Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store ma...Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels(e.g., item level and container level). Non-deterministic finite automata(NFA)based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.展开更多
Complex event processing (CEP) can extract meaningful events for real-time locating system (RTLS) applications. To identify complex event accurately in RTLS, we propose a new RFID complex event processing method GEEP,...Complex event processing (CEP) can extract meaningful events for real-time locating system (RTLS) applications. To identify complex event accurately in RTLS, we propose a new RFID complex event processing method GEEP, which is based on the timed automata (TA) theory. By devising RFID locating application into complex events, we model the timing diagram of RFID data streams based on the TA. We optimize the constraint of the event streams and propose a novel method to derive the constraint between objects, as well as the constraint between object and location. Experiments prove the proposed method reduces the cost of RFID complex event processing, and improves the efficiency of the RTLS.展开更多
The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidime...The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidimensional space, is difficult to utilize and process. This paper proposes an automatic data acquisition fi-amework to resolve such difficulty, which synthetically utilize intelligent inemet of things （IoT）, semantic web and complext event processing （CEP） technology. We also implement a SCEP prototype system with the capability of real-time detecting complex business events on the goods sorting line, which adopts a detection method consisting of four stages. The simulation results show that the system has good performance and feasible enough to deal with the complex business which need data support fTom multidimensional space.展开更多
随着RFID和传感器等数据采集设备的广泛使用及物联网的发展,产生了大量的事件类型的数据,原始的事件数据必须经过复杂事件处理(Complex Event Processing,CEP),才能变成具有丰富语意并对用户有价值的信息,复杂事件处理作为物联网智能处...随着RFID和传感器等数据采集设备的广泛使用及物联网的发展,产生了大量的事件类型的数据,原始的事件数据必须经过复杂事件处理(Complex Event Processing,CEP),才能变成具有丰富语意并对用户有价值的信息,复杂事件处理作为物联网智能处理层的重要组成部分,越来越受到重视.在实际应用中,许多事件流具有长过程的特点,要求相应的复杂事件处理需设置大时间窗口,相对于有限的内存,复杂事件处理面临新的挑战.现有的复杂事件处理均局限于内存进行,均未涉及外存的事件存储和检测.因此,现有的模型和系统均不能用于长过程复杂事件处理.为此,本文提出基于时间片划分的HTF(Hash structure by object ID in memory and Timeslice File in disk)事件实例存储策略和基于实例映射表的大时间窗口复杂事件检测方法,形成了面向长过程的复杂事件处理模型LPCEP(Complex Event Processing for Long Process).相关实验验证了模型用于长过程复杂事件处理的有效性和高效性.展开更多
One research crucial to wider adoption of Radio Frequency Identification （RFID） technology is how to efficiently transform sequences of RFID readings into meaningful business events. Contrary to traditional events, ...One research crucial to wider adoption of Radio Frequency Identification （RFID） technology is how to efficiently transform sequences of RFID readings into meaningful business events. Contrary to traditional events, RFID readings are usually of high volume and velocity, and have the attributes representing their reading objects, occurrence times and spots. Based on these characteristics and the Non-deterministic Finite Automata （NFA） implementation framework, this paper studies the performance issues of RFID complex event processing and proposes corresponding optimization techniques. Our techniques include： （1） taking advantage of negation events or exclusiveness between events to prune intermediate results, thus reduces memory consumption; （2） with different selectivities of complex events, purposefully reordering the join operations between events to improve overall efficiency, achieve higher stream throughput; （3） utilizing the slot-based or B＋-tree-based approach to optimizing the processing performance with the time window constraint. We present the analytical results of these techniques and validate their effectiveness through experiments.展开更多
In recent years, there has been a growing need for complex event processing （CEP）, ranging from supply chain management to security monitoring. In many scenarios events are generated in different sources but arrive ...In recent years, there has been a growing need for complex event processing （CEP）, ranging from supply chain management to security monitoring. In many scenarios events are generated in different sources but arrive at the central server out of order, due to the differences of network latencies. Most state-of-the-art techniques process out-of-order events by buffering the events until the total event order within a specified range can be guaranteed. Their main problems are leading to increasing response time and reducing system throughput. This paper aims to build a high performance out-of- order event processing mechanism, which can match events as soon as they arrive instead of buffering them till all arrive. A suffix-automaton-based event matching algorithm is proposed to speed up query processing, and a confidence-based accuracy evaluation is proposed to control the query result quality. The performance of our approach is evaluated through detailed accuracy and response time analysis. As experimental results show, our approach can obviously speed up the query matching time and produce reasonable query results.展开更多
Critical infrastructures (CI) are difficult to handle due to their complexity, size and the number of stakeholders involved. During emergency situations (e.g. fire or terrorist attack), a CI operator in the control ro...Critical infrastructures (CI) are difficult to handle due to their complexity, size and the number of stakeholders involved. During emergency situations (e.g. fire or terrorist attack), a CI operator in the control room is faced with a flood of information coming from different sensors and legacy monitoring systems. Since in these situations, time is critical and the operators are under a great deal of pressure, a holistic management of all the technical systems and actors involved is needed, reinforced by the Recommendation and Decision Support System (RDSS) that helps emergency managers to take correct and timely decisions. One way to provide an adequate RDSS support to the operator is proposed in this paper which is based on an intelligent, event driven layer that sits on top of the legacy CI monitoring system. Powered by the complex event processing capabilities and facility data model implemented in the form of CI ontology, this layer processes events originating from different sources, conducts the situation and risk assessment, and reacts accordingly, either automatically or via recommendations proposed to emergency personnel. To validate the proposed approach, an event-driven RDSS was deployed on an airport use case (Nikola Tesla airport in Belgrade), as one of the most complex CIs.展开更多
基金supported by National Social Science Fund (No. 16CTQ013)the Application Fundamental Research Foundation of Sichuan Province, China (No. 2017JY0011)the Key Project of Sichuan Provincial Department of Education, China (No. 2017GZ0333)
文摘Radio frequency identification(RFID) enabled retail store management needs workflow optimization to facilitate real-time decision making. In this paper, complex event processing(CEP) based RFID-enabled retail store management is studied, particularly focusing on automated shelf replenishment decisions. We define different types of event queries to describe retailer store workflow action over the RFID data streams on multiple tagging levels(e.g., item level and container level). Non-deterministic finite automata(NFA)based evaluation models are used to detect event patterns. To manage pattern match results in the process of event detection, optimization algorithm is applied in the event model to share event detection results. A simulated RFID-enabled retail store is used to verify the effectiveness of the method, experiment results show that the algorithm is effective and could optimize retail store management workflow.
