Fractal Image Compression on MIMD Architectures II: Classification Based Speed-up Methods

Since fractal image compression is computationally very expensive, speed-up techniques are required in addition to parallel processing in order to compress large images in reasonable time. In this paper we discuss parallel fractal image compression algorithms suited for MIMD architectures which employ block classification as speed-up method

A survey of parallel algorithms for fractal image compression

This paper presents a short survey of the key research work that has been undertaken in the application of parallel algorithms for Fractal image compression. The interest in fractal image compression techniques stems from their ability to achieve high compression ratios whilst maintaining a very high quality in the reconstructed image. The main drawback of this compression method is the very high computational cost that is associated with the encoding phase. Consequently, there has been significant interest in exploiting parallel computing architectures in order to speed up this phase, whilst still maintaining the advantageous features of the approach. This paper presents a brief introduction to fractal image compression, including the iterated function system theory upon which it is based, and then reviews the different techniques that have been, and can be, applied in order to parallelize the compression algorithm

A survey of techniques and technologies for web-based real-time interactive rendering

When exploring a virtual environment, realism depends mainly on two factors: realistic images and real-time feedback (motions, behaviour etc.). In this context, photo realism and physical validity of computer generated images required by emerging applications, such as advanced e-commerce, still impose major challenges in the area of rendering research whereas the complexity of lighting phenomena further requires powerful and predictable computing if time constraints must be attained. In this technical report we address the state-of-the-art on rendering, trying to put the focus on approaches, techniques and technologies that might enable real-time interactive web-based clientserver rendering systems. The focus is on the end-systems and not the networking technologies used to interconnect client(s) and server(s).Siemens; Bertelsmann mediaSystems GmbH; Eptron Multimedia; Instituto Politécnico do Porto - ISEP-IPP; Institute Laboratory for Mixed Realities at the Academy of Media Arts Cologne, LMR; Mälardalen Real-Time Research Centre (MRTC) at Mälardalen University in Västerås; Q-Systems

Methods for Signal Filtering and Modelling and Their Parallel Distributed Computing Implementation

In this thesis the problem of filtering and modelling one-dimensional discrete signals and implementation of corresponding parallel distributed algorithms will be addressed. In Chapter 2, the research areas of parallel distributed computing environments, rank-based nonlinear filter and fractal functions are reviewed. In Chapter 3, an Interactive Parallel Distributed Computing Environment (IPDCE) is implemented based on Parallel Virtual Machine (PVM) and an interactive application development tool, the Tc1 language. The approach we use is to provide a Tc1 version interface for all procedures of the PVM interface library so that users can utilize any PVM procedure to do their parallel computing interactively. In Chapter 4, an interactive parallel stack-filtering system is implemented, based on the IPDCE. The user can play with this filtering system in both traditional command mode and modern Graphics User Interface (GUI) mode. In order to reduce the time required to compute a standard stack filter, a new minimum threshold decomposition scheme is introduced and other techniques such as minimizing the number of logical operations and utilizing the CPU bit-fields parallel property are also suggested. In this filtering system the user can select sequential or parallel stack-filtering algorithms. The parallel distributed stack-filtering algorithm is implemented with equal task partitioning and PVM. Two numerical simulations show that the interactive parallel stack-filtering system is efficient for both the sequential and the parallel filtering algorithms. In Chapter 5, an extended Iterated Function System (IFS) interpolation method is introduced for modelling a given discrete signal. In order to get the solution of the inverse IFS problem in reasonable time, a suboptimal search algorithm, which estimates first the local self-affine region and then the map parameters is suggested, and the neighbourhood information of a self-affine region is used for enhancing the robustness of this suboptimal algorithm. The parallel distributed version of the in-verse IFS algorithm is implemented with equal task partitioning and using a Remote Procedure Call application programming interface library. The numerical simulation results show that the IFS approach achieves a higher signal to noise ratio than does an existing approach based on autoregressive modelling for self-affine and approximately self-affine one-dimensional signals and, when the number of computers is small, the speed-up ratio is almost linear. In Chapter 6, inverse IFS interpolation is introduced to model self-affine and approximately self-affine one-dimensional signals corrupted by Gaussian noise. Local cross-validation is applied for compromising between the degree of smoothness and fidelity to the data. The parallel distributed version of the inverse algorithm is implemented in Parallel Virtual Machine (PVM) with static optimal task partitioning. A simple computing model is applied which partitions tasks based on only each computer's capability. Several numerical simulation results show that the new IFS inverse algorithm achieves a higher signal to noise ratio than does existing autoregressive modelling for noisy self-affine or approximately self-affine signals.- There is little machine idle time relative to computing time in the optimal task partition mode. In Chapter 7, local IFS interpolation, which realises the IFS limit for self-affine data, is applied to model non self-affi.ne signals. It is difficult, however, to explore the whole parameter space to achieve globally optimal parameter estimation. A two-stage search scheme is suggested to estimate the self-affine region and the associated region parameters so that a suboptimal solution can be obtained in reasonable time. In the first stage, we calculate the self-affine region under the condition that the associated region length is twice that of the self-affine region. Then the second stage calculates the associated region for each self-affine region using a full search space. In order to combat the performance degradation caused by the the difference of machines capabilities and unpredictable external loads, a dynamic load-balance technique based on a data parallelism scheme is applied in the parallel distributed version of the inverse local IFS algorithm. Some numerical simulations show that our inverse local IFS algorithm works efficiently for several types of one-dimensional signal, and the parallel version with dynamic load balance can automatically ensure that each machine is busy with computing and with low idle time

