Controller Area Network (CAN) schedulability analysis: Refuted,revisited and revised

Controller Area Network (CAN) is used extensively in automotive applications, with in excess of 400 million CAN enabled microcontrollers manufactured each year. In 1994 schedulability analysis was developed for CAN, showing how worst-case response times of CAN messages could be calculated and hence guarantees provided that message response times would not exceed their deadlines. This seminal research has been cited in over 200 subsequent papers and transferred to industry in the form of commercial CAN schedulability analysis tools. These tools have been used by a large number of major automotive manufacturers in the design of in-vehicle networks for a wide range of cars, millions of which have been manufactured during the last decade. This paper shows that the original schedulability analysis given for CAN messages is flawed. It may provide guarantees for messages that will in fact miss their deadlines in the worst-case. This paper provides revised analysis resolving the problems with the original approach. Further, it highlights that the priority assignment policy, previously claimed to be optimal for CAN, is not in fact optimal and cites a method of obtaining an optimal priority ordering that is applicable to CAN. The paper discusses the possible impact on commercial CAN systems designed and developed using flawed schedulability analysis and makes recommendations for the revision of CAN schedulability analysis tools. Robert I. Davis received a DPhil in Computer Science from the University of York in 1995. Since then he has founded three start-up companies, all of which have succeeded in transferring real-time systems research into commercial product. At Northern Real-Time Technologies Ltd. (1995–1997) he was responsible for development of the Volcano CAN software library. At LiveDevices Ltd. (1997–2001) he was responsible for development of the Real-Time Architect suite of products, including an OSEK RTOS and schedulability analysis tools. In 2002, Robert returned to the University of York, and in 2004 he was involved in setting up a spin out company, Rapita Systems Ltd., aimed at transferring worst-case execution time analysis technology into industry. Robert is a member of the Real-Time Systems Research Group at the University of York, and a director of Rapita Systems Ltd. His research interests include scheduling algorithms and schedulability analysis for real-time systems. Alan Burns is head of the Real-Time Systems Research Group at the University of York. His research interests cover a number of aspects of real-time systems including the assessment of languages for use in the real-time domain, distributed operating systems, the formal specification of scheduling algorithms and implementation strategies, and the design of dependable user interfaces to real-time applications. He has authored/co-authored over 370 papers and 10 books, with a large proportion of them concentrating on real-time systems and the Ada programming language. Professor Burns has been actively involved in the creation of the Ravenscar Profile, a subset of Ada”s tasking model, designed to enable the analysis of real-time programs and their timing properties. Reinder J. Bril received a B.Sc. and an M.Sc. (both with honours) from the University of Twente, and a Ph.D. from the Technische Universiteit Eindhoven, the Netherlands. He started his professional career in January 1984 at the Delft University of Technology. From May 1985 until August 2004, he was with Philips, and worked in both Philips Research as well as Philips’ Business Units. He worked on various topics, including fault tolerance, formal specifications, software architecture analysis, and dynamic resource management, and in different application domains, e.g. high-volume electronics consumer products and (low volume) professional systems. In September 2004, he made a transfer back to the academic world, to the System Architecture and Networking (SAN) group of the Mathematics and Computer Science department of the Technische Universiteit Eindhoven. His main research interests are currently in the area of reservation-based resource management for networked embedded systems with real-time constraints. Johan J. Lukkien has been head of the System Architecture and Networking Research group at Eindhoven University of Technology since 2002. He received an M.Sc. and a Ph.D. from Groningen University in the Netherlands. In 1991, he joined Eindhoven University, after two years leave at the California Institute of Technology. His research interests include the design and performance analysis of parallel and distributed systems. Until 2000 he was involved in large-scale simulations in physics and chemistry. Since 2000, his research focus has shifted to the application domain of networked resource-constrained embedded systems. Contributions of the SAN group are in the area of component-based middleware for resource-constrained devices, distributed co-ordination, Quality of Service in networked systems and schedulability analysis in real-time systems.     

