Control of Computing and Communication Systems Lab
The Control of Computing and Communication Systems lab focuses on the analysis and control of network systems. Example of applications are: adaptive video streaming, Web real time communication WebRTC, control and orchestration of CDN, Server overload control, SIP overload control, TCP congestion control. Control of such systems involves: non linear control, switching control, time-delay system control, optimal control, robust control.
We are looking for graduates, PhDs, and PostDocs to conduct research in the context of the project PLATform for INnOvative services in future internet. Click here for more details on the positions.
|Research Topics||Research Projects|
2014 August Google Faculty Award 2014 for designing a congestion control algorithm for real-time communication within the WebRTC framework to enable video conference among Web browsers.
- Principal investigator: S. Mascolo
- Title:Congestion Control for Web Real-Time Communication (WebRTC)
- Press coverage: Link
- H. Lundin, S. Holmer, H. Alvestrand, L. De Cicco, and S. Mascolo
A Google Congestion Control Algorithm for Real-Time Communication
IETF draft RMCAT wg, draft-alvestrand-rmcat-congestion-02, Feb 2014 (Web: Link)
2013 Nov Our adaptive video streaming platform is used by:
2013 June In this paper we experimentally evaluate the Google Congestion Control (GCC) which has been recently proposed in the RTCWeb IETF WG. By setting up a controlled testbed, we have evaluated to what extent GCC flows are able to track the available bandwidth, while minimizing queuing delays, and fairly share the bottleneck with other GCC or TCP flows. We have found that the algorithm works as expected when a GCC flow accesses the bottleneck in isolation, whereas it is not able to provide a fair bandwidth utilization when a GCC flow shares the bottleneck with either a GCC or a TCP flow.
- L. De Cicco, G. Carlucci, and S. Mascolo
Experimental Investigation of the Google Congestion Control for Real-Time Flows
ACM SIGCOMM 2013 Workshop on Future Human-Centric Multimedia Networking, Hong Kong, China, Aug 2013 (PDF)
Cisco Award 2013 Funded by "Cisco University Research Program" managed by the Silicon Valley Community Foundation.This proposal aims at designing a robust, efficient and scalable control system for adaptive (live) video streaming over the best-effort Internet. The first part of the proposal will investigate, using a rigorous mathematical control approach, the advantage of designing a server-side with respect to a client-side adaptation method such as the one supported by Apple, Akamai or Microsoft IIS. The mathematical model will take into account propagation delays that play a critical role in such control system and it will be rigorous and yet simple so that it will provide a tool for easy designing and tuning of the control. The second part of the proposal will implement the adaptive video streaming system first on a single server located in our lab and then in a Amazon EC2 cloud or a ""Cisco Multimedia Cloud"" aiming at further deployment in production networks.
- Principal investigator: S. Mascolo
Title : Architecture for Robust and Efficient Control of Dynamic Adaptive Video Streaming over HTTP.
2013 March In this paper, we present a model of the automatic video stream-switching employed by Akamai along with a description of the client-side communication and control protocol. From the control architecture point of view, the automatic adaptation is achieved by means of two interacting control loops having the controllers at the client and the actuators at the server: one loop is the buffer controller, which aims at steering the client playout buffer to a target length by regulating the server sending rate; the other one implements the stream-switching controller and aims at selecting the video level. A detailed validation of the proposed model has been carried out through experimental measurements in an emulated scenario.
- L. De Cicco and S. Mascolo
An Adaptive Video Streaming Control System: Modeling, Validation, and Performance Evaluation
IEEE/ACM Transaction on Networking, in press (PDF)