Emerging high-speed networks will allow machines to access remote data nearly as quickly as they can access local data. This trend motivates the use of cooperative caching: coordinating the file caches of many machines distributed on a LAN to form a more effective overall file cache. In this paper we examine four cooperative caching algorithms using a trace-driven simulation study. These simulations indicate that for the systems studied cooperative caching can halve the number of disk accesses, improving file system read response time by as much as 73%. Based on these simulations we conclude that cooperative caching can significantly improve file system read response time and that relatively simple cooperative caching algorithms are sufficient to realize most of the potential performance gain.

Advances in network and processor technology have greatly changed the communication and computational power of local-area workstation clusters. However, operating systems still treat workstation clusters as a collection of loosely-connected processors, where each workstation acts as an autonomous and independent agent. This operating system structure makes it difficult to exploit the characteristics of current clusters, such as low-latency communication, huge primary memories, and high-speed processors, in order to improve the performance of cluster applications. This paper describes the design and implementation of global memory management in a workstation cluster. Our objective is to use a single, unified, but distributed memory management algorithm at the lowest level of the operating system. By managing memory globally at this level, all system- and higher-level software, including VM, file systems, transaction systems, and user applications, can benefit from available cluster memory. We have implemented our algorithm in the OSF/1 operating system running on an ATM-connected cluster of DEC Alpha workstations. Our measurements show that on a suite of memory-intensive programs, our system improves performance by a factor of 1.5 to 3.5. We also show that our algorithm has a performance advantage over others that have been proposed in the past.

Modern high-end disk arrays often have several gigabytes of cache RAM. Unfortunately, most array caches use management policies which duplicate the same data blocks at both the client and array levels of the cache hierarchy: they are inclusive. Thus, the aggregate cache behaves as if it was only as big as the larger of the client and array caches, instead of as large as the sum of the two. Inclusiveness is wasteful: cache RAM is expensive. We explore the benefits of a simple scheme to achieve exclusive caching, in which a data block is cached at either a client or the disk array, but not both. Exclusiveness helps to create the effect of a single, large unified cache. We introduce a DEMOTE operation to transfer data ejected from the client to the array, and explore its effectiveness with simulation studies. We quantify the benefits and overheads of demotions across both synthetic and real-life workloads. The results show that we can obtain useful -- sometimes substantial -- speedups. During our investigations, we also developed some new cache-insertion algorithms that show promise for multi-client systems, and report on some of their properties.

In this paper, we examine the utility of exploiting idle workstations for parallel computation. We attempt to answer the following questions. First, given a workstation pool, for what fraction of time can we expect to find a cluster of k workstations available? This provides an estimate of the opportunity for parallel computation. Second, how stable is a cluster of free machines and how does the stability vary with the size of the cluster? This indicates how frequently a parallel computation might have to stop for adapting to changes in processor availability. Third, what is the distribution of workstation idle-times? This information is useful for selecting workstations to place computation on. Fourth, how much benefit can a user expect? To state this in concrete terms, if I have a pool of size S, how big a parallel machine should I expect to get for free by harvesting idle machines. Finally, how much benefit can be achieved on a real machine and how hard does a parallel programmer ha...

We present a very low-overhead decentralized algorithm for cooperative caching that provides performance comparable to that of existing centralized algorithms. Unlike existing algorithms that rely on centralized control of cache functions, our algorithm uses hints (i.e. inexact information) to allow clients to perform these functions in a decentralized fashion. This paper shows that a hint-based system performs as well as a more tightly coordinated system while requiring less overhead. Simulations show that the block access times of our system are as good as those of the existing tightly-coordinated algorithms, while reducing manager load by more than a factor of 15, block lookup traffic by nearly a factor of two-thirds, and replacement traffic by more than a factor of 5.

ing with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept, ACM Inc., 1515 Broadway, New York, NY 10036 USA, fax +1 (212) 869-0481, or permissions@acm.org. 2 \Delta M. J. Franklin et al. 1. INTRODUCTION 1.1 Client-Server Database System Architectures Advances in distributed computing and object-orientation have combined to bring about the development of a new class of database systems. These systems employ a client-server computing model to provide both responsiveness to users and support for complex, shared data in a distributed environment. Current relational DBMS products are based on a query-shipping approach in which most query processing is performed at servers; clients are primarily used to manage the user interface. In contrast, object-oriented database systems (OODBMS), whi...

This paper presents cooperative prefetching and caching --- the use of network-wide global resources (memories, CPUs, and disks) to support prefetching and caching in the presence of hints of future demands. Cooperative prefetching and caching effectively unites disk-latency reduction techniques from three lines of research: prefetching algorithms, cluster-wide memory management, and parallel I/O. When used together, these techniques greatly increase the power of prefetching relative to a conventional (nonglobal -memory) system. We have designed and implemented PGMS, a cooperative prefetching and caching system, under the Digital Unix operating system running on a 1.28 Gb/sec Myrinetconnected cluster of DEC Alpha workstations. Our measurements and analysis show that by using available global resources, cooperative prefetching can obtain significant speedups for I/O-bound programs. For example, for a graphics rendering application, our system achieves a speedup of 4.9 over a non-prefetc...

Mobile Computing is a new emerging computing paradigm of the future. Data Management in this paradigm poses many challenging problems to the database community. In this paper we identify these new challenges and plan to investigate their technical significance. New research problems include management of location dependent data, wireless data broadcasting, disconnection management and energy efficient data access. 1 Introduction The rapidly expanding technology of cellular communications, wireless LAN, wireless data networks, and satellite services will give mobile users capability of accessing information anywhere and anytime. In the near future, tens of millions of users will carry a portable (palmtop, laptop) computer (often called personal digital assistant (PDA) or personal communicator) with wireless connection to a worldwide information network. Coming years will most likely be the decade of mobile or nomadic computing. This vision poses new challenging problems to the databas...

Mobile computing is a new emerging computing paradigm posing many challenging data management problems. We identify these new challenges and investigate their technical significance. New research problems include management of location dependent data, frequent disconnections, structuring distributed algorithms for mobile hosts, wireless data broadcasting, and energy efficient data access. 1 Introduction The rapidly expanding technology of cellular communications, wireless LAN, and satellite services will make it possible for mobile users to access information anywhere and at anytime. In the near future, tens of millions of users will carry a portable computer often called a personal digital assistant or a personal communicator. Various possibilities are shown in Figure 1. Smaller units will run on AA batteries and may be diskless; larger units will run on Ni-Cd packs. These will be powerful laptop computers with large memories and powerful processors. Regardless of size, all mobile co...

This paper studies the “filter effects ” that occur in Web proxy caching hierarchies due to the presence of multiple levels of caches. That is, the presence of one level of cache changes the structural characteristics of the workload presented to the next level of cache, since only the requests that miss in one cache are forwarded to the next cache. Trace-driven simulations, with empirical and synthetic traces, are used to demonstrate the presence and magnitude of the filter effects in a multi-level Web proxy caching hierarchy. Experiments focus on the effects of cache size, cache replacement policy, Zipf slope, and the depth of the Web proxy caching hierarchy. Finally, the paper considers novel cache management techniques that can better exploit the changing workload characteristics across a multi-level Web proxy caching hierarchy. Trace-driven simulations are used to evaluate the performance of these approaches. The simulation results demonstrate that size-based partitioning and heterogeneous cache replacement policies each offer improvements in overall caching performance. The sensitivity of the results to the degree of