A new cache replacement scheme based on backpropagation neural networks
ACM SIGARCH Computer Architecture News
Performance of the KORA-2 cache replacement scheme
ACM SIGARCH Computer Architecture News
Web proxy caching: the devil is in the details
ACM SIGMETRICS Performance Evaluation Review
Replacement policies for a proxy cache
IEEE/ACM Transactions on Networking (TON)
Evaluating content management techniques for Web proxy caches
ACM SIGMETRICS Performance Evaluation Review
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
IEEE Transactions on Knowledge and Data Engineering
WWW '03 Proceedings of the 12th international conference on World Wide Web
A survey of Web cache replacement strategies
ACM Computing Surveys (CSUR)
Cost-aware WWW proxy caching algorithms
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
Web proxy cache replacement scheme based on back-propagation neural network
Journal of Systems and Software
A quantitative study of recency and frequency based web cache replacement strategies
Proceedings of the 11th communications and networking simulation symposium
Improvement of the neural network proxy cache replacement strategy
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Estimating neural networks-based algorithm for adaptive cachereplacement
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An adaptive neural network-based method for tile replacement in a web map cache
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
| Hi-index | 0.00 |
Proxy servers are designed with three goals: decrease bandwidth, lessen user perceived lag, and reduce loads on origin servers by caching copies of web objects. To achieve these goals an efficient cache replacement technique should be utilized. Squid is a widely used proxy cache software. Squid's default cache replacement strategy is Least Recently Used. While this is a simple approach, it does not necessarily achieve the targeted goals. We use a different approach to address the cache replacement problem by training neural networks to make cache replacement decisions. In this paper we present the many improvements to our Neural Network Proxy Cache Replacement Strategy. We focus on the training of the neural networks and demonstrate the results for the effect of the number of hidden nodes, input node, the sliding window length and the learning rate on the neural network.