Network of Excellence in Internet Science

Alcatel-Lucent Bell

Alcatel-Lucent (ALB) product portfolio and solutions enable carriers, Internet service providers, enterprises and governments worldwide, to deliver voice, video, multimedia, and data communication services to end-users. ALB product portfolio addresses wireline edge/core, wireless/mobile and broadband access networks. With more than 77000 employees and operations in more than 130 countries, Alcatel-Lucent is a local partner with global reach. The company has one of the largest research, technology and innovation organizations focused on communications — Alcatel-Lucent Bell Labs — and the most experienced global services team in the industry. Alcatel-Lucent achieved adjusted revenues of Euro 16.98 billion in 2008, and is incorporated in France, with headquarters in Paris.

ALB is committed to support scientific, technical and network/system engineering research in communications industry at large. ALB is one of the largest innovation powerhouses in the communications industry; its R&D investment represents a combined effort of Euro 2.5 billion. Its patent portfolio includes over 26000 active patents spanning most information and communication technology areas. At the core of this inno-vation is Alcatel-Lucent’s Bell Labs, with scientists at the forefront of applied research areas such as networked multimedia/video and applica-tions, wireless and wireline access networks, self-adaptive networks, cognitive networks as well as fundamental research areas such as applied mathematics/statistics, algorithmics, and computer science.

Early 2006, Alcatel-Lucent Bell was also part of the co-founder group of the EIFFEL initiative that has been followed by a FP7 Call 1 Support Action (SA) on the future of the Internet towards the development of the future networked society. As part of the Future Internet Research and Experimentation (FIRE) initiative, Alcatel-Lucent Bell leads two FIRE STREPs projects on mutli-disciplinary research: the ECODE (Experimental COgnitive Distributed Engine) FP7 Call 2 project and the EULER (Experimental UpdateLess Evolutive Routing) FP7 Call 5 project. The ECODE project ( designs and experiments machine learning-based control techniques. For this purpose, the project has designed, developed, and experimented a distributed machine-learning component that augments the capability and functionality of the routing and the forwarding engine of routers. To evaluate the executability and the performance of the developed machine learning based control functionality, several experiments have been conducted at the iLab.t facility, located at IBBT.

The EULER project ( main objective is to investigate new routing paradigms so as to design, develop, and validate experimentally a distributed and dynamic routing scheme suitable for the future Internet and its evolution. The resulting routing scheme(s) is/are intended to address the fundamental limits of current stretch-1 shortest-path routing in terms of routing table scalability but also topology and policy dynamics (perform efficiently under dynamic network conditions). The followed research methodology relies on the cross-fertilization between i) structural, stochastic as well as measurement-based topology (dynamics and evolution) modelling, ii) policy interactions and dynamics modelling, and iii) dynamic routing algorithmics/distributed computing research disciplines; all three in combination with experimentation.