S-Club: an overlay-based efficient service discovery mechanism in CROWN Grid

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches. Chunming Hu is a research staff in the Institute of Advanced Computing Technology at the School of Computer Science and Engineering, Beihang University, Beijing, China. He received his B.E. and M.E. in Department of Computer Science and Engineering in Beihang University. He received the Ph.D. degree in School of Computer Science and Engineering of Beihang University, Beijing, China, 2005. His research interests include peer-to-peer and grid computing; distributed systems and software architectures. Yanmin Zhu is a Ph.D. candidate in the Department of Computer Science, Hong Kong University of Science and Technology. He received his B.S. degree in computer science from Xi’an Jiaotong University, Xi’an, China, in 2002. His research interests include grid computing, peer-to-peer networking, pervasive computing and sensor networks. He is a member of the IEEE and the IEEE Computer Society. Jinpeng Huai is a Professor and Vice President of Beihang University. He serves on the Steering Committee for Advanced Computing Technology Subject, the National High-Tech Program (863) as Chief Scientist. He is a member of the Consulting Committee of the Central Government’s Information Office, and Chairman of the Expert Committee in both the National e-Government Engineering Taskforce and the National e-Government Standard office. Dr. Huai and his colleagues are leading the key projects in e-Science of the National Science Foundation of China (NSFC) and Sino-UK. He has authored over 100 papers. His research interests include middleware, peer-to-peer (P2P), grid computing, trustworthiness and security. Yunhao Liu received his B.S. degree in Automation Department from Tsinghua University, China, in 1995, and an M.A. degree in Beijing Foreign Studies University, China, in 1997, and an M.S. and a Ph.D. degree in computer science and engineering at Michigan State University in 2003 and 2004, respectively. He is now an assistant professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include peer-to-peer computing, pervasive computing, distributed systems, network security, grid computing, and high-speed networking. He is a senior member of the IEEE Computer Society. Lionel M. Ni is chair professor and head of the Computer Science and Engineering Department at Hong Kong University of Science and Technology. Lionel M. Ni received the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, Indiana, in 1980. He was a professor of computer science and engineering at Michigan State University from 1981 to 2003, where he received the Distinguished Faculty Award in 1994. His research interests include parallel architectures, distributed systems, high-speed networks, and pervasive computing. A fellow of the IEEE and the IEEE Computer Society, he has chaired many professional conferences and has received a number of awards for authoring outstanding papers.     

Preference update for e-commerce applications: Model,language, and processing

It is likely that customers issue requests based on out-of-date information in e-commerce application systems. Hence, the transaction failure rates would increase greatly. In this paper, we present a preference update model to address this problem. A preference update is an extended SQL update statement where a user can request the desired number of target data items by specifying multiple preferences. Moreover, the preference update allows easy extraction of criteria from a set of concurrent requests and, hence, optimal decisions for the data assignments can be made. We propose a group evaluation strategy for preference update processing in a multidatabase environment. The experimental results show that the group evaluation can effectively increase the customer satisfaction level with acceptable cost. Peng Li is the Chief Software Architect of didiom LLC. Before that, he was a visiting assistant professor of computer science department in Western Kentucky University. He received his Ph.D. degree of computer science from the University of Texas at Dallas. He also holds a B.Sc. and M.S. in Computer Science from the Renmin University of China. His research interests include database systems, database security, transaction processing, distributed and Internet computer and E-commerce. Manghui Tu received a Bachelor degree of Science from Wuhan University, P.R. China in 1996, and a Master Degree in Computer Science from the University of Texas at Dallas 2001. He is currently working toward the PhD degree in the Department of Computer Science at the University of Texas at Dallas. Mr. Tu’s research interests include distributed systems, grid computing, information security, mobile computing, and scientific computing. His PhD research work focus on the data management in secure and high performance data grid. He is a student member of the IEEE. I-Ling Yen received her BS degree from Tsing-Hua University, Taiwan, and her MS and PhD degrees in Computer Science from the University of Houston. She is currently an Associate Professor of Computer Science at the University of Texas at Dallas. Dr. Yen’s research interests include fault-tolerant computing, security systems and algorithms, distributed systems, Internet technologies, E-commerce, and self-stabilizing systems. She had published over 100 technical papers in these research areas and received many research awards from NSF, DOD, NASA, and several industry companies. She has served as Program Committee member for many conferences and Program Chair/Co-Chair for the IEEE Symposium on Application-Specific Software and System Engineering & Technology, IEEE High Assurance Systems Engineering Symposium, IEEE International Computer Software and Applications Conference, and IEEE International Symposium on Autonomous Decentralized Systems. She is a member of the IEEE. Zhonghang Xia received the B.S. degree in applied mathematics from Dalian University of Technology in 1990, the M.S. degree in Operations Research from Qufu Normal University in 1993, and the Ph.D. degree in computer science from the University of Texas at Dallas in 2004. He is now an assistant professor in the Department of Computer Science, Western Kentucky University, Bowling Green, KY. His research interests are in the area of multimedia computing and networking, distributed systems, and data mining.     

