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

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...

While algorithms for cooperative proxy caching have been widely studied, little is understood about cooperative-caching performance in the large-scale World Wide Web environment. This paper uses both trace-based analysis and analytic modelling to show the potential advantages and drawbacks of inter-proxy cooperation. With our traces, we evaluate quantitatively the performance-improvement potential of cooperation between 200 small-organization proxies within a university environment, and between two large-organization proxies handling 23,000 and 60,000 clients, respectively. With our model, we extend beyond these populations to project cooperative caching behavior in regions with millions of clients. Overall, we demonstrate that cooperative caching has performance benefits only within limited population bounds. We also use our model to examine the implications of future trends in Web-access behavior and traffic.

This paper presents the design of a new Web server architecture called the asymmetric multiprocess event-driven (AMPED) architecture, and evaluates the performance of an implementation of this architecture, the Flash Web server. The Flash Web server combines the high performance of single-process event-driven servers on cached workloads with the performance of multi-process and multithreaded servers on disk-bound workloads. Furthermore, the Flash Web server is easily portable since it achieves these results using facilities available in all modern operating systems. The performance of different Web server architectures is evaluated in the context of a single implementation in order to quantify the impact of a server's concurrency architecture on its performance. Furthermore, the performance of Flash is compared with two widely-used Web servers, Apache and Zeus. Results indicate that Flash can match or exceed the performance of existing Web servers by up to 50 % across a wide range of real workloads. We also present results that show the contribution of various optimizations embedded in Flash.

In this paper, we demonstrate the power of providing a common set of Operating System services to wide-area applications, including mechanisms for naming, persistent storage, remote process execution, resource management, authentication, and security. On a single machine, application developers can rely on the local operating system to provide these abstractions. In the wide area, however, application developers are forced to build these abstractions themselves or to do without. This ad-hoc approach often results in individual programmers implementing non-optimal solutions, wasting both programmer effort and system resources. To address these problems, we are building a system, WebOS, that provides basic operating systems services needed to build applications that are geographically distributed, highly available, incrementally scalable, and dynamically reconfigurable. Experience with a number of applications developed under WebOS indicates that it simplifies system development and improves resource utilization. In particular, we use WebOS to implement Rent-A-Server to provide dynamic replication of overloaded Web services across the wide area in response to client demands.

Chip multiprocessor (CMP) systems have made the on-chip caches a critical resource shared among co-scheduled threads. Limited off-chip bandwidth, increasing on-chip wire delay, destructive inter-thread interference, and diverse workload characteristics pose key design challenges. To address these challenge, we propose CMP cooperative caching (CC), a unified framework to efficiently organize and manage on-chip cache resources. By forming a globally managed, shared cache using cooperative private caches. CC can effectively support two important caching applications: (1) reduction of average memory access latency and (2) isolation of destructive inter-thread interference. CC reduces the average memory access latency by balancing between cache latency and capacity opti-mizations. Based private caches, CC naturally exploits their access latency benefits. To improve the effective cache capacity, CC forms a “shared ” cache using replication control and LRU-based global replacement policies. Via cooperation throttling, CC provides a spectrum of caching behaviors between the two extremes of private and shared caches, thus enabling dynamic adaptation to suit workload requirements. We show that CC can achieve a robust performance advantage over private and shared cache schemes across different processor, cache and memory configurations, and a wide selection of multithreaded and multiprogrammed

Traditional operating systems use magnetic disks as paging devices, even though the cost of a disk transfer measured in processor cycles continues to increase. In this paper we explore the use of remote main memory for paging. We describe the design, implementation and evaluation of a pager that uses main memory of remote workstations as a faster-than-disk paging device and provides reliability in case of single workstation failures. Our pager has been implemented as a block device driver linked to the DEC OSF/1 operating system, without any modifications to the kernel code. Using several test applications we measure the performance of remote memory paging over an Ethernet interconnection network and find it to be faster than traditional disk paging. We evaluate the performance of various reliability policies and prove their feasibility even over low bandwidth networks, like Ethernet. We conclude that the benefits of reliable remote memory paging in workstation clusters are significant...

The protection of operating system code from user code in most systems is based on the separation provided by anarchitecturally enforced user/kernel boundary. The boundary isolates an application from the kernel and from other applications. Only through the system call interface can applications interact with kernel services or one another. The system call interface has worked well in the past because the number of services

High-end computing is suffering a data deluge from experiments, simulations, and apparatus that creates overwhelming application dataset sizes. End-user workstations—despite more processing power than ever before—are ill-equipped to cope with such data demands due to insufficient secondary storage space and I/O rates. Meanwhile, a large portion of desktop storage is unused. We present the FreeLoader framework, which aggregates unused desktop storage space and I/O bandwidth into a shared cache/scratch space, for hosting large, immutable datasets and exploiting data access locality. Our experiments show that FreeLoader is an appealing low-cost solution to storing massive datasets, by delivering higher data access rates than traditional storage facilities. In particular, we present novel data striping techniques that allow FreeLoader to efficiently aggregate a workstation’s network communication bandwidth and local I/O bandwidth. In addition, the performance impact on the native workload of donor machines is small and can be effectively controlled.

This paper improves upon previous synthetic workload models and compares the performance of dynamic spatial equipartitioning (EQS) and the semi-static quantum-based FB-PWS processor allocation defined in [23], under synthetic workloads that have not previously been considered.