Economic models and algorithms for distributed systems

Distributed computing paradigms for sharing resources such as Clouds, Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. While there are some success stories such as PlanetLab, OneLab, BOINC, BitTorrent, and SETI@home, a widespread use of these technologies for business applications has not yet been achieved. In a business environment, mechanisms are needed to provide incentives to potential users for participating in such networks. These mechanisms may range from simple non-monetary access rights, monetary payments to specific policies for sharing. Although a few models for a framework have been discussed (in the general area of a "Grid Economy"), none of these models has yet been realised in practice. This book attempts to fill this gap by discussing the reasons for such limited take-up and exploring incentive mechanisms for resource sharing in distributed systems. The purpose of this book is to identify research challenges in successfully using and deploying resource sharing strategies in open-source and commercial distributed systems.

Parallel and distributed computing with Java

The Java language first came to public attention in 1995. Within a year, it was being speculated that Java may be a good language for parallel and distributed computing. Its core features, including being objected oriented and platform independence, as well as having built-in network support and threads, has encouraged this view. Today, Java is being used in almost every type of computer-based system, ranging from sensor networks to high performance computing platforms, and from enterprise applications through to complex research-based.simulations. In this paper the key features that make Java a good language for parallel and distributed computing are first discussed. Two Java-based middleware systems, namely MPJ Express, an MPI-like Java messaging system, and Tycho, a wide-area asynchronous messaging framework with an integrated virtual registry are then discussed. The paper concludes by highlighting the advantages of using Java as middleware to support distributed applications.

Semantic organization to enhance active learning based on distributed multimedia educational resources

In order to organize distributed educational resources efficiently, to provide active learners an integrated, extendible and cohesive interface to share the dynamically growing multimedia learning materials on the Internet, this paper proposes a generic resource organization model with semantic structures to improve expressiveness, scalability and cohesiveness. We developed an active learning system with semantic support for learners to access and navigate through efficient and flexible manner. We learning resources in an efficient and flexible manner. We provide facilities for instructors to manipulate the structured educational resources via a convenient visual interface. We also developed a resource discovering and gathering engine based on complex semantic associations for several specific topics.

A flexible monitoring and notification system for distributed resources

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware, a faulty, system or application software. Desirable characteristics for monitoring systems are the ability to connect to any number of different types of monitoring agents and to provide different views of the system, based on a client's particular preferences. This paper outlines and discusses the ongoing activities within the GridRM wide-area resource-monitoring project.

Linear hashtable motion estimation algorithm for distributed video processing

This paper presents a parallel Linear Hashtable Motion Estimation Algorithm (LHMEA). Most parallel video compression algorithms focus on Group of Picture (GOP). Based on LHMEA we proposed earlier [1][2], we developed a parallel motion estimation algorithm focus inside of frame. We divide each reference frames into equally sized regions. These regions are going to be processed in parallel to increase the encoding speed significantly. The theory and practice speed up of parallel LHMEA according to the number of PCs in the cluster are compared and discussed. Motion Vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass Hexagonal Search (HEXBS) motion estimation, which only searches a small number of Macroblocks (MBs). We evaluated distributed parallel implementation of LHMEA of TPA for real time video compression.

Impact of transmission errors in enhanced relay-enabled distributed coordination function

This paper analyzes the performance of Enhanced relay-enabled Distributed Coordination Function (ErDCF) for wireless ad hoc networks under transmission errors. The idea of ErDCF is to use high data rate nodes to work as relays for the low data rate nodes. ErDCF achieves higher throughput and reduces energy consumption compared to IEEE 802.11 Distributed Coordination Function (DCF) in an ideal channel environment. However, there is a possibility that this expected gain may decrease in the presence of transmission errors. In this work, we modify the saturation throughput model of ErDCF to accurately reflect the impact of transmission errors under different rate combinations. It turns out that the throughput gain of ErDCF can still be maintained under reasonable link quality and distance.