Reliable broadcasts and communication models: tradeoffs and lower bounds

Reliable Broadcast is a mechanism by which a processor in a distributed system disseminates a value to all other processors in the presence of both communication and processor failures. Protocols to achieve Reliable Broadcast are at the heart of most fault-tolerant applications. We characterize the execution time of Reliable Broadcast protocols as a function of the communication model. This model includes familiar communication structures such as fully-connected point-to-point graphs, linear chains, rings, broadcast networks (such as Ethernet) and buses. We derive a parameterized protocol that implements Reliable Broadcast for any member within this class. We obtain lower bound results that show the optimality of our protocols. The lower bound results identify a time complexity gap between systems where processors may only fail to send messages, and systems where processors may fail both to send and to receive messages. The tradeoffs that our results reveal between performance, resiliency and network cost offer many new alternatives previously not considered in designing fault-tolerant systems. Özalp Babaoglu is Associate Professor in the Department of Computer Science at Cornell University, Ithaca, New York. His research interests include distributed systems, fault tolerance, performance evaluation and modeling. He received a BS in electrical engineering from George Washington University, Washington, D.C. in 1976. From the University of California, Berkeley, he received a MS in 1977 and a PhD in 1981, both in computer science. While at Berkeley, he designed and implemented the virtual memory extensions to VAX Unix that came to be known as 3. Obsd. Pat Stephenson is a Doctoral Candidate in the Computer Science Department at Cornell University, Ithaca, New York. His research interests include distributed systems and fault tolerance. In 1983, he received a B.A. (Mod.) in computer science from Trinity College, Dublin, Ireland. He received his MS in computer science from Cornell in 1986. He is currently working on new tradeoffs in the design of fault-tolerant algorithms. Rogério Drummond is Assistant Professor in the Computer Science Department at the Universidade Estadual de Campinas (UNICAMP), São Paulo, Brazil. His interests include distributed computing, fault tolerance and operating systems. He received a BS and a MS in computer science from the Universidade Estadual de Campinas in 1978 and 1980, respectively. In 1986 he received a PhD in computer science from Cornell University. He is currently working on integrated environments for the development of software and hardware.Partial support for this work was provided by the National Science Foundation under Grants DCR-86-01864 and MCS-82-10356 and AT&T under a Foundation GrantSupported partially by the Defense Advanced Research Projects Agency (DoD) under ARPA order 5378, Contract MDA 903-85-C-0124, and partially by an IBM graduate fellowship. The views, opinions and findings contained in this report are solely those of the authors and should not be construed as an official Department of Defense position, policy, or decisionSupported partially by the CAPES and CNPq agencies of the Ministry of Education of Brazil     

Analysis of window-constrained execution time systems

Feasibility tests for hard real-time systems provide information about the schedulability of the task set. However, this information is a yes or a no answer, that is, whether the task set achieves the test or not. From the real-time system design point of view, having more information available would be useful. For example, how much the computation time can vary without jeopardising the system feasibility. This work specifically provides methods to determine off-line how much a task can increase its computation time, by maintaining the system feasibility under a dynamic priority scheduling. The extra time can be determined not only in all the task activations, but in n of a window of m invocations. This is what we call a window-constrained execution time system. The results presented in this work can be used in all kinds of real-time systems: fault tolerance management, imprecise computation, overrun handling, control applications, etc. Patricia Balbastre is an assistant professor of Computer Engineering. She graduated in Electronic Engineering at the Technical University of Valencia, Spain, in 1998. And the Ph.D. degree in Computer Science at the same university in 2002. Her main research interests include real-time operating systems, dynamic scheduling algorithms and real-time control. Ismael Ripoll received the B.S. degree from the Polytechnic University of Valencia, Spain, in 1992; the Ph.D. degree in Computer Science at the Polytechnic University of Valencia, Spain, in 1996. Currently he is Professor in the DISCA Department of the same University. His research interests include embedded and real-time operating systems. Alfons Crespo is Professor of the Department of Computer Engineering of the Technical University of Valencia. He received the PhD in Computer Science from the Technical University of Valencia, Spain, in 1984. He held the position of Associate professor in 1986 and full Professor in 1991. He leads the group of Industrial Informatics and has been the responsible of several European and Spanish research projects. His main research interest include different aspects of the real-time systems (scheduling, hardware support, scheduling and control integration, …). He has published more than 60 papers in specialised journals and conferences in the area of real-time systems.     

