Randomized Competitive Algorithms for Generalized Caching

We consider online algorithms for the generalized caching problem. Here we are given a cache of size k and pages with arbitrary sizes and fetching costs. Given a request sequence of pages, the goal is to minimize the total cost of fetching the pages into the cache. We give an online algorithm with competitive ratio O(log2 k), which is the first algorithm for the problem with competitive ratio sublinear in k. We also give improved O(log k)-competitive algorithms for the special cases of the Bit Model and Fault model. In the Bit Model, the fetching cost is proportional to the size of the page and in the Fault model all fetching costs are uniform. Previously, an O(log2 k)-competitive algorithm due to Irani [14] was known for both of these models. Our algorithms are based on an extension of the primal-dual framework for online algorithms which was developed by Buchbinder and Naor [7]. We first generate an O(log k)-competitive fractional algorithm for the problem. This is done by using a...

• Type: Journal
• Year: 2012
• Where: SIAMCOMP
• Authors: Nikhil Bansal, Niv Buchbinder, Joseph Naor
• Keywords: Analysis Of Algorithms, Logical Reasoning, Lp Formulation, Problem Complexity, SIAMCOMP 2012