Parallel and Distributed Processing with Applications: Preface

This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms. Design and Analysis of Approximation Algorithms is a graduate course in theoretical computer science taught widely in the universities, both in the United States and abroad. There are, however, very few textbooks available for this course. Among those available in the market, most books follow a problem-oriented format; that is, they collected many important combinatorial optimization problems and their approximation algorithms, and organized them based on the types, or applications, of problems, such as geometric-type problems, algebraic-type problems, etc. Such arrangement of materials is perhaps convenient for a researcher to look for the problems and algorithms related to his/her work, but is difficult for a student to capture the ideas underlying the various algorithms. In the new book proposed here, we follow a more structured, technique-oriented presentation. We organize approximation algorithms into different chapters, based on the design techniques for the algorithms, so that the reader can study approximation algorithms of the same nature together. It helps the reader to better understand the design and analysis techniques for approximation algorithms, and also helps the teacher to present the ideas and techniques of approximation algorithms in a more unified way.

Malicious URL, a.k.a. malicious website, is a common and serious threat to cyber security. Malicious URLs host unsolicited content (spam, phishing, drive-by downloads, etc.) and lure unsuspecting users to become victims of scams (monetary loss, theft of private information, and malware installation), and cause losses of billions of dollars every year. It is imperative to detect and act on such threats in a timely manner. Traditionally, this detection is done mostly through the usage of blacklists. However, blacklists cannot be exhaustive, and lack the ability to detect newly generated malicious URLs. To improve the generality of malicious URL detectors, machine learning techniques have been explored with increasing attention in recent years. This article aims to provide a comprehensive survey and a structural understanding of Malicious URL Detection techniques using machine learning. We present the formal formulation of Malicious URL Detection as a machine learning task, and categorize and review the contributions of literature studies that addresses different dimensions of this problem (feature representation, algorithm design, etc.). Further, this article provides a timely and comprehensive survey for a range of different audiences, not only for machine learning researchers and engineers in academia, but also for professionals and practitioners in cyber security industry, to help them understand the state of the art and facilitate their own research and practical applications. We also discuss practical issues in system design, open research challenges, and point out important directions for future research.

This paper surveys state-of-the-art approaches designed to decrease the power consumption of wearable health monitoring devices, thereby optimizing battery life. Specifically, this paper examines a concept proposed by researchers in a separate investigation, which involves active computation offloading. This entails developing an algorithm that efficiently distributes data processing tasks between wearable health monitoring devices and mobile applications. Researchers have successfully reduced system power consumption by up to 20% by intelligently offloading computations based on existing device characteristics. In contrast, another ECG remote monitoring system focuses on designing the lowest power sensor while keeping the system low cost and scalable. Lastly, this paper provides ideas to further lower power by state-of-the-art chip design, algorithmic and system design techniques.

Declarative Programming Tools for Fermentor Control System

SummaryThe C programming language is a foundational technology for modern computing with millions of lines of code implementing everything from hobby projects to commercial operating systems. This installation base and the programmers producing it represent a massive software engineering investment spanning decades and likely to continue for decades more. Nevertheless, C, which was first standardized almost 30 years ago, lacks many features that make programming in more modern languages safer and more productive. The goal of the C project (pronounced “C for all”) is to create an extension of C that provides modern safety and productivity features while still ensuring strong backward compatibility with C and its programmers. Prior projects have attempted similar goals but failed to honor the C programming style; for instance, adding object‐oriented or functional programming with garbage collection is a nonstarter for many C developers. Specifically, C is designed to have an orthogonal feature set based closely on the C programming paradigm, so that C features can be added incrementally to existing C code bases, and C programmers can learn C extensions on an as‐needed basis, preserving investment in existing code and programmers. This paper presents a quick tour of C features, showing how their design avoids shortcomings of similar features in C and other C‐like languages. Experimental results are presented to validate several of the new features.