Binary-coding-based ant colony optimization and its convergence

Ant colony optimization (ACO for short) is a meta-heuristics for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. In this paper, genetic algorithm's (GA for short) ideas are introduced into ACO to present a new binary-coding based ant colony optimization. Compared with the typical ACO, the algorithm is intended to replace the problem's parameter-space with coding-space, which links ACO with GA so that the fruits of GA can be applied to ACO directly. Furthermore, it can not only solve general combinatorial optimization problems, but also other problems such as function optimization. Based on the algorithm, it is proved that if the pheromone remainder factor ρ is under the condition of ρ≥1, the algorithm can promise to converge at the optimal, whereas if 0<ρ<1, it does not. This work is supported by the Science Foundation of Shanghai Municipal Commission of Science and Technology under Grant No.00JC14052. Tian-Ming Bu received the M.S. degree in computer software and theory from Shanghai University, China, in 2003. And now he is a Ph.D. candidate of Fudan University in the same area of theory computer science. His research interests include algorithms, especially, heuristic algorithms and heuristic algorithms and parallel algorithms, quantum computing and computational complexity. Song-Nian Yu received the B.S. degree in mathematics from Xi'an University of Science and Technology, Xi'an, China, in 1981, the Ph.D. degree under Prof. L. Lovasz's guidance and from Lorand University, Budapest, Hungary, in 1990. Dr. Yu is a professor in the School of Computer Engineering and Science at Shanghai University. He was a visiting professor as a faculty member in Department of Computer Science at Nelson College of Engineering, West Virginia University, from 1998 to 1999. His current research interests include parallel algorithms' design and analyses, graph theory, combinatorial optimization, wavelet analyses, and grid computing. Hui-Wei Guan received the B.S. degree in electronic engineering from Shanghai University, China, in 1982, the M.S. degree in computer engineering from China Textile University, China, in 1989, and the Ph.D. degree in computer science and engineering from Shanghai Jiaotong University, China, in 1993. He is an associate professor in the Department of Computer Science at North Shore Community College, USA. He is a member of IEEE. His current research interests are parallel and distributed computing, high performance computing, distributed database, massively parallel processing system, and intelligent control.     

Optimal bandwidth utilization of all-optical ring with a converter of degree 4

In many models of all-optical routing,a set of communication paths in a network is given,and a wavelength is to be assigned to each path so that paths sharing an edge receive different wavelengths .The goal is to assign as few wavelengths as possible,in order to use the optical bandwidth efficiently.If a node of a network contains a wavelength converter,any path that passes through this node may change its wavelength .Having converters at some of the nodes can reduce the mumber of wavelengths required for routing,This paper presents a wavelength converter with degree 4and gives a routing algorithm which shows that any routing with load L can be realized with L wavelengths when a node of an all-optical ring hosts such a wavelength converter.It is also proved that 4 is the minimum degree of the converter to reach the full utilization of the available wavelengths if only one mode of an all-optical ring hosts a converter.     

