10614369
PICO: A Middleware Framework for Pervasive Computing
The pervasive information community organization is a framework for creating mission-oriented dynamic communities of autonomous software entities that perform tasks for users and devices. PICO's telemedicine example scenario demonstrates its potential as a simple, unique, and versatile middleware framework for pervasive computing.
6061688
Mobile Agent Connection Establishment and Management (CEMA)—Message Exchange for Pervasive Computing Environments
Pervasive computing is an emerging technology that offers new possibilities to distributed computing and computer networking; it employs a wide variety of smart, ubiquitous devices throughout an individual's working and living environment. Mobile agents are software entities that can migrate between servers (mobile agent environments) of the network accomplishing various tasks on the behalf of their owners. The objective of this paper is to describe a test and prototyping environment for experimenting with mobile agents in pervasive environments. A prototype environment for a novel, proactive infrastructure is described for mobile agent assisted pervasive computing. In addition, a new message passing algorithm is provided for mobile agent connection establishment and management (CEMA). Simulation results show the performance of the proposed approach.
13161865
On the Reliability and Additional Overhead of Reliable On-Demand Multicast Routing Protocol for Mobile Ad Hoc Networks
Multicasting is the transmission of datagrams to a group of hosts identified by a single destination address, providing simple and efficient communication for group-oriented applications. Many applications currently envisioned for mobile ad hoc networks require multicasting. Several multicasting protocols have been proposed for mobile ad hoc networks, one of the most popular being the On Demand Multicast Routing Protocol. This paper provides a review of ad hoc multicast routing protocols, focusing on MAODV, ODMRP and a variation of ODMRP called reliable-ODMRP. NS-2 simulations are used to compare the reliability and overhead of MAODV, ODMRP, and R-ODMRP.
29185449
Performance Analysis and Scalability of the ThreadmanTM Thread Manager
15495414
A tool based methodology for development of automatically scalable and reusable parallel code
Program performance may be improved by efficiently programming some key sections of the software. We present a methodology for converting selected portions of source code into automatically scalable multithreaded routines, without forcing programmers to concentrate on parallel programming issues. These developed routines can be reused across various projects, operating systems and system architectures. To support this methodology two separate but tightly coupled tools have been developed -PARSA/sup (TM)/ software development environment (SDE) and the ThreadMan/sup (TM)/ thread manager. The SDE addresses programming issues by allowing a graphical object based approach to develop multithreaded routines that abstracts the users from parallel programming. ThreadMan manages the software developed using SDE. ThreadMan is a user-level thread manager that automatically spawns and schedules threads at runtime. Two examples have been developed using this methodology to demonstrate that there is virtually no degradation in performance when compared to sequential code, in a single processor system and scalability is achieved as the number of processors is increased.
38463254
Locating and Ranking XML Documents Based on Content and Structure Synopses
We present a new framework for indexing, locating and ranking XML documents based on content and structural synopses extracted from the documents. Instead of indexing each single element or term in a document, we extract a structural summary and a small number of data synopses from the document, which are indexed in an efficient way suitable for query evaluation. Our query language is XPath extended with full-text search. The result of query evaluation is a ranked list of document locations that best match the query. We propose a novel aggregated ranking scheme, which is integrated into the query evaluation to score the documents based on those data synopses. Our experimental evaluation shows that our indexing scheme outperforms the standard XML indexing scheme based on inverted lists and our ranking scheme is effective in terms of precision and recall.
62674005
Itinerant Agents for Mobile Computing
59728652
Practical Grid Computing for Massively Multiplayer Games
666127
Changing the Game in Strategic Sourcing at Procter & Gamble: Expressive Competition Enabled by Optimization
Procter & Gamble put into practice CombineNets approach to building sourcing networks, called expressive competition. At its heart is a vision that looks past lowest-price reverse auctions and combinatorial package bidding toward a highly expressive commerce relationship with suppliers. It enables suppliers to make electronic offers that express rich forms of capabilities and efficiencies. As the buyer, P&G also uses an expressive language to state constraints and preferences. The detailed expressions of supply and demand are brought together via an advanced optimization engine to decide the optimal allocation of business to the suppliers. By March 2005, over a period of two and a half years, P&G had sourced over 3 billion through expressive commerce and seen 294.8 million (9.6 percent) in recommended savings. In the process, P&Gs suppliers benefited from the win-win approach: expressive competition matched demand to the most efficient means of production (rather than squeezing suppliers profit margins) and removed the exposure risks in making offers. Beyond direct monetary savings, the benefits included the redesign of supply networks with quantitative understanding of the trade-offs and the ability to implement in weeks instead of months.
9657478
Computational Electromagnetics and Parallel Dense Matrix Computations
We present computational results using CORAL, a parallel, three-dimensional, nonlinear magnetostatic code based on a volume integral equation formulation. A key feature of CORAL is the ability to solve, in parallel, the large, dense systems of linear equations that are inherent in the use of integral equation methods. Using the Chameleon and PSLES libraries ensures portability and access to the latest linear algebra solution technology.
2370359
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Electrical power management in large-scale IT systems such as commercial data-centers is an application area of rapidly growing interest from both an economic and ecological perspective, with billions of dollars and millions of metric tons of CO2 emissions at stake annually. Businesses want to save power without sacrificing performance. This paper presents a reinforcement learning approach to simultaneous online management of both performance and power consumption. We apply RL in a realistic laboratory testbed using a Blade cluster and dynamically varying HTTP workload running on a commercial web applications middleware platform. We embed a CPU frequency controller in the Blade servers' firmware, and we train policies for this controller using a multi-criteria reward signal depending on both application performance and CPU power consumption. Our testbed scenario posed a number of challenges to successful use of RL, including multiple disparate reward functions, limited decision sampling rates, and pathologies arising when using multiple sensor readings as state variables. We describe innovative practical solutions to these challenges, and demonstrate clear performance improvements over both hand-designed policies as well as obvious "cookbook" RL implementations.