Abstract
Content caching at intermediate nodes is an effective way to optimize the operations of Computer networks, so that future requests can be served without going back to the origin of the content. Several caching techniques have been proposed in literature, including techniques that require major changes to the Internet architecture. In this work, we present a low complexity, distributed, and online caching algorithm based on content popularity. Our algorithm performs en-route caching using a simple cost-reward comparison. Therefore, it can be integrated with the current TCP/IP model. We use the concept of competitive ratio to measure the performance of any online caching algorithm, in terms of traffic savings, with respect to the performance of the optimal offline algorithm that has a complete knowledge of the future. We show that under our settings, no online algorithm can achieve a better competitive ratio than $\Omega (\log n)$ , where n is the number of nodes in the network. Furthermore, we show that under realistic scenarios, our algorithm has an asymptotically optimal competitive ratio in terms of the number of nodes in the network. We also study several extensions to the basic algorithm and show their effectiveness through extensive simulations.
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