Parallel downloading retrieves different pieces of a file from different servers simultaneously and so is expected to greatly shorten file fetch times. A key requirement is that the different servers must hold the same file. We have already proposed a proxy system that can ensure file freshness and concordance. In this paper, we combine parallel downloading with the proxy server technology in order to download a file quickly and ensure that it is the latest version. Our previous paper on parallel downloading took neither the downloading order of file fragments nor the buffer space requirements into account; this paper corrects those omissions. In order to provide the user with the required file in correct order as a byte stream, the proxy server must reorder the pieces fetched from multiple servers and shuffle in the delayed blocks as soon as possible. Thus, "substitution download" is newly introduced, which requests delayed blocks from other servers to complete downloading earlier. Experiments on substitution download across the Internet clarify the tradeoff between the buffering time and the redundant traffic generated by duplicate requests to multiple servers. As a result, the pseudo-optimum balance is discovered and our method is shown both not to increase downloading time and to limit the buffer space. This network software can be applied to download files smoothly absorbing the difference in performance characteristics among heterogeneous networks.

This paper considers the reliable multicast transport protocols used in hybrid networks that include wired and wireless networks and transparent proxy servers. We present four analytic performance models of two extreme reliable multicast transport protocols, sender-initiated and receiver-initiated, and supported and unsupported by transparent proxy servers are considered in each reliable multicast protocol. We analyze the throughputs of these four different models mathematically. Numerical results show that transparent proxy servers give good effects to overall performance. Furthermore, the receiver-initiated reliable multicast supported by transparent proxy servers gives better performances of total throughput than sender-initiated reliable multicast supported by transparent proxy servers. We provide efficiency criterion of the optimal number of transparent proxy servers for each protocol under varying wireless loss probabilities. Numerical results are verified by simulations.

We propose a novel routing algorithm for reverse proxy servers, called load balancing content address hashing (LB-CAH), and evaluate the performance of the proposed routing algorithm compared with that of the content address hashing (CAH) and the hash and slide (HAS) routing algorithms. The proposed LB-CAH routing algorithm calculates the popularity of pages in the load balancer using an LFU caching technique and periodically makes a popularity list. Using this popularity list, the proposed routing algorithm selects a reverse proxy server as follows. When the requested page appears in the popularity list, the request is routed according to the round robin method; otherwise, it is routed according to the content address hashing method. We evaluate and compare the LB-CAH, CAH and HAS routing algorithms by simulation experiments from the viewpoints of load balancing, consumed cache space and cache hit rate. Simulation experiments show that the proposed LB-CAH routing algorithm achieves almost the same degree of load balancing as the HAS algorithm and the same cache hit rate as the CAH algorithm for reverse proxy servers in various web site environments.

Mining traversal patterns on the Internet is one of critical issues for exploring the user access behaviors. In this paper, we propose a new data mining scheme for mining frequent trip traversal patterns on the Internet. First, we define a trip traversal as a historical contiguous sequence of web sites or web pages, which were surfed or visited on an information-providing system by one user. Next, we derive all of the maximal trip traversals by analyzing and filtering these collected trip traversals. For mining the large trip traversals from the maximal trip traversals, we present a data mining scheme integrated with the schemes presented in. Here, the extracted large trip traversals can be thought of as the realistic frequent browsed behaviors for most of users either on a web site or on an information-providing system, such as a proxy server. Finally, we implement and design a data mining system to explore the large trip traversal patterns in order to capture user access patterns to some proxy server.