Finite-horizon scheduling of radar dwells with online template construction

Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon. Sathish Gopalakrishnan is a visting scholar in the Department of Computer Science, University of Illinois at Urbana-Champaign, where he defended his Ph.D. thesis in December 2005. He received an M.S. in Applied Mathematics from the University of Illinois in 2004 and a B.E. in Computer Science and Engineering from the University of Madras in 1999. Sathish’s research interests concern real-time and embedded systems, and the design of large-scale reliable systems. He received the best student paper award for his work on radar dwell scheduling at the Real-Time Systems Symposium 2004. Marco Caccamo graduated in computer engineering from the University of Pisa in 1997 and received the Ph.D. degree in computer engineering from the Scuola Superiore S. Anna in 2002. He is an Assistant Professor of the Department of Computer Science at the University of Illinois. His research interests include real-time operating systems, real-time scheduling and resource management, wireless sensor networks, and quality of service control in next generation digital infrastructures. He is recipient of the NSF CAREER Award (2003). He is a member of ACM and IEEE. Chi-Sheng Shih is currently an assistant professor at the Graduate Institute of Networking and Multimedia and Department of Computer Science and Information Engineering at National Taiwan University since February 2004. He received the B.S. in Engineering Science and M.S. in Computer Science from National Cheng Kung University in 1993 and 1995, respectively. In 2003, he received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His main research interests are embedded systems, hardware/software codesign, real-time systems, and database systems. Specifically, his main research interests focus on real-time operating systems, real-time scheduling theory, embedded software, and software/hardware co-design for system-on-a-chip. Chang-Gun Lee received the B.S., M.S. and Ph.D. degrees in computer engineering from Seoul National University, Korea, in 1991, 1993 and 1998, respectively. He is currently an Assistant Professor in the Department of Electrical Engineering, Ohio State University, Columbus. Previously, he was a Research Scientist in the Department of Computer Science, University of Illinois at Urbana-Champaign from March 2000 to July 2002 and a Research Engineer in the Advanced Telecomm. Research Lab., LG Information & Communications, Ltd. from March 1998 to February 2000. His current research interests include real-time systems, complex embedded systems, QoS management, and wireless ad-hoc networks. Chang-Gun Lee is a member of the IEEE Computer Society. Lui Sha graduated with the Ph.D. degree from Carnegie-Mellon University in 1985. He was a Member and then a Senior Member of Technical Staff at Software Engineering Institute (SEI) from 1986 to 1998. Since Fall 1998, he has been a Professor of Computer Science at the University of Illinois at Urbana Champaign, and a Visiting Scientist of the SEI. He was the Chair of IEEE Real Time Systems Technical Committee from 1999 to 2000, and has served on its Executive Committee since 2001. He was a member of National Academy of Science’s study group on Software Dependability and Certification from 2004 to 2005, and is an IEEE Distinguished Visitor (2005 to 2007). Lui Sha is a Fellow of the IEEE and the ACM.     

