As part of Time Warner's interactive TV trial in Orlando, Florida, we have implemented mechanisms for the construction of highly available and scalable system services and applications. Our mechanisms rely on an underlying distributed objects architecture, similar to Spring[1]. We have extended a standard name service interface to provide selectors for choosing among service replicas and auditing to allow the automatic detection and removal of unresponsive objects from the name space. In addition, our system supports resource recovery, by letting servers detect client failures, and automated restart of failed services. Our experience has been that these mechanisms greatly simplify the development of services that are both highly available and scalable. The system was built in less than 15 months, is currently in a small number of homes, and will support the trial's 4,000 users later this year. 1 Introduction Interactive TV (ITV) is a new application domain for distributed systems. Alt...

Spring provides a uniform name service for an open ended collection of object types-in principle, any object, of any type, can be bound to any name. The name service implements authentication and access control to protect itself, and provides these same functions in an integrated way for the convenience of clients and the object managers that implement the various objects in the system. An object manager can delegate these functions to the name service, or implement its own policies. The name service is implemented as a collection of name servers which are generally autonomous and separate from each other and also from object managers. The architecture allows trusted and untrusted name servers and object managers to participate in providing naming and in publishing objects. Authentication is done at appropriate times to establish trust. These trust relationships are encoded in capability-like authenticated objects which are reused to avoid authentication complexity and overhead after trust is established.>

In this paper we describe an architecture for extensible file systems. The architecture enables the extension of file system functionality by composing (or stacking) new file systems on top of existing file systems. A file system that is stacked on top of an existing file system can access the existing file system's files via a well-defined naming interface and can share the same underlying file data in a coherent manner. We describe extending file systems in the context of the Spring operating system. Composing file systems in Spring is facilitated by basic Spring features such as its virtual memory architecture, its strongly-typed well-defined interfaces, its location-independent object invocation mechanism, and its flexible naming architecture. File systems in Spring can reside in the kernel, in user-mode, or on remote machines, and composing them can be done in a very flexible manner.

The Sprite network operating system uses large main-memory disk block caches to achieve high performance in its file system. It provides non-write-through file caching on both client and server machines. A simple cache consistency mechanism permits files to be shared by multiple clients without danger of stale data. In order to allow the file cache to occupy as much memory as possible, the file system of each machine negotiates with the virtual memory system over physical memory usage and changes the size of the file cache dynamically. Benchmark programs indicate that client caches allow diskless Sprite workstations to perform within O-12 percent of workstations with disks. In addition, client caching reduces server loading by 50 percent and network traffic by 90 percent.

This paper compares the performance of executing compiled Prolog code on two different architectures under development at U. C. Berkeley. The first is the PLM, a special-purpose CISC architecture intended as a coprocessor for a host machine. The second is SPUR, a general-purpose RISC architecture that supports tagged data. Fourteen standard benchmark programs were run on both the PLM and SPUR simulators. The compiled code for SPUR was obtained by simple macro-expansion of PLM code generated by the PLM Prolog compiler. The two implementations are compared with regard to static and dynamic program size, execution speed, and memory system performance. On average, the macrocoded SPUR implementation has a static code size 14 times larger than the PLM, executes 16 times more instructions, yet requires only 2.3 times the number of machine cycles (or has the performance of 0.43 PLMs). When memory system performance is taken into account, SPUR is equivalent to 0.29 PLMs. Optimizations of the macro-expanded code and minor architectural changes to SPUR would increase this ratio to 0.53, or 0.60 for the largest benchmarks. Thus a tagged RISC architecture can execute Prolog at least half as fast as a special-purpose CISC architecture for Prolog.

This paper describes a simple distributed mechanism for caching files among a networked collection of workstations. We have implemented it as part of Sprite, a new operating system being implemented at the University of California at Berkeley. A preliminary version of Sprite is currently running on Sun-2 and Sun-3 workstations, which have about 1-2 MIPS processing power and 4-16 Mbytes of main memory. The system is targeted for workstations like these and newer models likely to become available in the near future; we expect the future machines to have at least five to ten times the processing power and main memory of our current machines, as well as small degrees of multiprocessing. We hope that Sprite will be suitable for networks of up to a few hundred of these workstations. Because of economic and environmental factors, most workstations will not have local disks; instead, large fast disks will be concentrated on a few server machines.