Using Broadcast Networks to Create On-demand Extremely Large Scale High-throughput Computing Infrastructures

The availability of large quantities of processors is a crucial enabler of many-task computing. Voluntary computing systems have proven that it is possible to build computing platforms with millions of nodes to support the execution of embarrassingly parallel applications. These systems, however, lack the flexibility of more traditional grid infrastructures. On the other hand, flexible infrastructures currently available can gather only dozens of thousands nodes. We propose a novel architecture for generic Distributed Computing Infrastructures (DCI) that can be instantiated on demand to be, at the same time, flexible and highly-scalable. Bringing the scalability from voluntary computing, the flexibility from grid computing and the elasticity from cloud computing in a single arrangement, our proposal allows for fast setup, fast initialization and fast dismantle of customized DCI supported by both dedicated and shared underlying infrastructures. Our approach leverages broadcast communication as an efficient mechanism to enable aggregation of geographically distributed computing resources, including millions of non-traditional processing devices such as PDA, mobile phones and Digital TV receivers, using both opportunistic and non-opportunistic models. We show the feasibility of the proposed architecture by implementing it atop a digital television system. We also assess the performance of such system and show that it can be used to execute several classes of many-tasks computing applications with very high efficiency, substantially decreasing their response time.

As a supplement to the Global Positioning System (GPS) in an urban center and indoor environment, the digital television (DTV) segment sync signal can be employed to obtain a mobile user’s position. Two DTV receivers and a counter are integrated to measure the time difference of arrival (TDOA) for a pair of received signals from a transmitter and its corresponding repeater (DTVR). Using the measurements from a transmitter and its multiple corresponding DTVR pairs, the mobile user position can be estimated using the recursive least square method. An experiment done in Seoul using two low-grade high resolution digital television (HDTV) receivers and a two-channel universal counter demonstrates that the mean value of the mobile user position measurement is accurate to 42.58 meters circular error probability (CEP).

This paper presents a research of current practices in audio description broadcast in Spanish television channels. The results of this research show that in some television channels the audio description is broadcasted in 'receiver mix audio description' mode while in other channels the alternative used is 'broadcaster mix audio description' mode. In both cases, correct signalling and correct audio description coding is crucial so that digital television receivers can recognize audio description in the broadcast signal and reproduce it upon user request. The current practice of audio description broadcast in Spanish television channels only partially fulfils DVB standard. In addition, not all digital television receivers are able to reproduce appropriately the wide range of options defined in DVB to convey audio description in the television channels. The consequence for the users is less availability of audio description services than expected. Some of the problems detected for the activation of audio description in users' receivers can be solved by applying some enhancement to signalling information used by broadcasters in their DVB television channels. Finally, some recommendations for the users are included to present the key aspects for audio description activation in their digital television receivers.

Nowadays visualization-based knowledge discovery can play an important role in astrophysics. Collaborative visualization can enable multiple users to share visualization experiences, e.g. by interacting simultaneously with astrophysical datasets giving feedback on what other participants are doing/seeing. Further, workflow-driven applications allow reproduction of specific visualization results, a challenging task as selecting suitable visualization parameters may not be a straightforward process. This paper presents VisIVO Science Gateway, a web-based workflow-enabled framework integrating large-scale, multidimensional datasets and applications for visualization and data filtering on Distributed Computing Infrastructures (DCIs). Advanced users are able to create, change, invoke, and monitor workflows while standard users are provided with easy-to-use customised web interfaces hiding all technical aspects of the visualization algorithms and DCI configurations.

In a single frequency network (SFN) for the Advanced Television Systems Committee (ATSC) terrestrial digital television (DTV) system, co-channel interference induced by the multiple transmitters and/or repeaters which use the same output channel is inevitable. Since the presence of interference results in the performance degradation of the SFN, it is crucial to manipulate the interference by adjusting the transmit power and the emission time of each transmitter and repeater within the SFN. In the ATSC terrestrial DTV system, in order to facilitate the interference manipulation process, a transmitter identification (TxID) signal which is embedded in the transmit signal from each transmitter and repeater is recommended. However, such an embedded signal may degrade the DTV signal quality even though the injection level of the TxID signal is very low compared to the DTV signal. Hence, the effect of the TxID signal on the DTV signal needs to be investigated before deploying the SFN with TxID signal. In this paper, the effect of the TxID signal on the performance of legacy DTV receivers is investigated not only with extensive computer simulation but also with laboratory and field tests. According to the various test results, the average performance loss of the conventional DTV receiver due to the TxID signal is less than 0.2 dB when the TxID signal is injected at 30 dB below the DTV signal power.

We propose the methodology of field strength prediction for a digital television (DTV) receiver by virtue of Rec. ITU-R P.1546. The curves shown in this Rec. represent the point-to area field strength for 1kW effective radiated power in the 30 MHz ∼ 3000 MHz. Some computed results are illustrated here from the formulation of field strength for DTV receiver. It was shown that the error of field strength value for dense urban area (R = 30 m) is in the range of about 6.8 ∼ 11.5 % compared with the Okumura-Hata model under some conditions. In addition comparison of service distance between analog and digital TV receivers has been also illustrated. The presented method provides the predicted values of field strength for TV receiver whether transmission quality can be assured or not, and it can be also used to get the protection ratio or separated distance for frequency sharing in the same or adjacent band.