Causal memory: definitions,implementation, and programming

Summary The abstraction of a shared memory is of growing importance in distributed computing systems. Traditional memory consistency ensures that all processes agree on a common order of all operations on memory. Unfortunately, providing these guarantees entails access latencies that prevent scaling to large systems. This paper weakens such guarantees by definingcausal memory, an abstraction that ensures that processes in a system agree on the relative ordering of operations that arecausally related. Because causal memory isweakly consistent, it admits more executions, and hence more concurrency, than either atomic or sequentially consistent memories. This paper provides a formal definition of causal memory and gives an implementation for message-passing systems. In addition, it describes a practical class of programs that, if developed for a strongly consistent memory, run correctly with causal memory. Mustaque Ahamad is an Associate Professor in the College of Computing at the Georgia Institute of Technology. He received his M.S. and Ph.D. degrees in Computer Science from the State University of New York at Stony Brook in 1983 and 1985 respectively. His research interests include distributed operating systems, consistency of shared information in large scale distributed systems, and replicated data systems. James E. Burns received the B.S. degree in mathematics from the California Institute of Technology, the M.B.I.S. degree from Georgia State University, and the M.S. and Ph.D. degrees in information and computer science from the Georgia Institute of Technology. He served on the faculty of Computer Science at Indiana University and the College of Computing at the Georgia Institute of Technology before joining Bellcore in 1993. He is currently a Member of Technical Staff in the Network Control Research Department, where he is studying the telephone control network with special interest in behavior when faults occur. He also has research interests in theoretical issues of distributed and parallel computing especially relating to problems of synchronization and fault tolerance.This work was supported in part by the National Science Foundation under grants CCR-8619886, CCR-8909663, CCR-9106627, and CCR-9301454. Parts of this paper appeared in S. Toueg, P.G. Spirakis, and L. Kirousis, editors,Proceedings of the Fifth International Workshop on Distributed Algorithms, volume 579 ofLecture Notes on Computer Science, pages 9–30, Springer-Verlag, October 1991The photograph of Professor J.E. Burns was published in Volume 8, No. 2, 1994 on page 59This author's contributions were made while he was a graduate student at the Georgia Institute of Technology. No photograph and biographical information is available for P.W. Hutto Gil Neiger was born on February 19, 1957 in New York, New York. In June 1979, he received an A.B. in Mathematics and Psycholinguistics from Brown University in Providence, Rhode Island. In February 1985, he spent two weeks picking cotton in Nicaragua in a brigade of international volunteers. In January 1986, he received an M.S. in Computer Science from Cornell University in Ithaca, New York and, in August 1988, he received a Ph.D. in Computer Science, also from Cornell University. On August 20, 1988, Dr. Neiger married Hilary Lombard in Lansing, New York. He is currently a Staff Software Engineer at Intel's Software Technology Lab in Hillsboro, Oregon. Dr. Neiger is a member of the editorial boards of theChicago Journal of Theoretical Computer Science and theJournal of Parallel and Distributed Computing.     

