9352626
Implications of I/O for Gang Scheduled Workloads
The job workloads of general-purpose multiprocessors usually include both compute-bound parallel jobs, which often require gang scheduling, as well as I/O-bound jobs, which require high CPU priority for the individual gang members of the job in order to achieve interactive response times. Our results indicate that an effective interactive multiprocessor scheduler must be flexible and tailor the priority, time quantum, and extent of gang scheduling to the individual needs of each job.
7375714
Space-time scheduling of instruction-level parallelism on a raw machine
Increasing demand for both greater parallelism and faster clocks dictate that future generation architectures will need to decentralize their resources and eliminate primitives that require single cycle global communication. A Raw microprocessor distributes all of its resources, including instruction streams, register files, memory ports, and ALUs, over a pipelined two-dimensional mesh interconnect, and exposes them fully to the compiler. Because communication in Raw machines is distributed, compiling for instruction-level parallelism (ILP) requires both spatial instruction partitioning as well as traditional temporal instruction scheduling. In addition, the compiler must explicitly manage all communication through the interconnect, including the global synchronization required at branch points. This paper describes RAWCC, the compiler we have developed for compiling general-purpose sequential programs to the distributed Raw architecture. We present performance results that demonstrate that although Raw machines provide no mechanisms for global communication the Raw compiler can schedule to achieve speedups that scale with the number of available functional units.
3800033
Exponential index: a parameterized distributed indexing scheme for data on air
Wireless data broadcast has received a lot of attention from industries and academia in recent years. Access efficiency and energy conservation are two critical performance concerns in a wireless data broadcast environment. To improve the efficiency of energy consumption on mobile devices, traditional disk-based indexing techniques such as B$^+$-tree have been extended to index broadcast data on a wireless channel. However, existing designs are mostly based on centralized tree structures. Most of these indexing techniques are not flexible in the sense that the trade-off between access efficiency and energy conservation is not adjustable based on application specific requirements. We propose in this paper a novel parameterized index, called the exponential index, which can be tuned to optimize the access latency with the tuning time bounded by a given limit, and vice versa. The proposed index is very efficient because it facilitates replication naturally by sharing links in multiple search trees and thus minimizes storage overhead. Experimental results show that the exponential index not only achieves better performance than the state-of-the-art indexes but also enables great flexibility in trade-offs between access latency and tuning time.
6881391
Evolving Complex Robot Behaviors
Building robots is a tough job because the designer has to predict the interactions between the robot and the environment as well as to deal with them. One solution to such diculties in designing robots is to adopt learning methods. The evolution-based approach is a special method of machine learning and it has been advocated to automate the design of robots. Yet, the tasks achieved so far are fairly simple. In this work, we ®rst analyze the diculties of applying evolutionary approaches to synthesize robot controllers for complicated tasks, and then suggest an approach to resolve them. Instead of directly evolving a monolithic control system, we propose to decompose the overall task to ®t in the behavior-based control architecture, and then to evolve the separate behavior modules and arbitrators using an evolutionary approach. Consequently, the job of de®ning ®tness functions becomes more straightforward and the tasks easier to achieve. To assess the performance of the developed approach, we evolve a control system to achieve an application task of box-pushing as an example. Experimental results show the promise and eciency of the presented approach. Ó 1999 Elsevier Science Inc. All rights reserved.
14424972
A study on channel allocation for data dissemination in mobile computing environments
This paper studies channel allocation methods for data dissemination through broadcast and on‐demand channels. Analytical models and cost formulae for exclusive broadcast channels and exclusive on‐demand channels are provided. Based on the models, we further derive cost models for dynamic channel allocation methods and propose a channel adaptation algorithm for optimizing system performance. The channel adaptation algorithm can be executed in O(n) time, where n is the number of data items in the database. Performance evaluation shows that the channel allocation algorithm produces optimal channel allocation which significantly improves the system performance under various parameter settings.
12587628
Proactive caching for spatial queries in mobile environments
Semantic caching enables mobile clients to answer spatial queries locally by storing the query descriptions together with the results. However, it supports only a limited number of query types, and sharing results among these types is difficult. To address these issues, we propose a proactive caching model which caches the result objects as well as the index that supports these objects as the results. The cached index enables the objects to be reused for all common types of queries. We also propose an adaptive scheme to cache such an index, which further optimizes the query response time for the best user experience. Simulation results show that proactive caching achieves a significant performance gain over page caching and semantic caching in mobile environments where wireless bandwidth and battery are precious resources.
21907802
An Architecture for a Next-Generation Internet Based on Web Services and Utility Computing
We present an architecture for a next-generation Internet based on Web services and utility computing. This architecture would be realised as a series of open but interacting markets. We present a scenario whereby these markets could develop, driven by economic forces and market opportunities, exploiting technologies developed in e-Science and grid computing. We argue that, if properly realised such an architecture would provide a safer and more cost-effective way of supporting the Internet than the current infrastructure and would provide many opportunities for radical developments, affecting and unifying many areas of academia, business and society