Wireless transmission of a single bit can require over 1000 times more energy than a single computation. It can therefore be beneficial to perform additional computation to reduce the number of bits transmitted. If the energy required to compress data is less than the energy required to send it, there is a net energy savings and an increase in battery life for portable computers. This article presents a study of the energy savings possible by losslessly compressing data prior to transmission. A variety of algorithms were measured on a StrongARM SA-110 processor. This work demonstrates that, with several typical compression algorithms, there is a actually a net energy increase when compression is applied before transmission. Reasons for this increase are explained and suggestions are made to avoid it. One such energy-aware suggestion is asymmetric compression , the use of one compression algorithm on the transmit side and a different algorithm for the receive path. By choosing the lowest-energy compressor and decompressor on the test platform, overall energy to send and receive data can be reduced by 11% compared with a well-chosen symmetric pair, or up to 57% over the default symmetric zlib scheme.

In digital hardware system design, the quality of the product is directly related to the number of meaningful design alternatives properly considered. Unfortunately, existing modeling methodologies and tools have properties which make them less than ...

As raw system performance continues to improve at exponential rates, the utility of many services is increasingly limited by availability rather than performance. A key approach to improving availability involves replicating the service across multiple, wide-area sites. However, replication introduces well-known trade-offs between service consistency and availability. Thus, this article explores the benefits of dynamically trading consistency for availability using a continuous consistency model . In this model, applications specify a maximum deviation from strong consistency on a per-replica basis. In this article, we: i) evaluate the availability of a prototype replication system running across the Internet as a function of consistency level, consistency protocol, and failure characteristics, ii) demonstrate that simple optimizations to existing consistency protocols result in significant availability improvements (more than an order of magnitude in some scenarios), iii) use our experience with these optimizations to prove tight upper bound on the availability of services, and iv) show that maximizing availability typically entails remaining as close to strong consistency as possible during times of good connectivity, resulting in a communication versus availability trade-off.

Despite decades of research in extensible operating system technology, extensions such as device drivers remain a significant cause of system failures. In Windows XP, for example, drivers account for 85% of recently reported failures.This article describes Nooks, a reliability subsystem that seeks to greatly enhance operating system (OS) reliability by isolating the OS from driver failures. The Nooks approach is practical: rather than guaranteeing complete fault tolerance through a new (and incompatible) OS or driver architecture, our goal is to prevent the vast majority of driver-caused crashes with little or no change to the existing driver and system code. Nooks isolates drivers within lightweight protection domains inside the kernel address space, where hardware and software prevent them from corrupting the kernel. Nooks also tracks a driver's use of kernel resources to facilitate automatic cleanup during recovery.To prove the viability of our approach, we implemented Nooks in the Linux operating system and used it to fault-isolate several device drivers. Our results show that Nooks offers a substantial increase in the reliability of operating systems, catching and quickly recovering from many faults that would otherwise crash the system. Under a wide range and number of fault conditions, we show that Nooks recovers automatically from 99% of the faults that otherwise cause Linux to crash.While Nooks was designed for drivers, our techniques generalize to other kernel extensions. We demonstrate this by isolating a kernel-mode file system and an in-kernel Internet service. Overall, because Nooks supports existing C-language extensions, runs on a commodity operating system and hardware, and enables automated recovery, it represents a substantial step beyond the specialized architectures and type-safe languages required by previous efforts directed at safe extensibility.

The LOCKSS project has developed and deployed in a world-wide test a peer-to-peer system for preserving access to journals and other archival information published on the Web. It consists of a large number of independent, low-cost, persistent Web caches that cooperate to detect and repair damage to their content by voting in “opinion polls.” Based on this experience, we present a design for and simulations of a novel protocol for voting in systems of this kind. It incorporates rate limitation and intrusion detection to ensure that even some very powerful adversaries attacking over many years have only a small probability of causing irrecoverable damage before being detected.

Pervasive computing provides an attractive vision for the future of computing. Computational power will be available everywhere. Mobile and stationary devices will dynamically connect and coordinate to seamlessly help people in accomplishing their tasks. For this vision to become a reality, developers must build applications that constantly adapt to a highly dynamic computing environment. To make the developers' task feasible, we present a system architecture for pervasive computing, called <i>one.world</i>. Our architecture provides an integrated and comprehensive framework for building pervasive applications. It includes services, such as discovery and migration, that help to build applications and directly simplify the task of coping with constant change. We describe our architecture and its programming model and reflect on our own and others' experiences with using it.

Gossip-based broadcast algorithms, a family of probabilistic broadcast algorithms, trade reliability guarantees against "scalability" properties. Scalability in this context has usually been expressed in terms of message throughput and delivery latency, but there has been little work on how to reduce the memory consumption for membership management and message buffering at large scale.This paper presents lightweight probabilistic broadcast ( lpbcast ), a novel gossip-based broadcast algorithm, which complements the inherent throughput scalability of traditional probabilistic broadcast algorithms with a scalable memory management technique. Our algorithm is completely decentralized and based only on local information: in particular, every process only knows a fixed subset of processes in the system and only buffers fixed "most suitable" subsets of messages. We analyze our broadcast algorithm stochastically and compare the analytical results both with simulations and concrete implementation measurements.

We present the design, implementation, and evaluation of run-time adaptation within the River dataflow programming environment. The goal of the River system is to provide adaptive mechanisms that allow database query-processing applications to cope with performance variations that are common in cluster platforms. We describe the system and its basic mechanisms, and carefully evaluate those mechanisms and their effectiveness. In our analysis, we answer four previously unanswered and important questions. Are the core run-time adaptive mechanisms effective, especially as compared to the ideal? What are the keys to making them work well? Can applications easily use these primitives? And finally, are there situations in which run-time adaptation is not sufficient? In performing our study, we utilize a three-pronged approach, comparing results from idealized models of system behavior, targeted simulations, and a prototype implementation. As well as providing insight on the positives and negatives of run-time adaptation both specifically in River and in a broader context, we also comment on the interplay of modeling, simulation, and implementation in system design.

COCA is a fault-tolerant and secure online certification authority that has been built and deployed both in a local area network and in the Internet. Extremely weak assumptions characterize environments in which COCA's protocols execute correctly: no assumption is made about execution speed and message delivery delays; channels are expected to exhibit only intermittent reliability; and with 3t+ 1 COCA servers up totmay be faulty or compromised. COCA is the first system to integrate a Byzantine quorum system (used to achieve availability) with proactive recovery (used to defend against mobile adversaries which attack, compromise, and control one replica for a limited period of time before moving on to another). In addition to tackling problems associated with combining fault-tolerance and security, new proactive recovery protocols had to be developed. Experimental results give a quantitative evaluation for the cost and effectiveness of the protocols.

This paper describes the miss classification table, a simple mechanism that enables the processor or memory controller to identify each cache miss as either a conflict miss or a capacity (non-conflict) miss. The miss classification table works by storing part of the tag of the most recently evicted line of a cache set. If the next miss to that cache set has a matching tag, it is identified as a conflict miss. This technique correctly identifies 88% of misses.Several applications of this information are demonstrated, including improvements to victim caching, next-line prefetching, cache exclusion, and a pseudo-associative cache. This paper also presents the adaptive miss buffer (AMB), which combines several of these techniques, targeting each miss with the most appropriate optimization, all within a single small miss buffer. The AMB's combination of techniques achieves 16% better performance than any single technique alone.