The recent introduction of Content Distribution Networks (CDNs) enhances the delivery of high quality multimedia content to end users. In a CDN architecture, the content is replicated to so-called surrogate servers, generally at the edge of the transport network, to improve the quality of service (QoS) of streaming multimedia delivery services. By using peer-to-peer (P2P) technologies, these edge servers can co-operate and provide a more scalable and robust service in a self-organizing CDN.In this paper, we propose a set of distributed replica placement algorithms (RPAs), based on an Integer Linear Programming (ILP) formulation of the centralized content placement problem. These algorithms further enhance the CDN performance by optimizing the network and server load, reducing network delays and avoiding congestion. Although the proposed algorithms are designed for and tested on different network topologies, we focus on robust ring based CDNs in this study. Content placement on such a network topology can be calculated analytically and can be used for comparison.

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Abstract. Effective network monitoring is vital for the growing number of control and management applications typically found in present-day networks. Increasing link speeds and the diversity of monitoring applications' needs have exposed severe limitations of existing monitoring techniques. As a response, the EU IST SCAMPI project designs and implements a scalable and programmable architecture for monitoring multi-gigabit networks. The SCAMPI architecture has an expressive programming interface, uses intelligent hardware, provides user policy management and resource control, and achieves scalability through parallelism. This paper addresses the problems with current high-speed network monitoring and presents the system architecture and components of the SCAMPI platform.

Abstract. Because of the ever-increasing popularity of the Internet, network monitoring becomes very mission critical to guarantee the operation of IP networks, e.g. to detect network failures and stop intrusion attempts. A majority of these monitoring tasks require only a small subset of all passing packets, which share some common properties such as identical header fields or similar patterns in their data. Nowadays, next to the increasing network speed, much of these tasks become very complex. In order to capture only the useful packets, these applications need to evaluate a large set of expressions. In this paper, we present a platform independent filter and pattern matcher optimization algorithm, which reduces the required number of evaluated expressions. The performance of the algorithm will be validated both analytically and by means of a high-speed monitoring system.