Smart Sensor Technologies for IoT

The recent development in wireless networks and devices has led to novel services that will utilize wireless communication on a new level. Much effort and resources have been dedicated to establishing new communication networks that will support machine-to-machine communication and the Internet of Things (IoT). In these systems, various smart and sensory devices are deployed and connected, enabling large amounts of data to be streamed. Smart services represent new trends in mobile services, i.e., a completely new spectrum of context-aware, personalized, and intelligent services and applications. A variety of existing services utilize information about the position of the user or mobile device. The position of mobile devices is often achieved using the Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, integrating GNSS chips into all devices might have a negative impact on the battery life of future IoT applications. Therefore, alternative solutions to position estimation should be investigated and implemented in IoT applications. This Special Issue, “Smart Sensor Technologies for IoT” aims to report on some of the recent research efforts on this increasingly important topic. The twelve accepted papers in this issue cover various aspects of Smart Sensor Technologies for IoT

Summary of Research 1994

The views expressed in this report are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government.This report contains 359 summaries of research projects which were carried out under funding of the Naval Postgraduate School Research Program. A list of recent publications is also included which consists of conference presentations and publications, books, contributions to books, published journal papers, and technical reports. The research was conducted in the areas of Aeronautics and Astronautics, Computer Science, Electrical and Computer Engineering, Mathematics, Mechanical Engineering, Meteorology, National Security Affairs, Oceanography, Operations Research, Physics, and Systems Management. This also includes research by the Command, Control and Communications (C3) Academic Group, Electronic Warfare Academic Group, Space Systems Academic Group, and the Undersea Warfare Academic Group

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

Design and analysis of a 3-dimensional cluster multicomputer architecture using optical interconnection for petaFLOP computing

In this dissertation, the design and analyses of an extremely scalable distributed multicomputer architecture, using optical interconnects, that has the potential to deliver in the order of petaFLOP performance is presented in detail. The design takes advantage of optical technologies, harnessing the features inherent in optics, to produce a 3D stack that implements efficiently a large, fully connected system of nodes forming a true 3D architecture. To adopt optics in large-scale multiprocessor cluster systems, efficient routing and scheduling techniques are needed. To this end, novel self-routing strategies for all-optical packet switched networks and on-line scheduling methods that can result in collision free communication and achieve real time operation in high-speed multiprocessor systems are proposed. The system is designed to allow failed/faulty nodes to stay in place without appreciable performance degradation. The approach is to develop a dynamic communication environment that will be able to effectively adapt and evolve with a high density of missing units or nodes. A joint CPU/bandwidth controller that maximizes the resource allocation in this dynamic computing environment is introduced with an objective to optimize the distributed cluster architecture, preventing performance/system degradation in the presence of failed/faulty nodes. A thorough analysis, feasibility study and description of the characteristics of a 3-Dimensional multicomputer system capable of achieving 100 teraFLOP performance is discussed in detail. Included in this dissertation is throughput analysis of the routing schemes, using methods from discrete-time queuing systems and computer simulation results for the different proposed algorithms. A prototype of the 3D architecture proposed is built and a test bed developed to obtain experimental results to further prove the feasibility of the design, validate initial assumptions, algorithms, simulations and the optimized distributed resource allocation scheme. Finally, as a prelude to further research, an efficient data routing strategy for highly scalable distributed mobile multiprocessor networks is introduced

Efficient Passive Clustering and Gateways selection MANETs

Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets