Anil Singh
ABSTRACT
Edge computing extends a traditional cloud data centre model often by using a micro data centre (mdc) at the network edge for computation and storage. As these edge devices are in proximity to users, this results in improved application response times and reduces load on the cloud data center (cdc). In this paper, we propose a security and deadline aware scheduling algorithm called RT-SANE (Real-Time Security Aware scheduling on the Network Edge). Applications with stringent privacy requirements are scheduled on an mdc closer to the user, whereas others can be scheduled on a cdc or a remote mdc. We also discuss how application performance and network latency influence the choice of an mdc or cdc. The intuition is that due to a lower communication latency between the user & the mdc, more applications are able to meet their deadlines when run on the mdc. Conversely, applications with loose deadlines may be executed on a cdc. In order to facilitate this, we also propose a distributed orchestration architecture and protocol that is both performance & security aware. Simulation results show that RTSANE offers superior real-time performance compared to a number of other scheduling policies in an Edge computing environment, while meeting application privacy requirements.
- Fog Computing and the Internet of Things: Extend the Cloud to Where the Things Are, Cisco White Paper, 2015.Google Scholar
- A. V. Daesterjerdi and R. Buyya, Fog Computing: Helping the Internet of things to realize their potential, IEEE Computer, vol. 49, no. 8, pp. 112--116, 2016. Google ScholarDigital Library
- L. F. Bittencourt, O. Rana, and I. Petri, Cloud Computing at the Edges, Springer International Publishing, 2016, pp. 3--12.Google Scholar
- F. Bonomi, R. Milito, P. Natarajan, and J. Zhu, Fog Computing: A platform for Internet of things and analytics, Springer International Publishing, 2014, pp. 169--196.Google Scholar
- B. Jennings and R. Stadler, Resource management in clouds: survey and research challenges, Journal of Network and Systems Management, vol. 23, no. 3, 2015, pp. 567--619. Google ScholarDigital Library
- H. Gupta, A. V. Dastjerdi, S. K. Ghosh, and R. Buyya, iFogSim: A toolkit for modeling and simulation of resource management techniques in Internet of things, edge and fog computing environments, CORR abs, vol. 1606.02007, 2016. {Online}. Available: http://arxi.org/abs/1606.02007.Google Scholar
- L. F. Bittencourt, E. R. M. Madeira, and N. L. S. Da Fonseca, Scheduling in hybrid clouds, IEEE Communications Magazine, vol. 50, no. 9, 2012, pp. 42--47.Google ScholarCross Ref
- J. D. Montes, M. Abdelbaky, M. Zhou, and M. Parashar, Cometcloud: Enabling software-defined federations for end-to-end application work-flows, IEEE Internet Computing, vol. 19, no. 1, 2015, pp. 69--73. Google ScholarDigital Library
- C. L. Liu and J. W. Layland, Scheduling algorithms for multiprogramming in a hard real-time environment, Journal of the ACM, vol. 20, no. 1, 1973, pp. 46--61. Google ScholarDigital Library
- Z. Guo and S. Baruah, A neurodynamic approach for real-time scheduling via maximizing piecewise linear utility, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 2, 2016, pp. 238--248.Google ScholarCross Ref
- J. Singh, S. Betha, B. Mangipudi, N. Auluck, Contention aware energy efficient scheduling on heterogeneous multiprocessors, IEEE Transactions on Parallel and Distributed Systems, vol. 26, no. 5, 2014, pp. 1251--1264.Google ScholarCross Ref
- B. A. Hridita, M. Irfan & M. S. Islam, Mobility aware task allocation for mobile cloud computing, International Journal of Computer Applications, Vol. 137, No. 9, 2016 pp. 35--41.Google ScholarCross Ref
