M. et al. Flexible connectivity and qoe/qos management for 5g

networks: The 5g norma view. In: IEEE. Communications Workshops (ICC), 2016 IEEE International Conference on. [S.l.], 2016. p. 373–379.

GUTIERREZ-ESTEVEZ, D. M. et al. The path towards resource elasticity for 5g network architecture. In: IEEE. Wireless Communications and Networking Conference Workshops (WCNCW), 2018 IEEE. [S.l.], 2018. p. 214–219.

HALEPLIDIS, E. et al. Software-defined networking (SDN): Layers and architecture terminology. [S.l.], 2015.

HAN, B. et al. Network function virtualization: Challenges and opportunities for innovations. IEEE Communications Magazine, IEEE, v. 53, n. 2, p. 90–97, 2015. HAN, R. et al. Enabling cost-aware and adaptive elasticity of multi-tier cloud applications. Future Generation Computer Systems, Elsevier, v. 32, p. 82–98, 2014. HERBST, N. R.; KOUNEV, S.; REUSSNER, R. H. Elasticity in cloud computing: What it is, and what it is not. In: ICAC. [S.l.: s.n.], 2013. v. 13, p. 23–27.

HU, F.; HAO, Q.; BAO, K. A survey on software-defined network and openflow: From concept to implementation. IEEE Communications Surveys & Tutorials, IEEE, v. 16, n. 4, p. 2181–2206, 2014.

ITU. Framework of Network Virtualization for Future Networks. 2012. Disponível em: <https://www.itu.int/rec/T-REC-Y.3011/en>. Acesso em: 23 dez. 2018.

JAIN, R. The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. [S.l.]: John Wiley & Sons, 1990.

JEFF BARR. AWS Auto Scaling. 2018. Disponível em:

<https://aws.amazon.com/pt/autoscaling/>. Acesso em: 10 jan. 2019.

KAN, C. Docloud: An elastic cloud platform for web applications based on docker. In: IEEE. 2016 18th International Conference on Advanced Communication Technology (ICACT). [S.l.], 2016. p. 478–483.

KREUTZ, D. et al. Software-defined networking: A comprehensive survey. Proceedings of the IEEE, Ieee, v. 103, n. 1, p. 14–76, 2015.

KUMAR, D.; GONDHI, N. K. A qos-based reactive auto scaler for cloud environment. In: IEEE. 2017 International Conference on Next Generation Computing and Information Systems (ICNGCIS). [S.l.], 2017. p. 19–23.

LI, M. et al. A scalable and elastic publish/subscribe service. In: IEEE. 2011 IEEE International Parallel & Distributed Processing Symposium. [S.l.], 2011. p. 1254–1265. LI, Y.; CHEN, M. Software-defined network function virtualization: A survey. IEEE Access, IEEE, v. 3, p. 2542–2553, 2015.

LIN, T.; ZHOU, Z. Nfv-enabled network slicing. In: IEEE. 2018 IEEE International Conference on Communications Workshops (ICC Workshops). [S.l.], 2018. p. 1–6. LORENZ, D. et al. Slicenet: Cognitive slice management framework for virtual

multi-domain 5g networks. In: ACM. Proceedings of the 11th ACM International Systems and Storage Conference. [S.l.], 2018. p. 129–129.

LORIDO-BOTRAN, T.; MIGUEL-ALONSO, J.; LOZANO, J. A. A review of auto-scaling techniques for elastic applications in cloud environments. Journal of grid computing, Springer, v. 12, n. 4, p. 559–592, 2014.

LORIDO-BOTRCN, T.; MIGUEL-ALONSO; LOZANO, J. A. Comparison of auto-scaling techniques for cloud environments. 2013.

MA, L. et al. An sdn/nfv based framework for management and deployment of service based 5g core network. China Communications, IEEE, v. 15, n. 10, p. 86–98, 2018. MARINESCU, D. C. Cloud computing: Theory and practice. Computer Science Division, 2012.

MARTÍNEZ, R. et al. Network slicing resource allocation and monitoring over multiple clouds and networks. In: IEEE. 2018 Optical Fiber Communications Conference and Exposition (OFC). [S.l.], 2018. p. 1–3.

