Performance Evaluation of Caching Policies in NDN - an ICN Architecture

Information Centric Networking (ICN) advocates the philosophy of accessing the content independent of its location. Owing to this location independence in ICN, the routers en-route can be enabled to cache the content to serve the future requests for the same content locally. Several ICN architectures have been proposed in the literature along with various caching algorithms for caching and cache replacement at the routers en-route. The aim of this paper is to critically evaluate various caching policies using Named Data Networking (NDN), an ICN architecture proposed in literature. We have presented the performance comparison of different caching policies naming First In First Out (FIFO), Least Recently Used (LRU), and Universal Caching (UC) in two network models; Watts-Strogatz (WS) model (suitable for dense short link networks such as sensor networks) and Sprint topology (better suited for large Internet Service Provider (ISP) networks) using ndnSIM, an ns3 based discrete event simulator for NDN architecture. Our results indicate that UC outperforms other caching policies such as LRU and FIFO and makes UC a better alternative for both sensor networks and ISP networks

Dynamic Coded Caching in Wireless Networks

We consider distributed and dynamic caching of coded content at small base stations (SBSs) in an area served by a macro base station (MBS). Specifically, content is encoded using a maximum distance separable code and cached according to a time-to-live (TTL) cache eviction policy, which allows coded packets to be removed from the caches at periodic times. Mobile users requesting a particular content download coded packets from SBSs within communication range. If additional packets are required to decode the file, these are downloaded from the MBS. We formulate an optimization problem that is efficiently solved numerically, providing TTL caching policies minimizing the overall network load. We demonstrate that distributed coded caching using TTL caching policies can offer significant reductions in terms of network load when request arrivals are bursty. We show how the distributed coded caching problem utilizing TTL caching policies can be analyzed as a specific single cache, convex optimization problem. Our problem encompasses static caching and the single cache as special cases. We prove that, interestingly, static caching is optimal under a Poisson request process, and that for a single cache the optimization problem has a surprisingly simple solution

Dynamic Coded Caching in Wireless Networks

We consider distributed and dynamic caching of coded content at small base stations (SBSs) in an area served by a macro base station (MBS). Specifically, content is encoded using a maximum distance separable code and cached according to a time-to-live (TTL) cache eviction policy, which allows coded packets to be removed from the caches at periodic times. Mobile users requesting a particular content download coded packets from SBSs within communication range. If additional packets are required to decode the file, these are downloaded from the MBS. We formulate an optimization problem that is efficiently solved numerically, providing TTL caching policies minimizing the overall network load. We demonstrate that distributed coded caching using TTL caching policies can offer significant reductions in terms of network load when request arrivals are bursty. We show how the distributed coded caching problem utilizing TTL caching policies can be analyzed as a specific single cache, convex optimization problem. Our problem encompasses static caching and the single cache as special cases. We prove that, interestingly, static caching is optimal under a Poisson request process, and that for a single cache the optimization problem has a surprisingly simple solution.Comment: To appear in IEEE Transactions on Communication

Optimistic No-regret Algorithms for Discrete Caching

We take a systematic look at the problem of storing whole files in a cache with limited capacity in the context of optimistic learning, where the caching policy has access to a prediction oracle (provided by, e.g., a Neural Network). The successive file requests are assumed to be generated by an adversary, and no assumption is made on the accuracy of the oracle. In this setting, we provide a universal lower bound for prediction-assisted online caching and proceed to design a suite of policies with a range of performance-complexity trade-offs. All proposed policies offer sublinear regret bounds commensurate with the accuracy of the oracle. Our results substantially improve upon all recently-proposed online caching policies, which, being unable to exploit the oracle predictions, offer only $O(\sqrt{T})$ regret. In this pursuit, we design, to the best of our knowledge, the first comprehensive optimistic Follow-the-Perturbed leader policy, which generalizes beyond the caching problem. We also study the problem of caching files with different sizes and the bipartite network caching problem. Finally, we evaluate the efficacy of the proposed policies through extensive numerical experiments using real-world traces.Comment: Accepted to ACM SIGMETRICS 202

When Exploiting Individual User Preference Is Beneficial for Caching at Base Stations

Most of prior works optimize caching policies based on the following assumptions: 1) every user initiates request according to content popularity, 2) all users are with the same active level, and 3) users are uniformly located in the considered region. In practice, these assumptions are often not true. In this paper, we explore the benefit of optimizing caching policies for base stations by exploiting user preference considering the spatial locality and different active level of users. We obtain optimal caching policies, respectively minimizing the download delay averaged over all file requests and user locations in the network (namely network average delay), and minimizing the maximal weighted download delay averaged over the file requests and location of each user (namely maximal weighted user average delay), as well as minimizing the weighted sum of both. The analysis and simulation results show that exploiting heterogeneous user preference and active level can improve user fairness, and can also improve network performance when users are with spatial locality.Comment: Accepted by IEEE ICC 2018 Workshop on Information-Centric Edge Computing and Caching for Future Network

Building a flexible web caching system.

Web caching is a technology that has demonstrated to improve traffic on the Internet. To find out how to implement a Web caching architecture that assures improvements is not an easy task. The problem is more difficult when we are interested in deploying a distributed and cooperative Web caching system. We have found that some cooperative Web caching architectures could be unviable when changes on the network environment appear. This situation suggests that a cooperative Web caching system could get worst access to Web objects. However in this paper we present an architecture that combines the best of several Web caching configurations that we have previously analyzed. Our architecture gives basic ideas for implementing a cooperative Web caching system using groups of HTTP proxy servers which can improve access to remote Web objects regardless of the changes that might occur on the network environment (changes that could produce modifications in Web object validation policies and/or types of caching communication).Peer Reviewe