- X. D. Pham & E. N. Huh, Towards task scheduling in a cloud fog computing system. The 18th Asia-Pacific Network Operations and Management Symposium, APNOMS, Kanazawa, Japan, October 5--7, 2106, pp. 1--4.Google Scholar
- M. Shojafar, N. Cordeschi and E. Baccarelli, Energy-efficient adaptive resource management for real-time vehicular cloud services, IEEE Transactions on Cloud Computing, preprint, April 6, 2016, pp. 1--14.Google Scholar
- L. F. Bittencourt, M. M. Lopes, I. Petri and O. Rana, Towards virtual machine migration in fog computing, The 10th International conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), November 4--6, 2015, Krakow, Poland, pp. 1--8. Google ScholarDigital Library
- F. Xia, L. T. Yang, L.Wang and A. Vinel, Internet of Things, Editorial, International Journal of Communication Systems, Vol. 25, 2012, pp. 1101--1102. Google ScholarDigital Library
- A. V. Dastjerdi, H. Gupta, R. N. Calheiros, S. K. Ghosh and R. Buyya, Fog computing: principles, architectures, and applications, Internet of Things: Principles and Paradigms, R. Buyya and A. Dastjerdi (eds), Morgan Kaufmann, ISBN: 978-0-12-805395-9, Burlington, Massachusetts, USA, May 2016.Google Scholar
- J. W. S. Liu, "Real-Time Systems", Prentice Hall, April 2000, 592 pages.Google Scholar
- S. Sharif, P. Watson, J. Taheri, S. Nepal, and A. Zomaya, Privacy-aware scheduling SaaS in high performance computing environments, IEEE Transactions on Parallel & Distributed Systems, vol. 28, no. 4, April 2017, pp. 1176--1188. Google ScholarDigital Library
- W. Shu, J. Cao, Q. Zhang, Y. Li, and L. Xu, Edge computing: vision and challenges, IEEE Internet of Things Journal, vol. 3, no. 5, October, 2016, pp. 637--646.Google ScholarCross Ref
- M. Satyanarayanan, G. Lewis, E. J. Morris, S. Simanta, J. Boleng, K. Ha, The role of cloudlets in hostile environments, IEEE Pervasive Computing, October, 2013, pp. 40--49. Google ScholarDigital Library
- M. Satyanarayanan, Augmenting cognition, IEEE Pervasive Computing, April, 2004, pp. 4--5. Google ScholarDigital Library
- S. Shekhar, A. D. Chhokra, A. Bhattacharjee, G. Aupy, and A. Gokhale, INDICES: Exploiting edge resources for performance aware cloud hosted services, First IEEE/ACM International Conference on Fog & Edge Computing, Madrid, Spain, May 14, 2017, pp. 75--80.Google ScholarCross Ref
- M. I. Naas, P. R. P. Orange, J. Boukhobza, L. Lemarchand, iFogStor: an IoT data placement strategy for fog infrastructure, First IEEE/ACM International Conference on Fog & Edge Computing, Madrid, Spain, May 14, 2017, pp. 97--104.Google ScholarCross Ref
- D. Evans, The Internet of Things, how the next evolution of the Internet is changing everything, Cisco White Paper, April 2011Google Scholar
Index Terms
- RT-SANE: Real Time Security Aware Scheduling on the Network Edge
Recommendations
Fog and Cloud Computing: A Solution for Business Application Deployment
With the introduction of cloud computing, many organizations have reduced the costs and burdens of maintaining an on-site data center, migrating their data and applications to the cloud. The accessibility to companies’ data and applications via the ...
Edge computing: A survey
AbstractIn recent years, the Edge computing paradigm has gained considerable popularity in academic and industrial circles. It serves as a key enabler for many future technologies like 5G, Internet of Things (IoT), augmented reality and ...
Highlights- A comprehensive survey on edge computing, i.e., Fog, Mobile-edge and Cloudlet.
- ...
Fogxy: An Architectural Pattern for Fog Computing
EuroPLoP '18: Proceedings of the 23rd European Conference on Pattern Languages of ProgramsFog computing is an emergent approach that tries to overcome challenges the cloud faces by introducing a fog tier in between the cloud and the edge of the network. With the advent of the cloud, computing power shifted back again to centralized ...
Comments