AgentTeamwork: Coordinating grid-computing jobs with mobile agents

AgentTeamwork is a grid-computing middleware system that dispatches a collection of mobile agents to coordinate a user job over remote computing nodes in a decentralized manner. Its utmost focus is to maintain high availability and dynamic balancing of distributed computing resources to a parallel-computing job. For this purpose, a mobile agent is assigned to each process engaged in the same job, monitors its execution at a different machine, takes its periodical execution snapshot, moves it to a lighter-loaded machine, and resumes it from the latest snapshot upon an accidental crash. The system also restores broken inter-process communication involved in the same job using its error-recoverable socket and mpiJava libraries in collaboration among mobile agents. We have implemented the first version of our middleware including a mobile agent execution platform, error-recoverable socket and mpiJava API libraries, a job wrapper program, and several types of mobile agents such as commander, resource, sentinel, and bookkeeper agents, each orchestrating, allocating resources to, monitoring and maintaining snapshots of a user process respectively. This paper presents AgentTeamwork’s execution model, its implementation techniques, and our performance evaluation using the Java Grande benchmark test programs. Munehiro Fukuda received a B.S. from the College of Information Sciences and an M.S. from the Master’s Program in Science and Enginnering at the University of Tsukuba in 1986 and 1988. He received his M.S. and Ph.D. in Information and Computer Science at the University of California at Irvine in 1995 and 1997, respectively. He worked at IBM Tokyo Research Laboratory from 1988 to 1993 and taught at the University of Tsukuba from 1998 to 2001. Since 2001, he has been an assistant professor at Computing & Software Systems, the University of Washington, Bothell. His research interests include mobile agents, multi-threading, cluster computing, grid computing and distributed simulations. Koichi Kashiwagi received a Bachelor of Science degree from the Faculty of Science, Ehime University in 2000 and a Master of Engineering degree from the Department of Compter Science, Ehime University in 2002. In 2004 he became a research assistant in Department of Compter Science, Ehime University. His research interests include distributed computing, job scheduling, and grid computing. Shin-ya Kobayashi received the B.E. degree, M.E. degree, and Dr.E. degree in Communication Engineering from Osaka University in 1985, 1988, and 1991 respectively. From 1991 to 1999, he was on the faculty of Engineering at Kanazawa University, Japan. From 1999 to 2004, He was an Associate Professor in the Department of Computer Science, Ehime University. He is a Professor at Graduate School of Science and Engineering, Ehime University. His research interests include distributed processing, and parallel processing. He is a member of the Information Processing Society of Japan, the Institute of Electrical Engineers of Japan, IEEE, and ACM.     

Recent Progress on Selected Topics in Database Research ——-A Report by Nine Young Chinese Researchers Working in the United States

The study on database technologies, or more generally, the technologies of data and information management, is an important and active research field. Recently, many exciting results have been reported. In this fast growing field, Chinese researchers play more and more active roles. Research papers from Chinese scholars, both in China and abroad,appear in prestigious academic forums.In this paper,we, nine young Chinese researchers working in the United States, present concise surveys and report our recent progress on the selected fields that we are working on.Although the paper covers only a small number of topics and the selection of the topics is far from balanced, we hope that such an effort would attract more and more researchers,especially those in China,to enter the frontiers of database research and promote collaborations. For the obvious reason, the authors are listed alphabetically, while the sections are arranged in the order of the author list.     

A General Probability Formula of the Number of Location Areas＇ Boundaries Crossed by a Mobile Between Two Successive Call Arrivals

Mobility management is a challenging topic in mobile computing environment. Studying the situation of mobiles crossing the boundaries of location areas is significant for evaluating the costs and performances of various location management strategies. Hitherto, several formulae were derived to describe the probability of the number of location areas‘ boundaries crossed by a mobile. Some of them were widely used in analyzing the costs and performances of mobility management strategies. Utilizing the density evolution method of vector Markov processes, we propose a general probability formula of the number of location areas‘ boundaries crossed by a mobile between two successive calls. Fortunately, several widely-used formulae are special cases of the proposed formula.     

Fast evaluation of Bounded Slice-line Grid

Bounded Slice-line Grid (BSG) is an elegant representation of block placement, because it is very intuitionistic and has the advantage of handling various placement constraints. However, BSG has attracted little attention because its evaluation is very time-consuming. This paper proposes a simple algorithm independent of the BSG size to evaluate the BSG representation in O(nloglogn) time, where n is the number of blocks. In the algorithm, the BSG-rooms are assigned with integral coordinates firstly, and then a linear sorting algorithm is applied on the BSG-rooms where blocks are assigned to compute two block sequences, from which the block placement can be obtained in O(n log logn) time. As a consequence, the evaluation of the BSG is completed in O(nloglogn) time, where n is the number of blocks. The proposed algorithm is much faster than the previous graph-based O(n^2) algorithm. The experimental results demonstrate the efficiency of the algorithm.     

Oscillation amplitude-controlled resonant accelerometer design using a reference tracking automatic gain control