Jeff Magee and Jeff Kramer John Wiley and Sons, New York, NY, 1999, 374 pp. ISBN 0471987107, $64.99 The book is an introductory text to the ideas, concepts, and topics of concurrency. The text focuses on understanding concepts and techniques, and problems of concurrency, not on the implementation or language. The author's overall goal is that by a combination of learning and doing using Java should make the process of acquiring the skills relating to concurrency interesting, enjoyable, and challenging. The Java language is thus used only for illustration and programming experience of the reader. The book is intended for a computer science student or software developer. A background in programming is expected, as well as some familiarity with the essential concepts of object-oriented programming. Knowledge of the Java programming language and operating systems concepts is beneficial but not required. After reading the text, a reader can expect to have a broad understanding of the concepts of concurrency, the problems that arise, methods to emphasis desirable properties in a concurrent system, and ways to avoid the undesirable ones. The text provides a systematic treatment of concepts, as means to rigorously specify and model concurrent systems, with Java examples to animate and illustrate the concepts discussed. The book is organized into twelve chapters, with three appendices. The first eight chapters provide a concise and comprehensive foundation of concurrency, with the remaining four chapters focusing on more advanced concepts. The latter four chapters are somewhat supplemental and can be read at the discretion of the reader. The content of the text is self-contained, with no reliance upon external references. The authors provide a concluding set of notes and further topics which reference external works, but these are not used in the chapter contents. The introduction provides the foundation for the book, and an idea of what will follow in the rest of the text. The basics of modeling and Java are covered. Authors follow with the concepts of processes, threads and with the idea of concurrency. The emphasis is on using Java, and on the notation used to define a concurrent process or thread. The discussion continues covering interleaving and asynchronous concurrency. Various details about composition of parallel processes and finite state processing modeling are presented. The programming of concurrent execution using Java is then examined via the concept of multiple threads. Here, sharing objects among Java threads is also discussed. The concept of conditional synchronization is covered next, and is used to construct a monitor. The methods of the base object in Java is used, and a waiting queue associated with a Java object is discussed and implemented. This discussion is followed by introduction of deadlock. Authors show the conditions necessary for a deadlock to occur and present an analysis of a concurrent system establishing that such a system is deadlock-free. The classic Dining Philosopher's problem is used to illustrate the distinction between finding deadlocks in models and in programs. The presentation continues with the safety property (that asserts that nothing bad happens), and the liveliness property (that asserts that nothing good happens). Here, authors use the material on model-based design to consolidate many of the concepts previously discussed. No one modeling method or design methodology is emphasized. Then creation and elimination of threads in a running program is covered next. The dynamic starting and stopping of Java threads is presented. The discussion moves then to messaging passing. Asynchronous and synchronous messaging is presented with Java programming examples. The concept of a rendezvous, allowing for interaction in a messaging system, is also presented. Based on the concepts developed so far filter-pipeline, supervisor-worker, and announcer-listener concurrent architectures are examined. Java programs demonstrating how the elements of each model interact at runtime are developed. The presentation completes with modeling and implementing of timed systems. Time is signaled by the passage of successive time ticks. The authors then elaborate on a system that is event-based rather than thread-based. Java programs are used to illustrate in implementation the concepts discussed. The three appendices provide a reference, specification, and listing of semantics for the finite-state modeling algebra used by the authors throughout the book. The text is ideal for teaching in a classroom environment, or for a motivated reader to use for self-paced learning. Its organization follows a logical train of discussion and thought, with each chapter building successively on the other, with the more difficult concepts and topics withheld until later. This gradual approach makes the material flow smoothly and cohesively from the beginning to the end. The book is intended as a textbook, so does organize the material and discussion as one, but does not become too dry or bland to stifle the reader's interest in the material. The examples are inter-mixed with the discussion to highlight and emphasize essential points the authors make in each chapter. The text illustrates concepts well under discussion, and does not become a long-winded recital of theory. The topics examined are fundamental to concurrency, and are well illustrated and discussed, but no one topic is examined extensively. The code examples are well written concerning the programming style, indentation and comments. A CD is provided, containing the codes from the book. In addition supplementary material consisting of presentation slides and an errata is provided on the author's WWW site, as well as on the CD. The book is up to date both on the topics of concurrency, and with the Java applets, code, and programs used to illustrate them. Later, as the Java language evolves, the examples may need to be updated, but for the time being the text well represents that state of the Java language. William F. Gilreath, Micron Technology, Inc., Boise Idaho

Pair programming is one of the twelve practices of Extreme Programming (XP). Pair programming is usually performed by programmers that are collocated - working in front of the same monitor. But the inevitability of distributed development of software gives rise to important questions: How effective is pair programming if the pairs are not physically next to each other? What if the programmers are geographically distributed? An experiment was conducted at North Carolina State University to compare different working arrangements of student teams developing object-oriented software. Teams were both collocated and in distributed environments; some teams practiced pair programming while others did not. In particular, we compared the software developed by virtual teams using distributed pair programming against collocated teams using pair programming and against virtual teams that did not employ distributed pair programming. The results of the experiment indicate that it is feasible to develop software using distributed pair programming, and that the resulting software is comparable to software developed in collocated or virtual teams (without pair programming) in productivity and quality.

