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Friday, July 04, 2008
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Information Networking

Information networking is an area of great impact. The CMUPortugal Program will partner Carnegie Mellon faculty drawn from CyLab, CenSCIR, ECE, and CS and several Portuguese research groups, including those at Universidade de Aveiro, INESCID, IT, and Universidade de Coimbra. There will also be a strong involvement with companies in the Portugal Telecom group. In a relatively short time, the Internet has evolved from a small research network used by researchers into a critical infrastructure that delivers a wide variety of services to hundreds of millions of users. Looking forward, we see a number of trends that are likely to cause a similarly dramatic transformation in the next ten to fifteen years. First, while the Internet initially connected fixed, wired, computers, current trends suggest that in the near future, the vast majority of users will use wireless, mobile devices to access Internet services. These personal devices will be complemented by large numbers of non-computational devices, including sensors, actuators, and I/O devices, most of which will also be wireless. This means that wireless will be pervasive as an access network technology. At the same time, the service infrastructure is evolving from simple client-server applications into a sophisticated, highly distributed, highly resilient software platform that delivers personalized services to users. These trends suggest a number of important research areas in information networking. For brevity, we illustrate by focusing on research in wireless networking and the delivery of electronic and pervasive computing services.

The pervasiveness of wireless networks creates a number of challenges. A first challenge is at the network architecture level, where mobility, device heterogeneity, and variable network properties will require new architectural paradigms for access networks that can maintain high service quality for mobile users. These will include new proxy architectures, security and authentication mechanisms, naming and addressing mechanisms, and bandwidth provisioning techniques. At a lower level, the high demand for wireless bandwidth will put pressure on a scarce resource, namely the spectrum. This will require improved efficiency at all layers of the wireless protocol stack. This can be achieved by “autonomic” networking techniques that automatically optimize the network based on wireless channel conditions, traffic load, and node properties – manual network configuration and control will be impractical because of network complexity and dynamics. At the same time, architectural solutions such as spectrum-agile networking, in which nodes opportunistically and dynamically use available spectrum, can be used to increase network capacity.

In order to have impact, this wireless networking research agenda will have to be executed in a realistic, forward-looking broader systems context. The research will have to be driven by aggressive applications, such as high quality video stream and interactive games, and highly mobile users, including car-based wireless networks. Results will have to be evaluated using both large testbeds that combine a variety of devices and applications in a realistic way, and emulation techniques that allow a more controlled quantitative evaluation of individual techniques.

Another key challenge in information networks is the development of a scalable infrastructure that can deliver personalized electronic services in a resilient and secure fashion. Examples of such services include information retrieval, e-commerce, and video conferencing, but also more aggressive services such as virtual reality, remote medicine, and interactive games. Three factors combine to make the delivery of such services a very challenging problem: the complexity of services themselves, the dynamics and unreliability of the underlying hardware infrastructure (network, servers, storage), and the variable user demand.

This infrastructure will require a highly modular approach in which services are constructed from basic building blocks. Not only does this maximize the potential for software reuse, but it also opens the door for the automated configuration and optimization of network services using closed-loop control systems. The service infrastructure will include a set of monitoring probes that can quickly detect failures, changes in load, performance problems, and intrusions. The output of these probes feeds into a diagnostic module that can identify the cause of the problem and formulate an automated response. This will require research of both an experimental and formal nature in a variety of areas, including distributed systems, software engineering, formal methods, and security.

Besides the delivery of the above-mentioned “electronic” services, we also envision a dramatic growth in the delivery of “physical” services that leverage the rapid deployment of sensors, actuators, and I/O devices. Examples of such “pervasive computing” services include location- and context-aware services, automated control of the user’s physical environment (heat, light...), and personalized entertainment. The requirements in this area are similar to those mentioned above for the electronic services infrastructure: how can we deliver personalized services in a resilient and secure fashion. However, because of the localized nature of the services and the tight coupling to the physical world, the challenges are different. Questions include: how to manage the large volume of data, how to translate noisy, dynamic sensor data into useful information, how to engineer applications that continuously adapt to the user’s context, and how to maintain privacy and security in this device rich environment.

Addressing these challenges requires an architecture that separates the responsibility of the different players using well-defined interfaces. At the lowest layer, we need techniques for the configuration and management of the sensor networks so they can deliver the sensor data to a set of information services in a timely fashion. The sensor data will be filtered and combined with data from other sources (e.g. calendar and other databases) to create context information that will be tagged with meta-data, e.g. to time stamps, precision, etc. This will effectively create a distributed database of context information that can be used by a variety of applications. If designed right, this architecture and its component can be reused in many environments, e.g. office, home, etc. This pervasive computing infrastructure can be built, deployed, and maintained by commercial service providers, similar to the electronic services infrastructure.

The CMU-Portugal Program includes an advanced degree program, a Professional Master of Science in Information Networking, to be offered in partnership by the University of Aveiro and the INI at CMU. Other potential partners, namely for research activities, should be defined during the initial phase of the Program. A PhD and a research component to be pursued in partnership with the ECE Department at CMU complement this program.

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