In this paper, it is presented a novel approach for the self-sustained resonant accelerometer design, which takes advantages of an automatic gain control in achieving stabilized oscillation dynamics. Through the proposed system modeling and loop transformation, the feedback controller is designed to maintain uniform oscillation amplitude under dynamic input accelerations. The fabrication process for the mechanical structure is illustrated in brief. Computer simulation and experimental results show the feasibility of the proposed accelerometer design, which is applicable to a control grade inertial sense system. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Hyun Seok Yang. This work was supported by the BK21 Project ST·IT Fusion Engineering program in Konkuk University, 2008. This work was supported by the Korea Foundation for International Cooperation of Science & Technology(KICOS) through a grant provided by the Korean Ministry of Education, Science & Technology(MEST) in 2008 (No. K20601000001). Authors also thank to Dr. B.-L. Lee for the help in structure manufacturing. Sangkyung Sung is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the M.S and Ph.D. degrees in Electrical Engineering from Seoul National University in 1998 and 2003, respectively. His research interests include inertial sensors, avionic system hardware, navigation filter, and intelligent vehicle systems. Chang-Joo Kim is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aeronautical Engineering from Seoul National University in 1991. His research interests include nonlinear optimal control, helicopter flight mechanics, and helicopter system design. Young Jae Lee is a Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS related engineering problems. Jungkeun Park is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University. Dr. Park received the Ph.D. in Electrical Engineering and Computer Science from the Seoul National University in 2004. His current research interests include embedded real-time systems design, real-time operating systems, distributed embedded real-time systems and multimedia systems. Joon Goo Park is an Assistant Professor of the Department of Electronic Engineering at Gyung Book National University, Korea. He received the Ph.D. degree in School of Electrical Engineering from Seoul National University in 2001. His research interests include mobile navigation and adaptive control.     

New Meta-Heuristic for Combinatorial Optimization Problems: Intersection Based Scaling

Combinatorial optimization problems are found in many application fields such as computer science,engineering and economy. In this paper, a new efficient meta-heuristic, Intersection-Based Scaling (IBS for abbreviation), is proposed and it can be applied to the combinatorial optimization problems. The main idea of IBS is to scale the size of the instance based on the intersection of some local optima, and to simplify the search space by extracting the intersection from the instance, which makes the search more efficient. The combination of IBS with some local search heuristics of different combinatorial optimization problems such as Traveling Salesman Problem (TSP) and Graph Partitioning Problem (GPP) is studied, and comparisons are made with some of the best heuristic algorithms and meta-heuristic algorithms. It is found that it has significantly improved the performance of existing local search heuristics and significantly outperforms the known best algorithms.     

Self-stabilizing depth-first token circulation on networks

Summary This paper proposes a self-stabilizing protocol which circulates a token on a connected network in nondeterministic depth-first-search order, rooted at a special node. Starting with any initial state in which the network may have no token at all or more than one token, the protocol eventually makes the system stabilize in states having exactly one circulating token. With a slight modification to the protocol —by removing nondeterminism in the search — a depth-first-search tree on the network can be constructed. The proposed protocol runs on systems that allow parallel operations. Shing-Tsaan Huang was born in Taiwan on September 4, 1949. He got his Ph.D. degree in 1985 from Department of Computer Science, University of Maryland at College Park. Before he pursued his Ph.D. degree, he had worked several years in the computer industry in Taiwan. Professor Huang is currently the chairman of the Department of Computer Science, Tsing Hua University, Taiwan, Republic of China. His research interests include interconnection networks, operating systems and distributed computing. He is a senior member of the IEEE Computer Society and a member of the Association for Computing Machinery. Nian-Shing Chen was born in Taiwan on October 21, 1961. He received his Ph.D. degree in computer science from National Tsing Hua University in 1990. Dr. Chen is currently an associate professor with the Department of Information Management at Sun Yat-Sen University of Taiwan. His research interests include distributed systems, computer networks, computer viruses and expert systems. He is a member of IEEE and Phi Tau Phi honorary society.This research is supported by National Science Council of the Republic of China under the contract NSC81-0408-E-007-05 and NSC82-0408-E-007-027     

ARMiner: A Data Mining Tool Based on Association Rules

In this paper,ARM iner,a data mining tool based on association rules,is introduced.Beginning with the system architecture,the characteristics and functions are discussed in details,including data transfer,concept hierarchy generalization,mining rules with negative items and the re-development of the system.An example of the tool‘s application is also shown.Finally,Some issues for future research are presented.     