Hiding collaborative recommendation association rules

The concept of Privacy-Preserving has recently been proposed in response to the concerns of preserving personal or sensible information derived from data mining algorithms. For example, through data mining, sensible information such as private information or patterns may be inferred from non-sensible information or unclassified data. There have been two types of privacy concerning data mining. Output privacy tries to hide the mining results by minimally altering the data. Input privacy tries to manipulate the data so that the mining result is not affected or minimally affected. For output privacy in hiding association rules, current approaches require hidden rules or patterns to be given in advance [10, 18–21, 24, 27]. This selection of rules would require data mining process to be executed first. Based on the discovered rules and privacy requirements, hidden rules or patterns are then selected manually. However, for some applications, we are interested in hiding certain constrained classes of association rules such as collaborative recommendation association rules [15, 22]. To hide such rules, the pre-process of finding these hidden rules can be integrated into the hiding process as long as the recommended items are given. In this work, we propose two algorithms, DCIS (Decrease Confidence by Increase Support) and DCDS (Decrease Confidence by Decrease Support), to automatically hiding collaborative recommendation association rules without pre-mining and selection of hidden rules. Examples illustrating the proposed algorithms are given. Numerical simulations are performed to show the various effects of the algorithms. Recommendations of appropriate usage of the proposed algorithms based on the characteristics of databases are reported. Leon Wang received his Ph.D. in Applied Mathematics from State University of New York at Stony Brook in 1984. From 1984 to 1987, he was an assistant professor in mathematics at University of New Haven, Connecticut, USA. From 1987 to 1994, he joined New York Institute of Technology as a research associate in the Electromagnetic Lab and assistant/associate professor in the Department of Computer Science. From 1994 to 2001, he joined I-Shou University in Taiwan as associate professor in the Department of Information Management. In 1996, he was the Director of Computing Center. From 1997 to 2000, he was the Chairman of Department of Information Management. In 2001, he was Professor and director of Library, all in I-Shou University. In 2002, he was Associate Professor and Chairman in Information Management at National University of Kaohsiung, Taiwan. In 2003, he rejoined New York Institute of Technology. Dr.Wang has published 33 journal papers, 102 conference papers, and 5 book chapters, in the areas of data mining, machine learning, expert systems, and fuzzy databases, etc. Dr. Wang is a member of IEEE, Chinese Fuzzy System Association Taiwan, Chinese Computer Association, and Chinese Information Management Association. Ayat Jafari received the Ph.D. degree from City University of New York. He has conducted considerable research in the areas of Computer Communication Networks, Local Area Networks, and Computer Network Security, and published many technical articles. His interests and expertise are in the area of Computer Networks, Signal Processing, and Digital Communications. He is currently the Chairman of the Computer Science and Electrical Engineering Department of New York Institute of Technology. Tzung-Pei Hong received his B.S. degree in chemical engineering from National Taiwan University in 1985, and his Ph.D. degree in computer science and information engineering from National Chiao-Tung University in 1992. He was a faculty at the Department of Computer Science in Chung-Hua Polytechnic Institute from 1992 to 1994, and at the Department of Information Management in I-Shou University from 1994 to 2001. He was in charge of the whole computerization and library planning for National University of Kaohsiung in Preparation from 1997 to 2000, and served as the first director of the library and computer center in National University of Kaohsiung from 2000 to 2001 and as the Dean of Academic Affairs from 2003 to 2006. He is currently a professor at the Department of Electrical Engineering and at the Department of Computer Science and Information Engineering. His current research interests include machine learning, data mining, soft computing, management information systems, and www applications. Springer     

A Prolog simulator for deterministic P systems with active membranes

In this paper we propose a new way to represent P systems with active membranes based on Logic Programming techniques. This representation allows us to express the set of rules and the configuration of the P system in each step of the evolution as literals of an appropriate language of first order logic. We provide a Prolog program to simulate, the evolution of these P systems and present some auxiliary tools to simulate the evolution of a P system with active membranes using 2-division which solves the SAT problem following the techniques presented in Reference.¹⁰ Andrés Cordón-Franco: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Mathematical Logic, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical (software implementation) point of view. Miguel A. Gutiérrez-Naranjo: He is an assistant professor in the Computer Science and Artificial Intelligence Department at University of Sevilla, Spain. He is also a member of the Research Group on Natural Computing of the University of Seville. His research interest includes Machine Learning, Logic Programming and Membrane Computing, both from a theoretical and a practical point of view. Mario J. Pérez-Jiménez, Ph.D.: He is professor of Department of Computer Science and Artificial Intelligence at University of Seville, where he is the head of the Group of Research on Natural Computing, He has published 8 books of Mathematics and Computation, and more than 90 scientific articles in prestigious scientific journals. He is member of European Molecular Computing Consortium. Fernando Sancho-Caparrini: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Complex Systems, DNA Computing, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical point of view.     

