The Cooperative File System (CFS) is a new peer-to-peer readonly storage system that provides provable guarantees for the efficiency, robustness, and load-balance of file storage and retrieval. CFS does this with a completely decentralized architecture that can scale to large systems. CFS servers provide a distributed hash table (DHash) for block storage. CFS clients interpret DHash blocks as a file system. DHash distributes and caches blocks at a fine granularity to achieve load balance, uses replication for robustness, and decreases latency with server selection. DHash finds blocks using the Chord location protocol, which operates in time logarithmic in the number of servers. CFS is implemented using the SFS file system toolkit and runs on Linux, OpenBSD, and FreeBSD. Experience on a globally deployed prototype shows that CFS delivers data to clients as fast as FTP. Controlled tests show that CFS is scalable: with 4,096 servers, looking up a block of data involves contacting only seven servers. The tests also demonstrate nearly perfect robustness and unimpaired performance even when as many as half the servers fail.

We describe a family of caching protocols for distrib-uted networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, where delays caused by hot spots can be severe, and where it is not feasible for every server to have complete information about the current state of the entire network. The protocols are easy to implement using existing network protocols such as TCP/IP, and require very little overhead. The protocols work with local control, make efficient use of existing resources, and scale gracefully as the network grows. Our caching protocols are based on a special kind of hashing that we call consistent hashing. Roughly speaking, a consistent hash function is one which changes minimally as the range of the function changes. Through the development of good consistent hash functions, we are able to develop caching protocols which do not require users to have a current or even consistent view of the network. We believe that consistent hash functions may eventually prove to be useful in other applications such as distributed name servers and/or quorum systems. 1

Overcast is an application-level multicasting system that can be incrementally deployed using today's Internet infrastructure. These properties stem from Overcast's implementation as an overlay network. An overlay network consists of a collection of nodes placed at strategic locations in an existing network fabric. These nodes implement a network abstraction on top of the network provided by the underlying substrate network.

Active networks are a novel approach to network architecture in which the switches of the network perform customized computations on the messages flowing through them. This approach is motivated by both lead user applications, which perform user-driven computation at nodes within the network today, and the emergence of mobile code technologies that make dynamic network service innovation attainable. In this paper, we discuss two approaches to the realization of active networks and provide a snapshot of the current research issues and activities. Introduction – What Are Active Networks? In an active network, the routers or switches of the network perform customized computations on the messages flowing through them. For example, a user of an active network could send a “trace ” program to each router and arrange for the program to be executed when their packets are processed. Figure 1 illustrates how the routers of an IP

This paper describes the motivation, architecture and performance of SPIN, an extensible operating system. SPIN provides an extension infrastructure, together with a core set of extensible services, that allow applications to safely change the operating system's interface and implementation. Extensions allow an application to specialize the underlying operating system in order to achieve a particular level of performance and functionality. SPIN uses language and link-time mechanisms to inexpensively export ne-grained interfaces to operating system services. Extensions are written in a type safe language, and are dynamically linked into the operating system kernel. This approach o ers extensions rapid access to system services, while protecting the operating system code executing within the kernel address space. SPIN and its extensions are written in Modula-3 and run on DEC Alpha workstations. 1

General-purpose operating systems provide inadequate support for resource management in large-scale servers. Applications lack sufficient control over scheduling and management of machine resources, which makes it difficult to enforce priority policies, and to provide robust and controlled service. There is a fundamental mismatch between the original design assumptions underlying the resource management mechanisms of current general-purpose operating systems, and the behavior of modern server applications. In particular, the operating system's notions of protection domain and resource principal coincide in the process abstraction. This coincidence prevents a process that manages large numbers of network connections, for example, from properly allocating system resources among those connections. We propose and evaluate a new operating system abstraction called a resource container, which separates the notion of a protection domain from that of a resource principal. Resource containers ...

Active networks allow their users to inject customized programs into the nodes of the network. An extreme case, in which we are most interested, replaces packets with "capsules" -- program fragments that are executed at each network router/switch they traverse. Active architectures permit a massive increase in the sophistication of the computation that is performed within the network. They will enable new applications, especially those based on application-specific multicast, information fusion, and other services that leverage network-based computation and storage. Furthermore, they will accelerate the pace of innovation by decoupling network services from the underlying hardware and allowing new services to be loaded into the infrastructure on demand. In this paper, we describe our vision of an active network architecture, outline our approach to its design, and survey the technologies that can be brought to bear on its implementation. We propose that the research community mount a j...

We propose a new design for highly concurrent Internet services, whichwe call the staged event-driven architecture (SEDA). SEDA is intended

This paper has benefited from the detailed and perceptive comments of our reviewers, especially our shepherd Hank Levy. We thank Randy Katz and Eric Anderson for their detailed readings of early drafts of this paper, and David Culler for his ideas on TACC's potential as a model for cluster programming. Ken Lutz and Eric Fraser configured and administered the test network on which the TranSend scaling experiments were performed. Cliff Frost of the UC Berkeley Data Communications and Networks Services group allowed us to collect traces on the Berkeley dialup IP network and has worked with us to deploy and promote TranSend within Berkeley. Undergraduate researchers Anthony Polito, Benjamin Ling, and Andrew Huang implemented various parts of TranSend's user profile database and user interface. Ian Goldberg and David Wagner helped us debug TranSend, especially through their implementation of the rewebber

We consider cluster-based network servers in which a front-end directs incoming requests to one of a number of back-ends. Specifically, we consider content-based request distribution: the front-end uses the content requested, in addition to information about the load on the back-end nodes, to choose which back-end will handle this request. Content-based request distribution can improve locality in the back-ends' main memory caches, increase secondary storage scalability by partitioning the server's database, and provide the ability to employ back-end nodes that are specialized for certain types of requests. As a specific policy for content-based request distribution, we introduce a simple, practical strategy for locality-aware request distribution (LARD). With LARD, the front-end distributes incoming requests in a manner that achieves high locality in the back-ends' main memory caches as well as load balancing. Locality is increased by dynamically subdividing the server's working set o...