Identifying speed,tag average response times and reliability are the most important capabilities in passive RFID(radio frequency identification) system.QT(query tree) is a famous algorithm for lowest-cost RFID tags,bu...Identifying speed,tag average response times and reliability are the most important capabilities in passive RFID(radio frequency identification) system.QT(query tree) is a famous algorithm for lowest-cost RFID tags,but its shortcoming is high searching delay and high tag average response times.A prefix subsection matching binary(PSMB) algorithm based on QTalgorithm is proposed.The key idea of PSMB anti-collision algorithm is that,during searching phase,a given reader uses the particular tags ID,which has been searched out formerly,to shorten searching delay and depress tag average response times.The idea of PSMB algorithm can be described as follows.Usually,tag ID is composed of several subsections which have different meanings.Based on the tags ID searched out formerly,a given reader builds a prefix database.In subsequent searching phase,the reader uses its prefix database to deduce searching space of tag ID.Simulation results show that identification delay of PSMB algorithm is about 1/3 of QTalgorithm,tag average response times is about 1/4 of QTalgorithm,and system throughput rate is treble QTalgorithm.展开更多
The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It i...The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It is proved by experiment that the algorithm has three features, its construction process is quick, its cost of memory is small. At the same time, its searching process is as quick as the traditional algorithm. The algorithm is suitable for the application which requires preprocessing the patterns dynamically.展开更多
Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanc...Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.展开更多
The capacities of the nodes in the peer-to-peer system are strongly heterogeneous, hence one can benefit from distributing the load, based on the capacity of the nodes. At first a model is discussed to evaluate the lo...The capacities of the nodes in the peer-to-peer system are strongly heterogeneous, hence one can benefit from distributing the load, based on the capacity of the nodes. At first a model is discussed to evaluate the load balancing of the heterogeneous system, and then a novel load balancing scheme is proposed based on the concept of logical servers and the randomized binary tree, and theoretical guarantees are given. Finally, the feasibility of the scheme using extensive simulations is proven.展开更多
基金Sponsored by the National Natural Science Foundation of China(60372042)
文摘Identifying speed,tag average response times and reliability are the most important capabilities in passive RFID(radio frequency identification) system.QT(query tree) is a famous algorithm for lowest-cost RFID tags,but its shortcoming is high searching delay and high tag average response times.A prefix subsection matching binary(PSMB) algorithm based on QTalgorithm is proposed.The key idea of PSMB anti-collision algorithm is that,during searching phase,a given reader uses the particular tags ID,which has been searched out formerly,to shorten searching delay and depress tag average response times.The idea of PSMB algorithm can be described as follows.Usually,tag ID is composed of several subsections which have different meanings.Based on the tags ID searched out formerly,a given reader builds a prefix database.In subsequent searching phase,the reader uses its prefix database to deduce searching space of tag ID.Simulation results show that identification delay of PSMB algorithm is about 1/3 of QTalgorithm,tag average response times is about 1/4 of QTalgorithm,and system throughput rate is treble QTalgorithm.
基金This project was supported by the National "863" High Technology Research and Development Program of China(2003AA142160) and the National Natural Science Foundation of China (60402019)
文摘The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It is proved by experiment that the algorithm has three features, its construction process is quick, its cost of memory is small. At the same time, its searching process is as quick as the traditional algorithm. The algorithm is suitable for the application which requires preprocessing the patterns dynamically.
基金Project(2012CB725403)supported by the National Basic Research Program of ChinaProjects(71210001,51338008)supported by the National Natural Science Foundation of ChinaProject supported by World Capital Cities Smooth Traffic Collaborative Innovation Center and Singapore National Research Foundation Under Its Campus for Research Excellence and Technology Enterprise(CREATE)Programme
文摘Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.
基金the Electronic Development Foundation of Information Industry Ministry China (2002546).
文摘The capacities of the nodes in the peer-to-peer system are strongly heterogeneous, hence one can benefit from distributing the load, based on the capacity of the nodes. At first a model is discussed to evaluate the load balancing of the heterogeneous system, and then a novel load balancing scheme is proposed based on the concept of logical servers and the randomized binary tree, and theoretical guarantees are given. Finally, the feasibility of the scheme using extensive simulations is proven.
