There is an increasing need to quickly and efficiently learn network distances, in terms of metrics such as latency or bandwidth, between Internet hosts. For example, Internet content providers often place data and server mirrors throughout the Internet to improve access latency for clients, and it is necessary to direct clients to the closest mirrors based on some distance metric in order to realize the benefit of mirrors. We suggest a scalable Internet-wide architecture, called IDMaps, which measures and disseminates distance information on the global Internet. Higher-level services can collect such distance information to build a virtual distance map of the Internet and estimate the distance between any pair of IP addresses. We present our solutions to the measurement server placement and distance map construction problems in IDMaps. We show that IDMaps can indeed provide useful distance estimations to applications such as closest-mirror selection. 1 Keywords: network service, distributed algorithms, scalability, modeling. 1

Web content providers and content distribution network (CDN) operators often set up mirrors of popular content to improve performance. Due to the scale and decentralized administration of the Internet, companies have a limited number of sites (relative to the size of the Internet) where they can place mirrors. We formalize the mirror placement problem as a case of constrained mirror placement, where mirrors can only be placed on a preselected set of candidates. We study performance improvement in terms of client round-trip time (RTT) and server load when clients are clustered by the autonomous systems (AS) in which they reside. Our results show that, regardless of the mirror placement algorithm used, for only a surprisingly small range of values is increasing the number of mirror sites (under the constraint) effective in reducing client to server RTT and server load. In this range, we show that greedy placement performs the best.

To increase a client's perceived throughput while transferring large multimedia files, a parallel-access approach can be used to simultaneously transfer different pieces of a file from different mirrors. Previously proposed approaches, however, either employ very aggressive implementations with poor scalability or suffer from deployment difficulties on the current Internet. Using trace-driven and real Internet experiments, we show the effect of poor scalability and performance degradation for some of the previous parallel-access implementations. In this paper, we propose a hybrid scheme that (1) minimizes the added load on all mirrors while (2) maximizing the client-perceived throughput. Our scheme uses informed mirror selection based on round-trip time (RTT) measurements as well as dynamic monitoring. While using less than 10% of the available mirrors, we show a decrease in transfer time by more than 85% over traditional single-server transfers and 35% over other parallel-access implementations.

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Internet Service Providers and infrastructural companies often employ mirrors of popular content to decrease client download time and server load. Due to the immense scale of the Internet and decentralized administration of the networks, companies have a limited number of sites (relative to the size of the Internet) where they can place mirrors. Mirrors of popular content are usually replicated on every site to maximize reachability to clients. In this paper, we study the performance improvements as the number of mirrors increases under different placement algorithms subject to the constraint that mirrors can be placed only at certain locations. Although there are extensive theoretical studies on center placement and, more recently, analytical and empirical studies on web cache placement, we are not aware of any published literature on mirror placement especially in the case of constrained mirror placement. Our results show that increasing the number of mirror sites under the constraint is effective in reducing client download time and reducing server load only for a surprisingly small range of values regardless of the mirror placement algorithm.

Current web server farms have simple resource allocation models. One such model used is to dedicate a server or a group of servers for each client. Another model partitions physical servers into logical servers and assigns one to each client. However, both these approaches prevent resource sharing and reduce the ability to handle peak loads except at the cost of having to reserve resources that will lie idle most of the time. Yet another model allows clients to be served via multiple servers by using load-balancing techniques to distribute incoming requests. This implies that every client's application must reside and remain active on multiple servers. For complex applications, this approach uses up significant server resources.

Abstract. Modern Web sites provide multiple services that are deployed through complex technologies. The importance and the economic impact of consumeroriented Web sites introduce significant requirements in terms of performance and reliability. This chapter presents some methods for the design of novel Web sites and for the improvement of existing systems that must satisfy some performance requirements even in the case of unpredictable load variations. The chapter is concluded with a case study that describes the application of the proposed methods to a typical consumeroriented Web site.