Final Project Report: DOE Award FG02‐04ER25606 Overlay Transit Networking for Scalable, High Performance Data Communication across Heterogeneous Infrastructure

As the flood of data associated with leading edge computational science continues to escalate, the challenge of supporting the distributed collaborations that are now characteristic of it becomes increasingly daunting. The chief obstacles to progress on this front lie less in the synchronous elements of collaboration, which have been reasonably well addressed by new global high performance networks, than in the asynchronous elements, where appropriate shared storage infrastructure seems to be lacking. The recent report from the Department of Energy on the emerging 'data management challenge' captures the multidimensional nature of this problem succinctly: Data inevitably needs to be buffered, for periods ranging from seconds to weeks, in order to be controlled as it moves through the distributed and collaborative research process. To meet the diverse and changing set of application needs that different research communities have, large amounts of non-archival storage are required for transitory buffering, and it needs to be widely dispersed, easily available, and configured to maximize flexibility of use. In today's grid fabric, however, massive storage is mostly concentrated in data centers, available only to those with user accounts and membership in the appropriate virtual organizations, allocated as if its usage were non-transitory, and encapsulated behind legacy interfaces that inhibit the flexibility of use and scheduling. This situation severely restricts the ability of application communities to access and schedule usable storage where and when they need to in order to make their workflow more productive. (p.69f) One possible strategy to deal with this problem lies in creating a storage infrastructure that can be universally shared because it provides only the most generic of asynchronous services. Different user communities then define higher level services as necessary to meet their needs. One model of such a service is a Storage Network, analogous to those used within computation centers, but designed to operate on a global scale. Building on a basic storage service that is as primitive as possible, such a Global Storage Network would define a framework within which higher level services can be created. If this framework enabled a variety of more specialized middleware and supported a wide array of applications, then interoperability and collaboration could occur based on that common framework. The research in Logistical Networking (LN) carried out under the DOE's SciDAC program tested the value of this approach within the context of several SciDAC application communities. Below we briefly describe the basic design of the LN storage network and some of the results that the Logistical Networking community has achieved

A Framework for Downloading Wide-Area Files

The challenge of efficiently retrieving files that are broken into segments and replicated across the widearea is of prime importance to wide-area, peer-to-peer, and Grid file systems. Two different algorithms addressing this challenge have been proposed and evaluated. While both have been successful in different performance scenarios, there has been no unifying work that can view both algorithms under a single framework. In this thesis, we define such a framework, where download algorithms are defined in terms of the four dimensions that the client always controls: the number of simultaneous downloads, the degree of work replication, the failover strategy, and the server selection algorithm. We then explore the impact of varying parameters along each of these dimensions, testing the framework over several types of file distributions. In addition, the additional dependencies and trends that arise when files are augmented with erasure codes rather than replication are examined

Supporting multiple output devices on an ad-hoc basis in visualisation

In recent years, new visualisation techniques and devices, such as remote visualisation and stereoscopic displays, have been developed to help researchers. In a remote visualisation environment the user may want to see visualisation on a different device, such as a PDA or stereo device, and in different circumstances. Each device needs to be configured correctly, otherwise it may lead to an incorrect rendering of the output. For end users, however, it can be difficult to configure each device without a knowledge of the device property and rendering. Therefore, in a multiple user and multiple display environment, to obtain the correct display for each device can be a challenge. In this project, the focus on investigating a solution that can support end users to use different display devices easily. The proposed solution is to develop an application that can support the ad-hoc use of any display device without the system being preconfigured in advance. Thus, end users can obtain the correct visualisation output without any complex rendering configuration. We develop a client-server based approach to this problem. The client application can detect the properties of a device and the server application can use these properties to configure the rendering software to generate the correct image for subsequent display on the device. The approach has been evaluated through many tests and the results show that using the application is a useful in helping end users use different display devices in visualisation

Adaptive remote visualization system with optimized network performance for large scale scientific data

This dissertation discusses algorithmic and implementation aspects of an automatically configurable remote visualization system, which optimally decomposes and adaptively maps the visualization pipeline to a wide-area network. The first node typically serves as a data server that generates or stores raw data sets and a remote client resides on the last node equipped with a display device ranging from a personal desktop to a powerwall. Intermediate nodes can be located anywhere on the network and often include workstations, clusters, or custom rendering engines. We employ a regression model-based network daemon to estimate the effective bandwidth and minimal delay of a transport path using active traffic measurement. Data processing time is predicted for various visualization algorithms using block partition and statistical technique. Based on the link measurements, node characteristics, and module properties, we strategically organize visualization pipeline modules such as filtering, geometry generation, rendering, and display into groups, and dynamically assign them to appropriate network nodes to achieve minimal total delay for post-processing or maximal frame rate for streaming applications. We propose polynomial-time algorithms using the dynamic programming method to compute the optimal solutions for the problems of pipeline decomposition and network mapping under different constraints. A parallel based remote visualization system, which comprises a logical group of autonomous nodes that cooperate to enable sharing, selection, and aggregation of various types of resources distributed over a network, is implemented and deployed at geographically distributed nodes for experimental testing. Our system is capable of handling a complete spectrum of remote visualization tasks expertly including post processing, computational steering and wireless sensor network monitoring. Visualization functionalities such as isosurface, ray casting, streamline, linear integral convolution (LIC) are supported in our system. The proposed decomposition and mapping scheme is generic and can be applied to other network-oriented computation applications whose computing components form a linear arrangement

Big Data for Qualitative Research

Big Data for Qualitative Research covers everything small data researchers need to know about big data, from the potentials of big data analytics to its methodological and ethical challenges. The data that we generate in everyday life is now digitally mediated, stored, and analyzed by web sites, companies, institutions, and governments. Big data is large volume, rapidly generated, digitally encoded information that is often related to other networked data, and can provide valuable evidence for study of phenomena. This book explores the potentials of qualitative methods and analysis for big data, including text mining, sentiment analysis, information and data visualization, netnography, follow-the-thing methods, mobile research methods, multimodal analysis, and rhythmanalysis. It debates new concerns about ethics, privacy, and dataveillance for big data qualitative researchers. This book is essential reading for those who do qualitative and mixed methods research, and are curious, excited, or even skeptical about big data and what it means for future research. Now is the time for researchers to understand, debate, and envisage the new possibilities and challenges of the rapidly developing and dynamic field of big data from the vantage point of the qualitative researcher

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization