This paper introduces an analytical model for characterizing the instantaneous hit ratio and instantaneous average hit distance of a traditional least recently used (LRU) cache hierarchy. The analysis accounts for the use of two variants of the Time-to-Live (TTL) weak consistency mechanism. The first is the typical TTL scheme (TTL-T) used in the HTTP/1.1 protocol where expired objects are refreshed using conditional GET requests. The second is TTL immediate ejection (TTL-IE) where objects are ejected as soon as they expire. The analysis also accounts for two sharing protocols: Leave Copy Everywhere (LCE) and Promote Cached Objects (PCO). PCO is a new sharing protocol introduced in this paper that decreases the user's perceived latency and is robust under nonstationary access patterns.

This paper introduces a novel analytical model for estimating the cache hit ratio as a function of time. The cache may not reach the steady-state hit ratio when the number of Web objects, object popularity, and/or caching resources themselves are subject to change. Hence, the only way to quantify the hit ratio experienced by Web users is to calculate the instantaneous hit ratio. The proposed analysis considers a single Web cache with infinite or finite capacity. For a cache with finite capacity, two replacement policies are considered: Least Recently Used (LRU) and First-In-First-Out (FIFO). Based on the insights from the proposed analytical model, we propose a new replacement policy, called Frequency-Based-FIFO (FB-FIFO). The results show that FB-FIFO outperforms both LRU and FIFO, assuming that the number of Web objects is fixed. Assuming that new popular objects are generated periodically, the results show that FB-FIFO adapts faster than LRU and FIFO to the changes in the popularity of the cached objects when the cache capacity is large relative to the number of newly generated objects.

This paper presents a method for supporting wireless media streaming using a cache that is distributed across the mobile devices in the network. The performance of this scheme is compared to traditional institutional server (IS) caching on a network with a bandwidth constrained wireless backhaul. In addition to traditional caching hit ratio metrics, the paper studies how caching affects the call drop ratio due to limited backhaul bandwidth. These results indicate that the distributed caching method provides better service than IS caching as the number of users is increased. Finally, this paper also presents a scheme for conserving mobile device energy by limiting its participation in the caching scheme. Results show that most of the benefit of the distributed cache can be realized even with relatively few cache assists from each client.

In this paper, we consider the design of caching infrastructure to enhance the client-perceived performance of mobile wireless clients retrieving multimedia objects from the Internet. We consider three primary issues: location of the cache, size of the cache, and management policy for the cache. We consider both infrastructure-oriented caching at the Access Point (AP), as well as peer-assisted caching at the mobile clients. Simulation is used as the methodology for evaluation and comparison of caching strategies. The simulation results show that AP caching is generally more effective than client-side caching, that adequate performance is achievable with a mix of rather modest AP and client-side caches, and that Least Frequently Used (LFU) is the most effective cache replacement policy. Additional simulation experiments show that our results are robust across different request generation rates and client turnover rates.