Chain replication is a new approach to coordinating clusters of fail-stop storage servers. The approach is intended for supporting large-scale storage services that exhibit high throughput and availability without sacrificing strong consistency guarantees. Besides outlining the chain replication protocols themselves, simulation experiments explore the performance characteristics of a prototype implementation. Throughput, availability, and several objectplacement strategies (including schemes based on distributed hash table routing) are discussed.

Replication is a well-known technique to improve the accessibility of Web sites. It generally offers reduced client latencies and increases a site’s availability. However, applying replication techniques is not trivial, and various Content Delivery Networks (CDNs) have been created to facilitate replication for digital content providers. The

Abstract — Traditional approaches to mirroring, caching, and content distribution have an underlying assumption that minimizing network hop count minimizes client latency. However, with uncongested backbones and potentially high-latency service times for dynamic content, such techniques are of limited effectiveness. In this paper, we propose an architecture in which dispatchers at an overloaded Internet Data Center (IDC) can redirect requests for dynamic content to a geographically remote IDC. Using a combination of analytical modeling and testbed experiments, we show that the delay savings of redirecting requests to a lightly loaded IDC can far outweigh the overhead in inter-IDC network latency. Consequently, client end-to-end delays are significantly reduced without requiring modifications to clients, servers, or DNS.

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Abstract—This paper proposes a novel framework for developing adaptive and scalable network services. In the proposed framework, a network service is implemented as a group of autonomous agents that interact in the network environment. Agents in the proposed framework are autonomous and capable of simple behaviors (e.g., replication, migration, and death). In this paper, an evolutionary adaptation mechanism is designed using genetic algorithms (GAs) for agents to evolve their behaviors and improve their fitness values (e.g., response time to a service request) to the environment. The proposed framework is evaluated through simulations, and the simulation results demonstrate the ability of autonomous agents to adapt to the network environment. The proposed framework may be suitable for disseminating network services in dynamic and large-scale networks where a large number of data and services need to be replicated, moved, and deleted in a decentralized manner. Index Terms—Adaptive and scalable network services, autonomous agents, evolutionary computation, self-organization, swarm intelligence. I.

Abstract: The proliferation of Content Delivery Networks (CDN) reveals that existing content networks are owned and operated by individual companies. As a consequence, closed delivery networks are evolved which do not cooperate with other CDNs and in practice, islands of CDNs are formed. Moreover, the logical separation between contents and services in this context results in two content networking domains. But present trends in content networks and content networking capabilities give rise to the interest in interconnecting content networks. Finding ways for distinct content networks to coordinate and cooperate with other content networks is necessary for better overall service. In addition to that, meeting the QoS requirements of users according to the negotiated Service Level Agreements between the user and the content network is a burning issue in this perspective. In this paper, we present an open, scalable and Service-Oriented Architecture based system to assist the creation of open Content and Service Delivery Networks (CSDN). These open CSDNs scale and support sharing of resources through peering with other CSDNs. 1.

We present the design and implementation of the data replication subsystem of OceanStore, a global-scale storage system. Our system automatically replicates data on or near the the client machines where the data is accessed, in order to improve locality, scalability, and availability. These replicas cooperate to share data and disseminate updates securely and eciently.

Abstract: Content Delivery Networks (CDNs) have evolved to overcome the inherent limitations of the Internet in terms of user perceived Quality of Service (QoS) when accessing Web content. A CDN replicates content from the origin server to cache servers, scattered over the globe, in order to deliver content to end-users in a reliable and timely manner from nearby optimal surrogates. Content distribution on the Internet has received considerable research attention. It combines development of high-end computing technologies with highperformance networking infrastructure and distributed replica management techniques. Therefore, our aim is to categorize and analyze the existing CDNs, and to explore the uniqueness, weaknesses, opportunities, and future directions in this field. In this paper, we provide a comprehensive taxonomy with a broad coverage of CDNs in terms of organizational structure, content distribution mechanisms, request redirection techniques, and performance measurement methodologies. We study the existing CDNs in terms of their infrastructure, request-routing mechanisms, content replication techniques, load balancing, and cache management. We also provide an indepth analysis and state-of-the-art survey of CDNs. Finally, we apply the taxonomy to map various CDNs. The mapping of the taxonomy to the CDNs helps in “gap ” analysis in the content networking domain. It also provides a means to identify the present and future development in this field and validates the applicability and

The problem of placing replicated servers with QoS constraints is considered. Each server site may consist of multiple server types with varying capacities and each site can be placed in any location among those belonging to a given set. Each client can de served by more than one locationsaslongastherequestround-tripdelaysatisfies predetermined upper bounds. Our main focus is to minimize the cost of using the servers and utilizing the link bandwidth, while serving requests according to their delay constraint. This is an NP-hard problem. A pseudopolynomial and a polynomial algorithm that provide guaranteed approximation factors with respect to the optimal for the problem at hand are presented. 1

Abstract—In this paper, we discuss and compare several policies to place replicas in tree networks, subject to server capacity and Quality-of-Service (QoS) constraints. The client requests are known beforehand, while the number and location of the servers are to be determined. The standard approach in the literature is to enforce that all requests of a client be served by the closest server in the tree. We introduce and study two new policies. In the first policy, all requests from a given client are still processed by the same server, but this server can be located anywhere in the path from the client to the root. In the second policy, the requests of a given client can be processed by multiple servers. One major contribution of this paper is to assess the impact of these new policies on the total replication cost. Another important goal is to assess the impact of server heterogeneity, both from a theoretical and a practical perspective. In this paper, we establish several new complexity results and provide several efficient polynomial heuristics for NP-complete instances of the problem. These heuristics are compared one to the other, and their absolute performance is assessed by comparison with the optimal solution provided by an integer linear program.