This project aims at developing scientific and technological advances required for the deployment of real-time applications as part of the IoT paradigm. To provide support for real-time IoT traffic, we need to redesign various elements of today's Internet. This include how we reduce the impact of packet drops, how we route and schedule packets, and how we provide end-to-end support for such applications. The proposed research will focus on each of the above three issues related to IoT traffic control and communication, using real-time applications as the target domain.
PI "Redesigning Internet Protocols for Emerging Internet of Things Applications". KAUST CRG-5 with $1,487,649. (under review)
Prof. Fahad Dogar, Computer Science, Tufts University, USA
- E. Ahmad, M. Alaslani, F. Dogar, and B. Shihada, "Location-Aware, Context-Driven QoS for IoT Applications", IEEE Systems Journal, Accepted, 2019.
- M. Alaslani and B. Shihada, "Analyzing Latency and Dropping in Today’s Internet of Multimedia Things", in Proc. IEEE Consumer Communications & Networking Conference (CCNC), pp. 1 - 4, 2019
- M. Alaslani and B. Shihada, "Intelligent Edge: an Instantaneous Detection of IoT Traffic Load", in Proc. IEEE International Conference on Communications (ICC), pp. 1 - 6, 2018
Mobile Crowd-Sensing for E-Health Monitoring and Hot-Spot Detection, Bell Canada, Canada, KSA, April 2014. [PPT]
IoT: a Journey from Wireless Sensor Devices to Data Centers", Keynote Speech, IEEE CommNet, Moroco, April 2019.
- CrowdWatch v1.0, 2014. Android Application for extracting smart phone sensor data for crowd monitoring.
- SADIQ v1.0, 2017. SDN-based system for providing IoT applications with location aware and context-driven QoS. Also available at github.
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