Wireless sensor networks introduce innovative and interesting application scenarios that may support a variety of different application domains including environmental monitoring, disaster prevention, building automation, object tracking, nuclear reactor control, fire detection, agriculture, healthcare, and traffic monitoring. The widespread acceptance of these new services can be improved by the definition of frameworks and architectures that have the potential to radically simplify software development for wireless sensor network based applications. The aim of these new architectures is to support flexible, scalable programming of applications based on adaptive middleware. As a consequence, wireless sensor networks require novel programming paradigms and technologies. Moreover the design of new complex systems, characterized by the interaction of different and heterogeneous resources, will allow the development of innovative applications that meet high performance goals. As a consequence, wireless sensor networks require contributions from many fields such as embedded systems, distributed systems, data management, system security and applications. This Special Issue on Sensor Systems and Software provides a venue to report on recent developments in addressing the research challenges facing system development and software support for wireless sensor networks based systems. In particular, it places emphasis on layers well above the traditional MAC and routing, and transport layer protocols. In the paper Robust Image Transmission over Wireless Sensor Networks, Boluk, Baydere and Harmanci consider the problem of ubiquitous multimedia applications over wireless sensor networks. In particular, they attempt to address the problem of distortions caused on the image data due to channel and instant node failures. They propose two techniques, which they relate to multipath transmission, as a means to compensate for the occurrence of the above problems at the expense of increasing energy consumption and bandwidth requirements. The first technique is based on watermarking and aims to conceal errors by utilizing the discrete wavelet transform to embedding minute replicas of the original image into itself. The second technique is a modification of Reed-Solomon coding appropriate for this context. Through extensive simulations, they discover that error concealment with multipath fusion provides superior performance. Chen, Gonzalez, Vasilakos, Cao and Leung provide a survey in the very active area of Body Area Networks (BANs). Such networks are widely recognised as a core ingredient of next generation healthcare monitoring applications. The survey specifically considers BAN communication modes and their costs and benefits and identify the main design challenges and open issues that need to be addressed before BANs become competitive in applications. Finally, Zoumboulakis and Roussos consider the problem of Complex Event Detection in Extremely ResourceS. Sicari (*) Dipartimento di informatica e comunicazione, Universita degli studi dell’Insubria, Varese, Italy e-mail: sabrina.sicari@uninsubria.it

Multi-paradigm software development is a possible answer to attempts of finding the best paradigm. It was present in software development at the level of intuition and practiced as the “implementation detail” without a real support in design. Recently it is making a twofold breakthrough: several recent programming paradigms are encouraging it, while explicit multi-paradigm approaches aim at its full-scale support. In order to demonstrate this, a survey of selected recent software development (programming) paradigms (aspect-oriented approaches and generative programming) and multiparadigm approaches (multi-paradigm programming in Leda, multi-paradigm design in C++, and intentional programming) is presented. The survey is preceded and underpinned by the analysis of the concept of paradigm in computer science in the context of software development, since there is no common agreement about the meaning of this term, despite its wide use. The analysis has showed that there are two meanings of paradigm: large-scale and small-scale.

