A DMVOCC-MVDA （distributed multiversion optimistic concurrency control with multiversion dynamic adjustment） protocol was presented to process mobile distributed real-time transaction in mobile broadcast environment...A DMVOCC-MVDA （distributed multiversion optimistic concurrency control with multiversion dynamic adjustment） protocol was presented to process mobile distributed real-time transaction in mobile broadcast environments. At the mobile hosts, all transactions perform local pre-validation. The local pre-validation process is carried out against the committed transactions at the server in the last broadcast cycle. Transactions that survive in local pre-validation must be submitted to the server for local final validation. The new protocol eliminates conflicts between mobile read-only and mobile update transactions, and resolves data conflicts flexibly by using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions. Mobile read-only transactions can be committed with no-blocking, and respond time of mobile read-only transactions is greatly shortened. The tolerance of mobile transactions of disconnections from the broadcast channel is increased. In global validation mobile distributed transactions have to do check to ensure distributed serializability in all participants. The simulation results show that the new concurrency control protocol proposed offers better performance than other protocols in terms of miss rate, restart rate, commit rate. Under high work load （think time is ls） the miss rate of DMVOCC-MVDA is only 14.6%, is significantly lower than that of other protocols. The restart rate of DMVOCC-MVDA is only 32.3%, showing that DMVOCC-MVDA can effectively reduce the restart rate of mobile transactions. And the commit rate of DMVOCC-MVDA is up to 61.2%, which is obviously higher than that of other protocols.展开更多
There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing env...There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.展开更多
A prototype of fault diagnosis based on Petri net, which is developed for a satellite tele-control subsystem, is introduced in this paper. Its structure is first given with the emphasis on a Petri net modeling tool wh...A prototype of fault diagnosis based on Petri net, which is developed for a satellite tele-control subsystem, is introduced in this paper. Its structure is first given with the emphasis on a Petri net modeling tool which is designed using the object oriented method. The prototype is connected to the database with DAO (Date Access Object) technique, and makes the Petri net's firing mechanism and its analyzing methods to be packed up as DLL (Dynamic Link Library) documents. Compared with the rule-based expert system method, the Petri net-based one can store the knowledge in mathematical matrix and make inference more quickly and effectively.展开更多
DM usually means an efficient knowledge discovery from database, and the immune algorithm is a biological theory-based and global searching algorithm. A novel induction algorithm is proposed here which integrates a po...DM usually means an efficient knowledge discovery from database, and the immune algorithm is a biological theory-based and global searching algorithm. A novel induction algorithm is proposed here which integrates a power of individual immunity and an evolutionary mechanism of population. This algorithm does not take great care of discovering some classifying information, but unknown knowledge or a predication on higher level rules. Theoretical analysis and simulations both show that this algorithm is prone to the stabilization of a population and the improvement of entire capability, and also keeping a high degree of preciseness during the rule induction.展开更多
Nowadays, many kinds of computer network data management systems have been built widely in China. People have realized widely that management information system (MIS) has brought a revolution to the management mechani...Nowadays, many kinds of computer network data management systems have been built widely in China. People have realized widely that management information system (MIS) has brought a revolution to the management mechanism. Moreover, the managers of company need wide-range and comprehensive decision information more and more urgently which is the character of information explosion era. The needs of users become harsher and harsher in the design of MIS, and these needs have brought new problems to the general designers of MIS. Furthermore, the current method of traditional database development can't solve so big and complex problems of wide-range and comprehensive information processing. This paper proposes the adoption of parallel processing mode, the built of new decision support system (DSS) is to discuss and analyze the problems of information collection, processing and the acquirement of full-merit information with cross-domain and cross-VLDB (very-large database).展开更多
In solving the clustering problem in the context of knowledge discovery in databases (KDD), the traditional methods, for example, the K-means algorithm and its variants, usually require the users to provide the number...In solving the clustering problem in the context of knowledge discovery in databases (KDD), the traditional methods, for example, the K-means algorithm and its variants, usually require the users to provide the number of clusters in advance based on the pro-information. Unfortunately, the number of clusters in general is unknown to the users who are usually short of pro-information. Therefore, the clustering calculation becomes a tedious trial-and-error work, and the result is often not global optimal especially when the number of clusters is large. In this paper, a new dynamic clustering method based on genetic algorithms (GA) is proposed and applied for auto-clustering of data entities in large databases. The algorithm can automatically cluster the data according to their similarities and find the exact number of clusters. Experiment results indicate that the method is of global optimization by dynamically clustering logic.展开更多
