3rd ACM Conference on Information-Centric Networking (ICN 2016), Sept. 26-28, 2016

ICN architectures introduce a major paradigm shift in networking, by reorienting the focus from point-to-point communication to the acquisition of data and content. This paradigm shift has opened up new vistas for networking research. Traditional network functionalities such as routing, scheduling, and congestion control must be reinterpreted and redesigned for the information-centric context. Caching and multicast are significantly enabled by ICN architectures, and attain a new level of importance. Philosophically, ICN architectures aim to intelligently use both bandwidth and storage resources for efficient content distribution. As ICNs are still at an early stage of development, there is a tremendous opportunity to identify and develop schemes managing ICN resources that provide performance guarantees. This highlights the importance of comprehensive frameworks within which key ICN network functionalities are jointly optimized.

In this tutorial, we review several recently developed frameworks for the optimal design of ICN networks. Well grounded in the theory of stochastic control, optimization, and distributed systems, these frameworks yield new algorithms for jointly optimal information-centric forwarding, caching, scheduling, and congestion control. The resulting algorithms fully exploit the unique characteristics of ICN architectures, and provide optimality guarantees in terms of throughput, delay, and utility performance. Moreover, the algorithms are distributed, dynamic, and adaptable to changing user demands and network conditions. We discuss how these design frameworks and algorithms might be used to further realize the potential impact of ICN networking architectures.

The tutorial targets researchers interested in the modeling, analysis, and implementation of ICNs.

The tutorial will be organized in three sections: (a) Background and Motivation, providing an overview of the ICN paradigm, (b) Throuput Optimal ICN Design, discussing ICN designs that are throughput optimal, and (c) Delay Optimal ICN Design, discussing ICN designs that come with delay guarantees.

In more detail, the tutorial will cover the following topics:

• Background and Motivation. ICN vision, basic concepts (back propagation, caching and/or routing, path replication and traditional policies). Comparison to IP, pushing content to the edge, opportunities to optimize.
• Throughput Optimal ICN Design. Throughput maximization in ICN networks. The VIP Framework. Throughput optimal distributed, adaptive algorithms for joint forwarding and caching. Stable caching algorithms. Content-based congestion control. Distributed algorithms for optimal congestion control, caching, and forwarding.
• Delay Optimal ICN Design. Delay minimization as an offline optimization problem over arbitrary topologies. Offline approximation algorithms. Suboptimality of path replication with LRU, LFU, FIFO, and other traditional policies. Distributed, adaptive algorithms for caching with optimality guarantees. Joint caching and routing. General utility-based frameworks, TTL-based caches, and Che approximation.

Stratis Ioannidis is an Assistant Professor in the ECE Department of Northeastern University, in Boston, MA. He received his B.Sc. (2002) in Electrical and Computer Engineering from the National Technical University of Athens, Greece, and his M.Sc. (2004) and Ph.D. (2009) in Computer Science from the University of Toronto, Canada. Prior to joining Northeastern, he was a research scientist at the Technicolor research centers in Paris, France, and Palo Alto, CA, as well as at Yahoo Labs in Sunnyvale, CA. He has worked extensively on the design, modeling, and analysis of content distribution and caching algorithms for large-scale networks.

Edmund Yeh is a Professor of Electrical and Computer Engineering at Northeastern University, Boston, USA. He received his B.S. in Electrical Engineering with Distinction and Phi Beta Kappa from Stanford University in 1994. He then studied at Cambridge University on the Winston Churchill Scholarship, obtaining his M.Phil in Engineering in 1995. He received his Ph.D. in Electrical Engineering and Computer Science from MIT under Professor Robert Gallager in 2001. He was previously Assistant and Associate Professor of Electrical Engineering, Computer Science, and Statistics at Yale University. Professor Yeh was one of the co-PIs on the original NSF-funded FIA Named Data Networking project. He is the recipient of the Alexander von Humboldt Research Fellowship, the Army Research Office Young Investigator Award, and the Best Paper Award at the 2015 IEEE International Conference on Communications (ICC) Communication Theory Symposium, London, UK.