Performance evaluation of enhanced relay-enabled distributed coordination function

In this paper we evaluate the performance of our earlier proposed enhanced relay-enabled distributed coordination function (ErDCF) for wireless ad hoc networks. The idea of ErDCF is to use high data rate nodes to work as relays for the low data rate nodes. ErDCF achieves higher throughput and reduced energy consumption compared to IEEE 802.11 distributed coordination function (DCF). This is a result of. 1) using relay which helps to increase the throughput and lower overall blocking time of nodes due to faster dual-hop transmission, 2) using dynamic preamble (i.e. using short preamble for the relay transmission) which further increases the throughput and lower overall blocking time and also by 3) reducing unnecessary overhearing (by other nodes not involved in transmission). We evaluate the throughput and energy performance of the ErDCF with different rate combinations. ErDCF (11,11) (ie. R1=R2=11 Mbps) yields a throughput improvement of 92.9% (at the packet length of 1000 bytes) and an energy saving of 72.2% at 50 nodes.

Analysis of enhanced relay-enabled distributed coordination function under transmission errors

This paper analyzes the performance of enhanced relay-enabled distributed coordination function (ErDCF) for wireless ad hoc networks under transmission errors. The idea of ErDCF is to use high data rate nodes to work as relays for the low data rate nodes. ErDCF achieves higher throughput and reduces energy consumption compared to IEEE 802.11 distributed coordination function (DCF) in an ideal channel environment. However, there is a possibility that this expected gain may decrease in the presence of transmission errors. In this work, we modify the saturation throughput model of ErDCF to accurately reflect the impact of transmission errors under different rate combinations. It turns out that the throughput gain of ErDCF can still be maintained under reasonable link quality and distance.

Using a RESTful messaging and registry system to support a range a distributed applications

Tycho was conceived in 2003 in response to a need by the GridRM [1] resource-monitoring project for a ldquolight-weightrdquo, scalable and easy to use wide-area distributed registry and messaging system. Since Tycho's first release in 2006 a number of modifications have been made to the system to make it easier to use and more flexible. Since its inception, Tycho has been utilised across a number of application domains including widearea resource monitoring, distributed queries across archival databases, providing services for the nodes of a Cray supercomputer, and as a system for transferring multi-terabyte scientific datasets across the Internet. This paper provides an overview of the initial Tycho system, describes a number of applications that utilise Tycho, discusses a number of new utilities, and how the Tycho infrastructure has evolved in response to experience of building applications with it.

An asynchronous distributed dynamic channel assignment scheme for dense WLANs

Wireless local area networks (WLANs) have changed the way many of us communicate, work, play and live. Due to its popularity, dense deployments are becoming a norm in many cities around the world. However, increased interference and traffic demands can severely limit the aggregate throughput achievable if an effective channel assignment scheme is not used. In this paper, we propose an enhanced asynchronous distributed and dynamic channel assignment scheme that is simple to implement, does not require any knowledge of the throughput function, allows asynchronous channel switching by each access point (AP) and is superior in performance. Simulation results show that our proposed scheme converges much faster than previously reported synchronous schemes, with a reduction in convergence time and channel switches by tip to 73.8% and 30.0% respectively.

An improved distributed dynamic channel assignment scheme for dense WLANs

The popularity of wireless local area networks (WLANs) has resulted in their dense deployment in many cities around the world. The increased interference among different WLANs severely degrades the throughput achievable. This problem has been further exacerbated by the limited number of frequency channels available. An improved distributed and dynamic channel assignment scheme that is simple to implement and does not depend on the knowledge of the throughput function is proposed in this work. It also allows each access point (AP) to asynchronously switch to the new best channel. Simulation results show that our proposed scheme converges much faster than similar previously reported work, with a reduction in convergence time and channel switches as much as 77.3% and 52.3% respectively. When it is employed in dynamic environments, the throughput improves by up to 12.7%.