Applying language modeling to session identification from database trace logs

A database session is a sequence of requests presented to the database system by a user or an application to achieve a certain task. Session identification is an important step in discovering useful patterns from database trace logs. The discovered patterns can be used to improve the performance of database systems by prefetching predicted queries, rewriting the current query or conducting effective cache replacement.In this paper, we present an application of a new session identification method based on statistical language modeling to database trace logs. Several problems of the language modeling based method are revealed in the application, which include how to select values for the parameters of the language model, how to evaluate the accuracy of the session identification result and how to learn a language model without well-labeled training data. All of these issues are important in the successful application of the language modeling based method for session identification. We propose solutions to these open issues. In particular, new methods for determining an entropy threshold and the order of the language model are proposed. New performance measures are presented to better evaluate the accuracy of the identified sessions. Furthermore, three types of learning methods, namely, learning from labeled data, learning from semi-labeled data and learning from unlabeled data, are introduced to learn language models from different types of training data. Finally, we report experimental results that show the effectiveness of the language model based method for identifying sessions from the trace logs of an OLTP database application and the TPC-C Benchmark. Xiangji Huang joined York University as an Assistant Professor in July 2003 and then became a tenured Associate Professor in May 2006. Previously, he was a Post Doctoral Fellow at the School of Computer Science, University of Waterloo, Canada. He did his Ph.D. in Information Science at City University in London, England, with Professor Stephen E. Robertson. Before he went into his Ph.D. program, he worked as a lecturer for 4 years at Wuhan University. He also worked in the financial industry in Canada doing E-business, where he was awarded a CIO Achievement Award, for three and half years. He has published more than 50 refereed papers in journals, book chapter and conference proceedings. His Master (M.Eng.) and Bachelor (B.Eng.) degrees were in Computer Organization & Architecture and Computer Engineering, respectively. His research interests include information retrieval, data mining, natural language processing, bioinformatics and computational linguistics. Qingsong Yao is a Ph.D. student in the Department of Computer Science and Engineering at York University, Toronto, Canada. His research interests include database management systems and query optimization, data mining, information retrieval, natural language processing and computational linguistics. He earned his Master's degree in Computer Science from Institute of Software, Chinese Academy of Science in 1999 and Bachelor's degree in Computer Science from Tsinghua University. Aijun An is an associate professor in the Department of Computer Science and Engineering at York University, Toronto, Canada. She received her Bachelor's and Master's degrees in Computer Science from Xidian University in China. She received her PhD degree in Computer Science from the University of Regina in Canada in 1997. She worked at the University of Waterloo as a postdoctoral fellow from 1997 to 1999 and as a research assistant professor from 1999 to 2001. She joined York University in 2001. She has published more than 60 papers in refereed journals and conference proceedings. Her research interests include data mining, machine learning, and information retrieval.     

Fast and simple distributed consensus

Summary The problem of fault-tolerant agreement is fundamental to distributed computing. When agreement is to be reached in spite of arbitrary behavior by faulty processors, this problem is calledDistributed Consensus. By requiring that the number of faulty processors be , wheren is the number of processors in the system, we are able to derive two new protocols forDistributed Consensus. Both are simple and use messages that are only one bit in length, and both provide forearly stopping: the fewer failures there are, the fewer rounds of communication are required. One protocol is optimal with respect to the number of rounds of communication required, and the other is asymptotically optimal with respect to the total number of message bits exchanged. James E. Burns received the B.S. degree in mathematics from the California Institute of Technology, the M.B.I.S. degree from Georgia State University, and the M.S. and Ph.D. degrees in information and computer science from the Georgia Institute of Technology. He served on the faculty of Computer Science at Indiana University and the College of Computing at the Georgia Institute of Technology before joining Bellcore in 1993. He is currently a Member of Technical Staff in the Network Control Research Department, where he is studying the telephone control network with special interest in behavior when faults occur. He also has research interests in theoretical issues of distributed and parallel computing, especially relating to problems of synchronization and fault tolerance. Gil Neiger was born on February 19, 1957 in New York, New York. In June 1979, he received an A.B. in Mathematics and Psycholinguistics from Brown University in Proidence, Rhode Island. In February 1985, he spent two weeks picking cotton in Nicaragua in a brigade of international volunteers. In January 1986, he received an M.S. in Computer Science from Cornell University in Ithaca, New York and, in August 1988, he received a Ph.D. in Computer Science, also from Cornell University. On August 20, 1988, Dr. Neiger married Hilary Lombard in Lansing, New York. Since August 1988, he has been an Assistant Professor in the College of Computing (formely School of Information and Computer Science) at the Georgia Institute of Technology in Atlanta, Georgia. Dr. Neiger is a member of the editorial board of theChicago Journal of Theoretical Computer Science and theJournal of Parallel and Distributed Computing.This author was supported in part by the National Science Foundation under grants CCR-8909663, CCR-9106627, and CCR-9301454.