Exact Analysis of TTL Cache Networks: The Case of Caching Policies driven by Stopping Times

TTL caching models have recently regained significant research interest, largely due to their ability to fit popular caching policies such as LRU. This paper advances the state-of-the-art analysis of TTL-based cache networks by developing two exact methods with orthogonal generality and computational complexity. The first method generalizes existing results for line networks under renewal requests to the broad class of caching policies whereby evictions are driven by stopping times. The obtained results are further generalized, using the second method, to feedforward networks with Markov arrival processes (MAP) requests. MAPs are particularly suitable for non-line networks because they are closed not only under superposition and splitting, as known, but also under input-output caching operations as proven herein for phase-type TTL distributions. The crucial benefit of the two closure properties is that they jointly enable the first exact analysis of feedforward networks of TTL caches in great generality

Soft Cache Hits and the Impact of Alternative Content Recommendations on Mobile Edge Caching

Caching popular content at the edge of future mobile networks has been widely considered in order to alleviate the impact of the data tsunami on both the access and backhaul networks. A number of interesting techniques have been proposed, including femto-caching and "delayed" or opportunistic cache access. Nevertheless, the majority of these approaches suffer from the rather limited storage capacity of the edge caches, compared to the tremendous and rapidly increasing size of the Internet content catalog. We propose to depart from the assumption of hard cache misses, common in most existing works, and consider "soft" cache misses, where if the original content is not available, an alternative content that is locally cached can be recommended. Given that Internet content consumption is increasingly entertainment-oriented, we believe that a related content could often lead to complete or at least partial user satisfaction, without the need to retrieve the original content over expensive links. In this paper, we formulate the problem of optimal edge caching with soft cache hits, in the context of delayed access, and analyze the expected gains. We then show using synthetic and real datasets of related video contents that promising caching gains could be achieved in practice

A unified approach to the performance analysis of caching systems

We propose a unified methodology to analyse the performance of caches (both isolated and interconnected), by extending and generalizing a decoupling technique originally known as Che's approximation, which provides very accurate results at low computational cost. We consider several caching policies, taking into account the effects of temporal locality. In the case of interconnected caches, our approach allows us to do better than the Poisson approximation commonly adopted in prior work. Our results, validated against simulations and trace-driven experiments, provide interesting insights into the performance of caching systems.Comment: in ACM TOMPECS 20016. Preliminary version published at IEEE Infocom 201

Analytical Investigation of On-Path Caching Performance in Information Centric Networks

Information Centric Networking (ICN) architectures are proposed as a solution to address the shift from host-centric model toward an information centric model in the Internet. In these architectures, routing nodes have caching functionality that can influence the network traffic and communication quality since the data items can be sent from nodes far closer to the requesting users. Therefore, realizing effective caching networks becomes important to grasp the cache characteristics of each node and to manage system resources, taking into account networking metrics (e.g., higher hit ratio) as well as user’s metrics (e.g. shorter delay). This thesis studies the methodologies for improving the performance of cache management in ICNs. As individual sub-problems, this thesis investigates the LRU-2 and 2-LRU algorithms, geographical locality in distribution of users’ requests and efficient caching in ICNs. As the first contribution of this thesis, a mathematical model to approximate the behaviour of the LRU-2 algorithm is proposed. Then, 2-LRU and LRU-2 cache replacement algorithms are analyzed. The 2-LRU caching strategy has been shown to outperform LRU. The main idea behind 2-LRU and LRU-2 is considering both frequency (i.e. metric used in LFU) and recency (i.e. metric used in LRU) together for cache replacement process. The simulation as well as numeric results show that the proposed LRU-2 model precisely approximates the miss rate for LRU-2 algorithm. Next, the influence of geographical locality in users’ requests on the performance of network of caches is investigated. Geographically localized and global request patterns have both been observed to possess Zipf (i.e. a power-law distribution in which few data items have high request frequencies while most of data items have low request frequencies) properties, although the local distributions are poorly correlated with the global distribution. This suggests that several independent Zipf distributions combine to form an emergent Zipf distribution in real client request scenarios. An algorithm is proposed that can generate realistic synthetic traffic to regional caches that possesses Zipf properties as well as produces a global Zipf distribution. The simulation results show that the caching performance could have different behaviour based on what distribution the users’ requests follow. Finally, the efficiency of cache replacement and replication algorithms in ICNs are studied since ICN literature still lacks an empirical and analytical deep understanding of benefits brought by in-network caching. An analytical model is proposed that optimally distributes a total cache budget among the nodes of ICN networks for LRU cache replacement and LCE cache replication algorithms. The results will show how much user-centric and system-centric benefits could be gained through the in-network caching compared to the benefits obtained through caching facilities provided only at the edge of the network

"Running" ModelGraft to evaluate internet-scale ICN

<p>The analysis of Internet-scale Information-centric networks, and of cache networks in general, poses scalability issues like CPU and memory requirements, which can not be easily targeted by neither state-of-the-art analytical models nor well designed event-driven simulators. This demo focuses on showcasing performance of our new hybrid methodology, named ModelGraft, which we release as a simulation engine of the open-source ccnSim simulator: being able to seamlessly use a classic event-driven or the novel hybrid engine dramatically improves the flexibility and scalability of current simulative and analytical tools. In particular, ModelGraft combines elements and intuitions of stochastic analysis into a MonteCarlo simulative approach, offering a reduction of over two orders of magnitude in both CPU time and memory occupancy, with respect to the purely event-driven version of ccnSim, notably one of the most scalable simulators for Information-centric networks. This demo consists in gamifying the aforementioned comparison: we represent ModelGraft vs event-driven simulation as two athletes running a 100-meter competition using sprite-based animations. Differences between the two approaches in terms of CPU time, memory occupancy, and results accuracy, are highlighted in the score-board.</p