Content-centric wireless networks
This project seeks to advance our fundamental understanding of content-centric wireless networks. Communication networks are traditionally connection-centric, i.e., establish a reliable data connection between end-nodes. Recently, there has been a significant shift in network usage, where the users' intent is to access some specific (broadband and video) content rather than connect to a specific node. While there have been significant advances in enabling higher data rates in connection-centric wireless networks, the strategic use of storage along with jointly designed data delivery has received less attention in wireless networks. The goal of this project is to develop an information-theoretic framework for a content-centric approach to wireless, that enables a strategic positioning and use of storage jointly optimized with wireless information flow. This framework will be based on a content-distribution capacity region, which will characterize the region of transmission size versus cache storage, for different wireless network topologies, with user demands following from non-uniform content popularity profiles. We will develop both a theory and explicit strategies for content-centric wireless networks using a broad set of tools ranging from Shannon theory, network algorithms and coding as well as ideas from content-distribution network system design. The project also promotes the training of research engineers: we will integrate the research results into curricula by creating novel courses combining the underlying concepts in wireless network information flow, storage and wireless content-delivery systems. The research in this project, if successful, will contribute to the fundamental sciences of information flow and storage in wireless networks. Given the exponentially rising demand for wireless data, driven by media content, the results will serve as an enabler for wireless broadband content distribution that leverages dimensions beyond brute spectrum allocation.
- N. Karamchandani, U. Niesen, M. A. Maddah-Ali, and S. N. Diggavi, "Hierarchical coded caching," IEEE Transactions on Information Theory, vol. 62, iss. 6, pp. 3212-3229, 2016.
- J. Hachem, U. Niesen, and S. Diggavi, "A layered caching architecture for the interference channel," in Proc. 2016 IEEE International Symposium on Information Theory (ISIT), 2016, pp. 415-419.
- J. Hachem, N. Karamchandani, and S. N. Diggavi, "Coded Caching for Multi-level Popularity and Access," IEEE Transactions on Information Theory, vol. 63, iss. 5, pp. 3108-3141, 2017.
- J. Hachem, U. Niesen, and S. Diggavi, "Degrees of Freedom of Cache-Aided Wireless Interference Networks," Preprint, 2016.
- J. Hachem, N. Karamchandani, S. Moharir, and S. Diggavi, "Coded Caching With Partial Adaptive Matching," in Proc. 2017 IEEE International Symposium on Information Theory (ISIT), 2017.Note: available on arXiv:1705.03852 [cs.IT]Download: jad_adaptive.pdf
- J. Hachem, N. Karamchandani, and S. Diggavi, "Content caching and delivery over heterogeneous wireless networks," in Proc. Computer Communications (INFOCOM), 2015 IEEE Conference on, 2015, pp. 756-764.Abstract:Emerging heterogeneous wireless architectures consist of a dense deployment of local-coverage wireless access points (APs) with high data rates, along with sparsely-distributed, large-coverage macro-cell base stations (BS). We design a coded caching-and-delivery scheme for such architectures that equips APs with storage, enabling content pre-fetching prior to knowing user demands. Users requesting content are served by connecting to local APs with cached content, as well as by listening to a BS broadcast transmission. For any given content popularity profile, the goal is to design the caching-and-delivery scheme so as to optimally trade off the transmission cost at the BS against the storage cost at the APs and the user cost of connecting to multiple APs. We design a coded caching scheme for non-uniform content popularity that dynamically allocates user access to APs based on requested content. We demonstrate the approximate optimality of our scheme with respect to information-theoretic bounds. We numerically evaluate it on a YouTube dataset and quantify the trade-off between transmission rate, storage, and access cost. Our numerical results also suggest the intriguing possibility that, to gain most of the benefits of coded caching, it suffices to divide the content into a small number of popularity classes.
- J. Hachem, N. Karamchandani, and S. Diggavi, "Effect of number of users in multi-level coded caching," in Proc. Information Theory (ISIT), 2015 IEEE International Symposium on, 2015, pp. 1701-1705.Abstract:It has been recently established that joint design of content delivery and storage (coded caching) can significantly improve performance over conventional caching. This has also been extended to the case when content has non-uniform popularity through several models. In this paper we focus on a multi-level popularity model, where content is divided into levels based on popularity. We consider two extreme cases of user distribution across caches for the multi-level popularity model: a single user per cache (single-user setup) versus a large number of users per cache (multi-user setup). When the capacity approximation is universal (independent of number of popularity levels as well as number of users, files and caches), we demonstrate a dichotomy in the order-optimal strategies for these two extreme cases. In the multi-user case, sharing memory among the levels is order-optimal, whereas for the single-user case clustering popularity levels and allocating all the memory to them is the order-optimal scheme. In proving these results, we develop new information-theoretic lower bounds for the problem.
- N. Karamchandani, U. Niesen, M. A. Maddah-Ali, and S. Diggavi, "Hierarchical coded caching," in Proc. Information Theory (ISIT), 2014 IEEE International Symposium on, 2014, pp. 2142-2146.Abstract:It has recently been demonstrated that for single-layer cache networks, jointly designing caching and delivery can enable significant benefits over conventional caching. This was based on strategically designing the cached content to induce coded multicasting opportunities even among users with different demands and without foreknowledge of the user demands. In this work, we extend this coded caching approach to a multi-hop hierarchical content delivery network with two layers of caches. We propose a new caching scheme that combines two basic approaches. The first approach provides coded multicasting opportunities within each layer (through decoding and forwarding); the second approach provides coded multicasting opportunities across multiple layers (through strategic forwarding without decoding). By striking the right balance between these two approaches, we show that the proposed scheme achieves the optimal communication rates to within a constant multiplicative and additive gap. We further show that there is no tension between the rates in each of the two layers up to the aforementioned gap. Thus, both layers can simultaneously operate at approximately the minimum rate.
- J. Hachem, N. Karamchandani, and S. Diggavi, "Multi-level coded caching," in Proc. Information Theory (ISIT), 2014 IEEE International Symposium on, 2014, pp. 56-60.Abstract:Recent work has demonstrated that, for content caching, joint design of storage and delivery can yield significant benefits over conventional caching approaches. This is based on storing content in the caches in a way that creates coded-multicast opportunities even among users with different demands. Such a coded-caching scheme has been shown to be order-optimal for a caching system with single-level content, i.e., one where all content is uniformly popular. In this work, we consider a system with content divided into multiple levels, based on varying degrees of popularity. The main contribution of this work is the derivation of an information-theoretic outer bound for the multi-level setup, and the demonstration that, under some natural regularity conditions, a memory-sharing scheme, which operates each level in isolation according to a single-level coded caching scheme, is in fact order-optimal with respect to this outer bound.