A Situation Aware Information Infrastructure (\(SAI^2\)) Framework
Computer network infrastructures constitute the critical backbone of every socio-economic ICT system. Consequently, they are becoming increasingly mission-critical in our society since they provide always-on services for many everyday applications (e.g., Cloud Data Centres), safety-critical operations (e.g., Air Traffic Control networks), critical manufacturing services (e.g., Utility networks and Industrial Control Systems), and critical real-time services (e.g., Financial Trading Systems). The resilience and ability of such systems to remain operational in the face of threats is therefore paramount; this needs to be done by taking remedial action and intelligently reshaping their resources. At the same time, current communication architectures do not allow for such informed and adaptive provisioning. In this paper, we introduce the concepts, principles and current research activities related to a new Situation Aware Information Infrastructure (\(SAI^2\)) framework being developed for next generation ICT environments.
KeywordsSituation awareness Network resilience Security Computer networks
The work has been supported in part by the UK Engineering and Physical Sciences Research Council (EPSRC) grants EP/N033957/1, EP/L026015/1, and EP/L005255/1. The authors are grateful to Simon Jouet, Long Chen, Noor Shirazi, Steven Simpson and Ghulam Mohi Ud Din for their valuable input.
- 1.Jouet, S., Cziva, R., Pezaros, D.P.: Arbitrary packet matching in openflow. In: 16th IEEE International Conference on High Performance Switching and Routing (IEEE HPSR), Budapest, Hungary, 1–4 July 2015Google Scholar
- 2.Marnerides, A.K., Bhandari, A., Murthy, H., Mauthe, A.U.: A multilevel resilience framework for unified networked environments. In: 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), Ottawa, ON (2015)Google Scholar
- 3.Ariffin, M.A.M., Marnerides, A.K., Mauthe, A.U.: Multi-level resilience in networked environments: concepts & principles. In: IEEE CCNC 2017, Las Vegas, NV, USA (2017, to appear)Google Scholar
- 4.McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., Turner, J.: Openflow: enabling innovation in campus networks. In: ACM SIGCOMM, March 2008Google Scholar
- 8.Ud Din, G.M., Marnerides, A.K.: Short term power load forecasting using deep neural networks. In: IEEE International Conference on Computing, Networking and Communications (ICNC) 2017, Silicon Valley, USA, January 2017, to appearGoogle Scholar