MELL, P.; GRANCE, T. et al. The nist definition of cloud computing. Computer Security Division, Information Technology Laboratory, National Institute of Standards and Technology Gaithersburg, 2011.

MIJUMBI, R. et al. Network function virtualization: State-of-the-art and research challenges. IEEE Communications Surveys & Tutorials, IEEE, v. 18, n. 1, p. 236–262, 2016.

MUMFORD, R. Nokia Drives 5G MoNArch European Research Project. [S.l.]: HORIZON HOUSE PUBLICATIONS INC 685 CANTON ST, NORWOOD, MA 02062 USA, 2017. NASKOS, A.; GOUNARIS, A.; SIOUTAS, S. Cloud elasticity: a survey. In: SPRINGER. International Workshop on Algorithmic Aspects of Cloud Computing. [S.l.], 2015. p. 151–167.

OLIVA, A. De la et al. 5g-transformer: Slicing and orchestrating transport networks for industry verticals. IEEE Communications Magazine, IEEE, v. 56, n. 8, p. 78–84, 2018. ORDONEZ-LUCENA, J. et al. Network slicing for 5g with sdn/nfv: concepts, architectures and challenges. arXiv preprint arXiv:1703.04676, 2017.

RACKSPACE. Rackspace Public Cloud. 2018. Disponível em: <https://www.rackspace.com/pt/cloud>. Acesso em: 27 jan. 2019.

RIGHI, R. da R. et al. Autoelastic: Automatic resource elasticity for high performance applications in the cloud. IEEE Transactions on Cloud Computing, IEEE, v. 4, n. 1, p. 6–19, 2016.

RIGHI, R. da R. et al. A lightweight plug-and-play elasticity service for self-organizing resource provisioning on parallel applications. Future Generation Computer Systems, Elsevier, v. 78, p. 176–190, 2018.

SCIANCALEPORE, V. et al. Mobile traffic forecasting for maximizing 5g network slicing resource utilization. In: IEEE. INFOCOM 2017-IEEE Conference on Computer Communications, IEEE. [S.l.], 2017. p. 1–9.

SHENKER, S. et al. The future of networking, and the past of protocols. Open Networking Summit, v. 20, p. 1–30, 2011.

SILVA, F. S. D. et al. Necos project: Towards lightweight slicing of cloud federated infrastructures. In: IEEE. 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft). [S.l.], 2018. p. 406–414.

SONATA. EU H2020 - 5G Service Programing and Orchestration for Virtualized Software Networks. 2015. Disponível em: <https://5g-ppp.eu/sonata/>. Acesso em: 21 dez. 2018.

SPADARO, S. et al. Orchestrated sdn-based vdc provisioning over multi-technology optical data centre networks. In: IEEE. Transparent Optical Networks (ICTON), 2017 19th International Conference on. [S.l.], 2017. p. 1–4.

STEPHEN WATTS. SaaS vs PaaS vs IaaS: What’s The Difference and How To Choose. 2018. Disponível em: <https://www.bmc.com/blogs/saas-vs-paas-vs-iaas-whats-the- difference-and-how-to-choose/>. Acesso em: 22 dez. 2018.

STUART CLAYMAN. D3.1: NECOS System Architecture and Platform Specification. V1. 2018. Disponível em: <http://www.h2020-necos.eu/documents/deliverables/>. Acesso em: 22 fev. 2019.

SUN, C. et al. Enabling nfv elasticity control with optimized flow migration. IEEE Journal on Selected Areas in Communications, IEEE, 2018.

TALEB, T. et al. On multi-access edge computing: A survey of the emerging 5g network edge cloud architecture and orchestration. IEEE Communications Surveys & Tutorials, IEEE, v. 19, n. 3, p. 1657–1681, 2017.

TOOSI, A. N. et al. Management and orchestration of network slices in 5g, fog, edge and clouds. 2018.

ZHANG, Q.; CHENG, L.; BOUTABA, R. Cloud computing: state-of-the-art and research challenges. Journal of internet services and applications, Springer, v. 1, n. 1, p. 7–18, 2010.

ZHIQUN, X. et al. Emerging of telco cloud. China Communications, IEEE, v. 10, n. 6, p. 79–85, 2013.