At first thought, one may not realize the need for a special issue of Parallel and Distributed Computing Practices focused on Cluster Computing when our community has already invested years of research and spent a wealth of resources on traditional Big Iron supercomputers, for instance, the SGI/Cray Origin and IBM SP. Academia, industry, and national laboratories are still using, and for the foreseeable future, will continue to use, supercomputers to solve both grand-challenge scale and high-throughput applications. Then why the interest and new popularity of research into clusters for high-performance parallel and distributed applications? Clusters incorporate the tremendous successes that are attributable to our parallel and distributed processing community. Over the next decade, clusters will span the entire range of high-performance computing platforms. Instead of being restricted solely to supercomputers for achieving high-performance computing, the spectrum of available platforms will spread out to Beowulf-class clusters, to superclusters, and on to supercomputers. Moving along this continuum represents increasing computational resources, which in turn allows the capability for solving larger classes of applications or instances of problems. Compute-bound applications on workstations often may take advantage of the extra horsepower provided by symmetric multiprocessors. Applications with even larger computational requirements and a high-degree of concurrency may use Beowulf clusters, that is, clusters that are home-built from mass-market, commercial off-the-shelf workstations and networks, for instance, PC's interconnected by Fast Ethernet. A supercluster may contain commodity SMP nodes interconnected with scalable, low-latency, high-bandwidth networks, and is integrated by a system vendor rather than the computational scientist. Applications with greater complexity, for example, grand challenges from the sciences, demand scalable systems with high-performance, interconnects, perhaps coupled with terascale I/O subsystems, and thus, are appropriate for these superclusters. Finally, supercomputers, the largest of the clusters, may provide the ultimate platform for the highest-fidelity models and simulations and data-intensive applications. At each step up this ladder of cluster architectures, the system cost increases approximately by an order of magnitude, but having the high-performance capability to solve the problem of interest may require an entry point at any of these levels, the Beowulf, or supercluster, or even supercomputer platform. Cluster computing with Beowulf- or superclusters, thus, may be one or two orders of magnitude less expensive than a supercomputer, and provide a cost-effective solution and capability that was not available on a workstation. But this cost comparison measures just the basic system price. What about the applications? As recently as a few years ago, the lack of a canonical high-performance architectural paradigm meant that migrating to a new computer system, even from the same vendor, typically required redesigning applications to efficiently use the high-performance system. Thus, the application must be redesigned with parallel algorithms and libraries that are optimized for each high-performance system. This process of porting, redesigning, optimizing, debugging, and analyzing, the application may in fact be prohibitively expensive, and certainly frustrating when the process is completed just in time to greet the next generation system! That was then, this is now. With the successful standardization of system-level interfaces, many of these issues no longer hinder our expedited use of these new, high-performance clusters. The message-passing interface (MPI) is a clear example of a standard that has contributed significantly to the success of cluster computing. Supercomputer vendors working together with the high-performance computing community embarked on a process to standardize the user-level interface and behavior for passing messages between concurrent tasks. Now, using ordinary sequential compilers and vendor-supplied or freely-available implementations of this message-passing interface, applications can be implemented efficiently on one supercomputer and ported with little or no effort to other parallel machines. The message-passing paradigm, thus, provides a reasonably good canonical high-performance model and methodology for implementing high-performance applications. An algorithm that exhibits efficient execution and scaling on one machine then is likely to perform well on another with little or no additional programming effort. Using this cluster computing paradigm, algorithms typically are optimized by minimizing the number of remote memory accesses (reducing the amount of messages passed), and carefully organizing the data placement to increase memory locality. Thus, high-performance algorithms and applications that have been optimized for supercomputers, using the same cluster paradigm, may be appropriate for Beowulf and superclusters. Cluster computing, realizing the importance of a standard high-performance programming environment that applies equally well to both ends of the architectural spectrum, highly leverages these and other successes from parallel and distributed processing research and development. This is in an exciting, new era for high-performance computing where the canonical architectural paradigm stretches from home-built Beowulf clusters, to superclusters, and on to supercomputers. But cluster computing faces some challenges ahead of it. Continued research is required for designing 1) scalable, high-performance algorithms, applications, and methodologies, that can tolerate the communication overheads, and adapt to hybrid, SMP, and heterogeneous, nodes; 2) high-performance computer architectures, scalable interconnection networks, and I/O subsystems; and 3) scalable systems software, compilers, and monitoring tools. Cluster computing has come of age, and it is high time for the parallel and distributed processing community to lay the groundwork for our own legacy of success stories. David A. Bader University of New Mexico

the University of Amsterdam, May 20-31, 1974.This Tract collects the lecture notes of five of the courses given.The sixth course, given by Dr. R. Kowalski on Predicate Logic as a Programming Language in Artificial Intelligence, is scheduled to appear elsewhere.We are very grateful to the Netherlands Organization for the Advancement of Pure Research (Z.W.O.)

A bidirectional transformation is a pair of mappings between source and view data objects, one in each direction. When the view is modified, the source is updated accordingly with respect to some laws. One way to reduce the development and maintenance effort of bidirectional transformations is to have specialized languages in which the resulting programs are bidirectional by construction—giving rise to the paradigm of bidirectional programming. In this paper, we develop a framework for applicative-style and higher-order bidirectional programming, in which we can write bidirectional transformations as unidirectional programs in standard functional languages, opening up access to the bundle of language features previously only available to conventional unidirectional languages. Our framework essentially bridges two very different approaches of bidirectional programming, namely the lens framework and Voigtländer's semantic bidirectionalization, creating a new programming style that is able to obtain benefits from both.