基金Project(20030533011)supported by the National Research Foundation for the Doctoral Program of Higher Education of China
文摘A DMVOCC-MVDA （distributed multiversion optimistic concurrency control with multiversion dynamic adjustment） protocol was presented to process mobile distributed real-time transaction in mobile broadcast environments. At the mobile hosts, all transactions perform local pre-validation. The local pre-validation process is carried out against the committed transactions at the server in the last broadcast cycle. Transactions that survive in local pre-validation must be submitted to the server for local final validation. The new protocol eliminates conflicts between mobile read-only and mobile update transactions, and resolves data conflicts flexibly by using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions. Mobile read-only transactions can be committed with no-blocking, and respond time of mobile read-only transactions is greatly shortened. The tolerance of mobile transactions of disconnections from the broadcast channel is increased. In global validation mobile distributed transactions have to do check to ensure distributed serializability in all participants. The simulation results show that the new concurrency control protocol proposed offers better performance than other protocols in terms of miss rate, restart rate, commit rate. Under high work load （think time is ls） the miss rate of DMVOCC-MVDA is only 14.6%, is significantly lower than that of other protocols. The restart rate of DMVOCC-MVDA is only 32.3%, showing that DMVOCC-MVDA can effectively reduce the restart rate of mobile transactions. And the commit rate of DMVOCC-MVDA is up to 61.2%, which is obviously higher than that of other protocols.
文摘There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.
文摘A prototype of fault diagnosis based on Petri net, which is developed for a satellite tele-control subsystem, is introduced in this paper. Its structure is first given with the emphasis on a Petri net modeling tool which is designed using the object oriented method. The prototype is connected to the database with DAO (Date Access Object) technique, and makes the Petri net's firing mechanism and its analyzing methods to be packed up as DLL (Dynamic Link Library) documents. Compared with the rule-based expert system method, the Petri net-based one can store the knowledge in mathematical matrix and make inference more quickly and effectively.
基金This project was supported by the National Natural Science Foundation of China (No. 60073053) the Nationa1 "863" High-Tech P
文摘DM usually means an efficient knowledge discovery from database, and the immune algorithm is a biological theory-based and global searching algorithm. A novel induction algorithm is proposed here which integrates a power of individual immunity and an evolutionary mechanism of population. This algorithm does not take great care of discovering some classifying information, but unknown knowledge or a predication on higher level rules. Theoretical analysis and simulations both show that this algorithm is prone to the stabilization of a population and the improvement of entire capability, and also keeping a high degree of preciseness during the rule induction.
文摘Nowadays, many kinds of computer network data management systems have been built widely in China. People have realized widely that management information system (MIS) has brought a revolution to the management mechanism. Moreover, the managers of company need wide-range and comprehensive decision information more and more urgently which is the character of information explosion era. The needs of users become harsher and harsher in the design of MIS, and these needs have brought new problems to the general designers of MIS. Furthermore, the current method of traditional database development can't solve so big and complex problems of wide-range and comprehensive information processing. This paper proposes the adoption of parallel processing mode, the built of new decision support system (DSS) is to discuss and analyze the problems of information collection, processing and the acquirement of full-merit information with cross-domain and cross-VLDB (very-large database).
基金This project was supported by the National Natural Science Foundation of China (No. 79400013, No. 60074026).
文摘In solving the clustering problem in the context of knowledge discovery in databases (KDD), the traditional methods, for example, the K-means algorithm and its variants, usually require the users to provide the number of clusters in advance based on the pro-information. Unfortunately, the number of clusters in general is unknown to the users who are usually short of pro-information. Therefore, the clustering calculation becomes a tedious trial-and-error work, and the result is often not global optimal especially when the number of clusters is large. In this paper, a new dynamic clustering method based on genetic algorithms (GA) is proposed and applied for auto-clustering of data entities in large databases. The algorithm can automatically cluster the data according to their similarities and find the exact number of clusters. Experiment results indicate that the method is of global optimization by dynamically clustering logic.