Broadcasting has always been limited by interference between signals. With the introduction of digital terrestrial television broadcasting (DTTB) in the existing analog TV channels, interference remains a limiting factor in the post-transition era after analog signals are turned off and the spectrum is repacked. The use of first adjacent channels and the "UHF taboo channels" in the same community without transmitter spacing limits is unprecedented, and is a challenge to digital television (DTV) receiver designers. This paper discusses the nature of interference between DTV signals on adjacent and UHF taboo channels, and propose some solutions to receiver designers to mitigate the problem.

Distributed Computing Infrastructure is characterized by interfaces that are heterogeneous—syntactically and semantically. SAGA represents the most comprehensive community effort to date to address the heterogeneity by defining a simple, uniform access layer. In this paper, we describe the basic concepts underpinning its design and development. We also discuss RADICAL-SAGA which is the most widely used implementation of SAGA.

Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly.

Allocation of computing resources is a crucial issue when dealing with a huge number of tasks to be completed according to a given deadline and cost constraints. The task scheduling to several resources (e.g. grid, cloud or a supercomputer) with different characteristics is not trivial, especially if a trade-off in terms of time and cost is considered. We propose an allocation approach able to fulfill the given requirements about time and cost through the use of optimizing techniques and an adaptive behavior. Simulated productions of tasks have been run in order to evaluate the characteristics of the proposed approach.

In this paper, we address job scheduling in Distributed Computing Infrastructures, that is a loosely coupled network of autonomous acting High Performance Computing systems. In contrast to the common approach of mutual workload exchange, we consider the more intuitive operator's viewpoint of load-dependent resource reconfiguration. In case of a site's over-utilization, the scheduling system is able to lease resources from other sites to keep up service quality for its local user community. Contrary, the granting of idle resources can increase utilization in times of low local workload and thus ensure higher efficiency. The evaluation considers real workload data and is done with respect to common service quality indicators. For two simple resource exchange policies and three basic setups we show the possible gain of this approach and analyze the dynamics in workload-adaptive reconfiguration behavior.

WS-PGRADE/gUSE is a gateway framework that offers a set of high-level grid and cloud services by which interoperation between grids, clouds, and scientific user communities can be achieved. gUSE is also a workflow system that enables scientific communities to compose and execute a series of computational or data manipulation steps in a scientific application on Distributed Computing Infrastructures (DCIs). The current chapter summarizes the most important features of WS-PGRADE/gUSE.

The Cherenkov Telescope Array (CTA) - an array of several tens of Cherenkov telescopes - is the next generation of ground-based instrument in the field of very high energy gamma-ray astronomy. The CTA observatory is expected to produce a main data stream for permanent storage of the order of 1-to-5 GB/s for about 1000 hours of observation per year, thus producing a total data volume of the order of several PB per year. The CPU time needed to calibrate and process one hour of data taking will be of the order of some thousands CPU hours with current technology. The high data rate of CTA, together with the large computing power requirements for Monte Carlo (MC) simulations, need dedicated computing resources. Massive MC simulations are needed to study the physics of cosmic-ray atmospheric showers as well as telescope response and performance for different detectors and layout configurations. Given these large storage and computing requirements, the Grid approach is well suited, and a vast number of MC simulations are already running on the European Grid Infrastructure (EGI). In order to optimize resource usage and to handle all production and future analysis activities in a coherent way, a high-level framework with advanced functionalities is desirable. For this purpose we have preliminarly evaluated the DIRAC framework for distributed computing and tested it for the CTA workload and data management systems. In this paper we present a possible implementation of a Distributed Computing Infrastructure (DCI) Computing Model for CTA as well as the benchmark test results of DIRAC.

OF THE THESIS Pilot based frameworks for Weather Research Forecasting by Dinesh Prasanth Ganapathi Thesis Director: Dr. Shantenu Jha The Weather Research Forecasting (WRF) domain consists of complex workflows that demand the use of Distributed Computing Infrastructure (DCI). Weather forecasting requires that weather researchers use different set of initial conditions and one or a combination of physics models on the same set of input data. For these type of simulations an ensemble based computing approach becomes imperative. Most DCIs have local job-schedulers that have no smart way of dealing with the execution of an ensemble type of computational problem as the job-schedulers are built to cater to the bare essentials of resource allocation. This means the weather scientists have to submit multiple jobs to the job-scheduler. In this dissertation we use Pilot-Job based tools to decouple work-load submission and resource allocation therefore streamlining the complex workflows in Weather Research and Forecasting domain and reduce their overall time to completion. We also achieve location independent job execution, data movement, placement and processing. Next, we create the necessary enablers to run an ensemble of tasks bearing the capability to run on multiple heterogeneous distributed computing resources there by creating the opportunity to minimize the overall time consumed in running the models. Our experiments show that the tools developed exhibit very good, strong and weak scaling characteristics. These results bear the potential to change the way weather researchers are submitting traditional WRF jobs to the

Distributed computing owes its success to the development of infrastructure, middleware, and standards (e.g., CORBA) to support interoperability. The computing community has slowly recognized the need to protect information and has begun to develop commercial security infrastructures and standards. The US Government must protect national security information against unauthorized information flow. To support MLS distributed computing, a MLS infrastructure must be built that enables information sharing among users at different classification levels. This infrastructure should provide MLS services for protection of classified information and use both the emerging distributed computing and commercial security infrastructures, when possible. The resulting infrastructure will enable users to integrate commercial information technology products into their systems. In this paper, we examine the philosophy that has led to successful distributed computing among heterogeneous, autonomous components and propose an analogous approach for MLS distributed computing. We identify some services that are required to support MLS distributed computing, argue that these services are needed regardless of the MLS architecture used, present an approach for designing these services, and provide design guidance for a critical building block of the MLS infrastructure.