文摘Complex event processing (CEP) can extract meaningful events for real-time locating system (RTLS) applications. To identify complex event accurately in RTLS, we propose a new RFID complex event processing method GEEP, which is based on the timed automata (TA) theory. By devising RFID locating application into complex events, we model the timing diagram of RFID data streams based on the TA. We optimize the constraint of the event streams and propose a novel method to derive the constraint between objects, as well as the constraint between object and location. Experiments prove the proposed method reduces the cost of RFID complex event processing, and improves the efficiency of the RTLS.
文摘The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidimensional space, is difficult to utilize and process. This paper proposes an automatic data acquisition fi-amework to resolve such difficulty, which synthetically utilize intelligent inemet of things （IoT）, semantic web and complext event processing （CEP） technology. We also implement a SCEP prototype system with the capability of real-time detecting complex business events on the goods sorting line, which adopts a detection method consisting of four stages. The simulation results show that the system has good performance and feasible enough to deal with the complex business which need data support fTom multidimensional space.
文摘随着RFID和传感器等数据采集设备的广泛使用及物联网的发展,产生了大量的事件类型的数据,原始的事件数据必须经过复杂事件处理(Complex Event Processing,CEP),才能变成具有丰富语意并对用户有价值的信息,复杂事件处理作为物联网智能处理层的重要组成部分,越来越受到重视.在实际应用中,许多事件流具有长过程的特点,要求相应的复杂事件处理需设置大时间窗口,相对于有限的内存,复杂事件处理面临新的挑战.现有的复杂事件处理均局限于内存进行,均未涉及外存的事件存储和检测.因此,现有的模型和系统均不能用于长过程复杂事件处理.为此,本文提出基于时间片划分的HTF(Hash structure by object ID in memory and Timeslice File in disk)事件实例存储策略和基于实例映射表的大时间窗口复杂事件检测方法,形成了面向长过程的复杂事件处理模型LPCEP(Complex Event Processing for Long Process).相关实验验证了模型用于长过程复杂事件处理的有效性和高效性.
基金supported by the National Natural Science Foundation of China under Grant No.60720106001
文摘One research crucial to wider adoption of Radio Frequency Identification （RFID） technology is how to efficiently transform sequences of RFID readings into meaningful business events. Contrary to traditional events, RFID readings are usually of high volume and velocity, and have the attributes representing their reading objects, occurrence times and spots. Based on these characteristics and the Non-deterministic Finite Automata （NFA） implementation framework, this paper studies the performance issues of RFID complex event processing and proposes corresponding optimization techniques. Our techniques include： （1） taking advantage of negation events or exclusiveness between events to prune intermediate results, thus reduces memory consumption; （2） with different selectivities of complex events, purposefully reordering the join operations between events to improve overall efficiency, achieve higher stream throughput; （3） utilizing the slot-based or B＋-tree-based approach to optimizing the processing performance with the time window constraint. We present the analytical results of these techniques and validate their effectiveness through experiments.
基金supported by the National Natural Science Foundation of China under Grant Nos.61003058,60933001the Fundamental Research Funds for the Central Universities under Grant No.N090104001
文摘In recent years, there has been a growing need for complex event processing （CEP）, ranging from supply chain management to security monitoring. In many scenarios events are generated in different sources but arrive at the central server out of order, due to the differences of network latencies. Most state-of-the-art techniques process out-of-order events by buffering the events until the total event order within a specified range can be guaranteed. Their main problems are leading to increasing response time and reducing system throughput. This paper aims to build a high performance out-of- order event processing mechanism, which can match events as soon as they arrive instead of buffering them till all arrive. A suffix-automaton-based event matching algorithm is proposed to speed up query processing, and a confidence-based accuracy evaluation is proposed to control the query result quality. The performance of our approach is evaluated through detailed accuracy and response time analysis. As experimental results show, our approach can obviously speed up the query matching time and produce reasonable query results.
文摘Critical infrastructures (CI) are difficult to handle due to their complexity, size and the number of stakeholders involved. During emergency situations (e.g. fire or terrorist attack), a CI operator in the control room is faced with a flood of information coming from different sensors and legacy monitoring systems. Since in these situations, time is critical and the operators are under a great deal of pressure, a holistic management of all the technical systems and actors involved is needed, reinforced by the Recommendation and Decision Support System (RDSS) that helps emergency managers to take correct and timely decisions. One way to provide an adequate RDSS support to the operator is proposed in this paper which is based on an intelligent, event driven layer that sits on top of the legacy CI monitoring system. Powered by the complex event processing capabilities and facility data model implemented in the form of CI ontology, this layer processes events originating from different sources, conducts the situation and risk assessment, and reacts accordingly, either automatically or via recommendations proposed to emergency personnel. To validate the proposed approach, an event-driven RDSS was deployed on an airport use case (Nikola Tesla airport in Belgrade), as one of the most complex CIs.