This special issue is based on a collection of selected papers presented at the Fifth International Conference on Advanced Computing held in Chennai (Madras), India in December 97. The International Conference on Advanced Computing is organized annually in India by the Advanced Computing Society (ACS) which is a premier professional society set up in India to cater to the broad interests in the area of Advanced Computing. One of the significant activities of the Society is to organize regular Meetings/Conferences/Symposia. The Conferences are held annually in India during December. Out of the shortlisted papers presented at the Conference held in Chennai (Madras) during December 97, the following six papers were finally selected after a second round of detailed review of the papers. The first paper On designing and implementing collaborative system using Java-RMI by Rajeev R. Raje, Snehasis Mukhopadhyay, Michael Boyles and Nila Patel describe the use of Java-RMI in designing a collaborative information classifier. The principles of RMI, the details of the prototype, and some preliminary results are presented. The paper primarily concentrates on web-based computing paradigms. In the second paper A framework for performance-based program partitioning , Ram Subramanian and Santosh Pande present an efficient and accurate performance model based program-partitioning approach for parallel architectures. The interactions between computation and communication are captured through behavioral edges . The approach yields significant performance improvement. The third paper DDSCHED: a distributed dynamic real-time scheduling algorithm by Anup K. Bhattacharjee, K. Ravindranath, R. Mall and A. Pal presents a dynamic soft real-time scheduling algorithm for distributed systems. The algorithm is based on a local scheduler and a distributed scheduling scheme. The algorithm takes care of the network delays assuming that the communication protocol is CSMA/CD. In the fourth paper Generic operational decomposition for concurrent systems semantics and reflection , Annie Marcoux, Christine Maurel, Frederic Migeon and Patrick Salle discuss about the reflection in concurrent languages, particularly in actor-based languages. The main objective of the paper is to extend concurrent systems to reflection. The authors present a modular and dynamic description of entity operational management, and extend the decomposition to obtain reflective entities. The fifth paper Parallel programming using visual patterns by A. S. M. Sajeev proposes a two level approach to parallel programming within the context of a visual environment. The first level is the specification of patterns encapsulating process communation and synchronization, and the second level is the use of patterns for parallel programming. The approach encourages reuse of patterns. In the sixth paper An application framework for dynamic distributed software architectures , G. R. Ribeiro-Justo and P. R. F. Cunha present an object-oriented application framework for developing evolving (reconfigurable) software architectures for distributed systems. The application framework is called C++CL. Such a requirement is encountered in banking, industrial control and telecommunications applications. We are extremely thankful to the following reviewers who have helped us in reviewing the papers submitted for this special issue: Lawrence Jenkins N. Mohan Ram Nishit Narang Rajeev Shorey Sameer Adhikari K. Balaji K. Rajan Sumit Kasera Subhrajyothi Bhar Pankaj Sethi Ravindranath Kokku Guest Editors: L. M. Patnaik, Ravi Mittal and K. M. Mehta

El presente artículo surgió como una iniciativa académica en la cual se observa que las áreas de conocimiento en el desarrollo de software bajo el paradigma de Programación Orientada a Objetos - POO está confrontado por un modelo de almacenamiento de datos de tipo relacional lo que plantea dos escenarios diferentes que los desarrolladores tratan de mitigar a través de conversiones entre tipos o utilizando herramientas intermedias como el mapeo de objetos relacional que traen ciertas ventajas y desventajas, y por lo cual, se planteo dentro del proyecto la posibilidad de utilizar un motorde almacenamiento de tipo no relacional o NoSQL. Con el diseño y desarrollo del framework para generar aplicaciones web, el usuario podrá definir los objetos que considere incluir en la aplicación, los cuales se almacenarán en el motor MongoDB, el cual, organiza los datos en forma de documentos. La estructura dinámica de estos documentos se puede utilizar en gran cantidad de proyectos, incluyendo muchos que tradicionalmente funcionarían sobre bases de datos relacionales. Con el objetivo de socializar y evaluar el trabajo realizado, se diseñaron algunos instrumentos para recopilar información de usuarios con experiencia en el sector de las bases de datos y el desarrollo de software. Como resultado se resalta que los desarrolladores de software tienen claro los conceptos de persistencia de objetos a través del mapeo objeto relacional (ORM), que el aprendizaje de estas técnicas de desarrollo de software a través de la implementación de código propio o de la utilización de API´s tiene un grado alto de complejidad y en su mayoría (un 60%) son conscientes que estas implementaciones generan un bajo rendimiento en las aplicaciones. Además, se resalta la apertura de estos a optar por otras alternativas para organizar y almacenar la información, diferentes al enfoque relacional utilizado desde hace varios años.

Special issue on distributed information processing in social networks