NeTS Small: Analysis and Design of Best-Effort Content-Caching Networks

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Since the development of its earliest technical foundations more than 40 years ago, the Internet?s dominant communication paradigm has been packet-based, host-to-host communication. However, as the Internet has matured and increasingly more applications have been developed on top of this communication abstraction, there is a growing realization that many user applications are primarily concerned with accessing content rather than communicating with a specific host. In this content-centric view, emphasis is placed on what is obtained rather than from where it is obtained, and content search, dissemination (routing), and storage are consequently of increased importance. Indeed, several 'clean slate' approaches towards Internet architecture have emphasized in-network content naming, search, routing, and storage (including in-network caching ) as key architectural components of a next-generation Internet architecture.Intellectual Merit. This project undertakes fundamental research on developing the modeling and performance evaluation tools/methodologies, and on designing and evaluating approaches for a key architectural element of these content-centric network architectures - dynamic, demand-driven, in-network, content caching. This effort will develop bounding deterministic performance models of caching networks based on a -characterization of content request streams, probabilistic bounds performance using stochastic bounding techniques, and approximate performance models for networks of caches based on reduced-load approximation techniques. The research will also investigate several simple best-effort algorithms for content-caching and content-location; here, the focus will be on the underlying approaches themselves rather than their embodiment in any particular content-centric network architecture. Broader Impact. The modeling and analysis of in-network caching - a component of many content-centric next generation network architectures - will provide tools and techniques for analyzing such networks in much the same way that network calculi and reduced-load approximations have served as foundations for bounding and approximate analyses of complex queueing and blocking networks that have been used to model a wide range of packet-switched and circuit-switched networks and their protocols. The project's investigation of specific simple, 'best effort' content-caching and content-location algorithms is based on the belief that just as a best-effort Internet service model has proven to be 'good enough' compared with more sophisticated network architectures, best-effort caching may similarly prove 'good enough' when compared to more stateful and more complex request routing and cache-content management approaches. This would be a lesson with far-reaching impact. Graduate research assistants and undergraduate REU students will be mentored as part of this project, helping to educate the next generation of networking researchers. Involvement of minority graduate students will be coordinated through the Northeast Alliance for Graduate Education and the Professoriate (NEAGEP). Research results will be adopted into a widely-disseminated graduate networking course taught at the University of Massachusetts.