Image hiding scheme using modulus function and optimal substitution table

The simple least-significant-bit (LSB) substitution technique is the easiest way to embed secret data in the host image. To avoid image degradation of the simple LSB substitution technique, Wang et al. proposed a method using the substitution table to process image hiding. Later, Thien and Lin employed the modulus function to solve the same problem. In this paper, the proposed scheme combines the modulus function and the optimal substitution table to improve the quality of the stego-image. Experimental results show that our method can achieve better quality of the stego-image than Thien and Lin’s method does. The text was submitted by the authors in English. Chin-Shiang Chan received his BS degree in Computer Science in 1999 from the National Cheng Chi University, Taipei, Taiwan and the MS degree in Computer Science and Information Engineering in 2001 from the National Chung Cheng University, ChiaYi, Taiwan. He is currently a Ph.D. student in Computer Science and Information Engineering at the National Chung Cheng University, Chiayi, Taiwan. His research fields are image hiding and image compression. Chin-Chen Chang received his BS degree in applied mathematics in 1977 and his MS degree in computer and decision sciences in 1979, both from the National Tsing Hua University, Hsinchu, Taiwan. He received his Ph.D. in computer engineering in 1982 from the National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at the National Chiao Tung University. From 1983–1989, he was on the faculty of the Institute of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan. From 1989 to 2004, he has worked as a professor in the Institute of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. Since 2005, he has worked as a professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. Dr. Chang is a Fellow of IEEE, a Fellow of IEE and a member of the Chinese Language Computer Society, the Chinese Institute of Engineers of the Republic of China, and the Phi Tau Phi Society of the Republic of China. His research interests include computer cryptography, data engineering, and image compression. Yu-Chen Hu received his Ph.D. degree in Computer Science and Information Engineering from the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan in 1999. Dr. Hu is currently an assistant professor in the Department of Computer Science and Information Engineering, Providence University, Sha-Lu, Taiwan. He is a member of the SPIE society and a member of the IEEE society. He is also a member of the Phi Tau Phi Society of the Republic of China. His research interests include image and data compression, information hiding, and image processing.     

Efficient mining of association rules by reducing the number of passes over the database

This paper introduces a new algorithm of mining association rules.The algorithm RP counts the itemsets with different sizes in the same pass of scanning over the database by dividing the database into m partitions.The total number of pa sses over the database is only(k 2m-2)/m,where k is the longest size in the itemsets.It is much less than k .     

A Novel Computer Architecture to Prevent Destruction by Viruses

In today‘s Internet computing world,illegal activities by crackers pose a serious threat to computer security.It is well known that computer viruses,Trojan horses and other intrusive programs may cause sever and often catastrophic consequences. This paper proposes a novel secure computer architecture based on security-code.Every instruction/data word is added with a security-code denoting its security level.External programs and data are automatically addoed with security-code by hadware when entering a computer system.Instruction with lower security-code cannot run or process instruction/data with higher security level.Security-code cannot be modified by normal instruction.With minor hardware overhead,then new architecture can effectively protect the main computer system from destruction or theft by intrusive programs such as computer viruses.For most PC systems it includes an increase of word-length by 1 bit on register,the memory and the hard disk.     

A New Classification Method to Overcome Over—Branching

Classification is an important technique in data mining.The decision trees builty by most of the existing classification algorithms commonly feature over-branching,which will lead to poor efficiency in the subsequent classification period.In this paper,we present a new value-oriented classification method,which aims at building accurately proper-sized decision trees while reducing over-branching as much as possible,based on the concepts of frequent-pattern-node and exceptive-child-node.The experiments show that while using relevant anal-ysis as pre-processing ,our classification method,without loss of accuracy,can eliminate the over-branching greatly in decision trees more effectively and efficiently than other algorithms do.     

A Power-Aware Branch Predictor by Accessing the BTB Selectively

Microarchitects should consider power consumption, together with accuracy, when designing a branch predictor, especially in embedded processors. This paper proposes a power-aware branch predictor, which is based on the gshare predictor, by accessing the BTB （Branch Target Buffer） selectively. To enable the selective access to the BTB, the PHT （Pattern History Table） in the proposed branch predictor is accessed one cycle earlier than the traditional PHT if the program is executed sequentially without branch instructions. As a side effect, two predictions from the PHT are obtained through one access to the PHT, resulting in more power savings. In the proposed branch predictor, if the previous instruction was not a branch and the prediction from the PHT is untaken, the BTB is not accessed to reduce power consumption. If the previous instruction was a branch, the BTB is always accessed, regardless of the prediction from the PHT, to prevent the additional delay/accuracy decrease. The proposed branch predictor reduces the power consumption with little hardware overhead, not incurring additional delay and never harming prediction accuracy. The simulation results show that the proposed branch predictor reduces the power consumption by 29-47%.     

A Fast Scalable Classifier Tightly Integrated with RDBMS

In this pager,we report our success in building efficient scalable classifiers by exploring the capabilities of modern relational database management systems (RDBMS).In addition to high classification accuracy,the unique features of the approach include its high training speed ,linear scalability,and simplicity in implementation.More importantly,the major computation required in the approach can be implemented using standard functions provided by the modern realtional DBMS.Besides,with the effective rule pruning strategy,the algorithm proposed in this paper can produce a compact set of classification rules,The results of experiments conducted for performance evaluation an analysis are presented.