• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.989-997
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• 2018

Massive event stream brings us great challenges in its volume, velocity, variety, value and veracity. Picking up some valuable information from it often faces with long detection time, high memory consumption and low detection efficiency. Aiming to solve the problems above, an efficient complex event detection method based on NFA_HTS (Nondeterministic Finite Automaton_Hash Table Structure) is proposed in this paper. The achievement of this paper lies that we successfully use NFA_HTS to realize the detection of complex event from massive RFID event stream. Specially, in our scheme, after using NFA to capture the related RFID primitive events, we use HTS to store and process the large matched results, as a result, our scheme can effectively solve the problems above existed in current methods by reducing lots of search, storage and computation operations on the basis of taking advantage of the quick classification and storage technologies of hash table structure. The simulation results show that our proposed NFA_HTS scheme in this paper outperforms some general processing methods in reducing detection time, lowering memory consumption and improving event throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4307-4325
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• 2016

With the aim of solving the problems of long processing times, high memory consumption and low event throughput in the current processing approaches in out-of-order RFID event streams, an efficient complex event processing method based on INFA-HTS (Improved Nondeterministic Finite Automaton-Hash Table Structure) is presented in this paper. The contribution of this paper lies in the fact that we use INFA and HTS to successfully realize the detection of complex events for out-of-order RFID event streams. Specifically, in our scheme, to detect the disorder of out-of-order event streams, we expand the traditional NFA model into a new INFA model to capture the related RFID primitive events from the out-of-order event stream. To high-efficiently manage the large intermediate capturing results, we use the HTS to store and process them. As a result, these problems in the existing methods can be effectively solved by our scheme. The simulation results of our experiments show that our proposed method in this paper outperforms some of the current general processing approaches used to process out-of-order RFID event streams.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1554-1563
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• 2008

As the interests on RFID technologies increase, a lot of research activities on RFID middleware systems to handle the data acquired by RFID readers are going on actively. Meanwhile, even though various kinds of RFID middleware methodologies and related techniques have been proposed, the common data type which is dealt with in those systems is an EPC code, mainly. Also, there are few researches of the implementation of collecting the stream data queued from RFID readers endlessly and without blocking, classifying the data into some groups according to usage, and sending the resulting data to specific applications. In this paper, we propose the method of data handling in RFID middleware to efficiently process an EPC event stream data using detail filtering, checking of data modification, creation of data set to transfer, data grouping, and various kinds of RFID data format transform. Our method is based on a de facto international standard interface defined in the ALE middleware specification by EPCglobal, and application and service users can directly set various kinds of conditions to handle the stream data.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.143-154
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• 2008

RFID events are large volume of stream data which come out continuously. Many studies have been done to detect a business event in RFID stream. However, the existing methods have many problems which increase unnecessary operations when business events do not satisfy minimum conditions. In this paper, to remove unnecessary operations, we define the minimum condition of business events and propose an efficient method that detects business events only when the minimum condition is satisfied. To check the minimum condition of business events, we register business queries in a query index. We detect business events using the query index and bitmap. It is shown through various experiment that the proposed method outperforms the existing methods.

• The KIPS Transactions:PartD
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• v.14D no.3 s.113
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• pp.273-284
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• 2007

RFID middleware systems collect and filter the RFID streaming data gathered continuously by numerous readers in order to process requests from applications. These requests are called continuous queries because they are kept on executing during certain periods. To enhance the performance of the middleware, it is required to build an index to process the continuous queries efficiently. Several approaches of building an index on not data records but queries, called Query Index, are proposed and widely used for evaluating continuous queries over streaming data. The EPCglobal proposed an Event Cycle Specification (ECSpec) model, which is a standard query interface for RFID applications. Continuous queries based on ECSpec consist of a large number of segments for representing the query conditions. The problem with using any of the existing query indexes on these continuous queries is that it takes a long time to build the index because it is necessary to insert a large number of segments into the index. To solve this problem, we propose an Aggregate Transformation that converts a group of segments into a compressed data which is representative of the segments. We compare the performance of a transformed index with the existing query indexes.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.166-178
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• 2007

The ALE specification of EPCglobal is leading the development of RFID standards, includes the Event Cycle Specification (ECSpec) describing how long a cycle is, how to filter RFID tag data and which reader is interested in. The ECSpec is a specification for filtering and collecting RFID tag data. It is registered to a middleware for long time and is evaluated to return results satisfying the requirements included in it. Thus, it is quite similar to the continuous query. It can be transformed into a continuous query as its predicate in WHERE clause is characterized by the long interval. Long intervals cause problems deteriorating insertion and search performance of existing query indices. In this paper, we propose a TLC-index as a new query index structure for long interval data. The TLC-index has hybrid structure that uses the cell construct of CQI-index with the virtual construct of VCR-index for partitioning long intervals. The TLC-index can reduce the storage cost and improve the insertion performance through decomposing long intervals into one or more cell constructs that have long size. It can also improve the search performance through decomposing short intervals into one or more virtual constructs that have short size enough to fit into those intervals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.683-690
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• 2011

The conventional sensor tag data filtering algorithm uses time window based data filtering for each tag data. However, this approach shows many performance problems such as low error and event detection rate and larger storage size requirement. In this paper, we propose a collaborative sensor tag data filtering algorithm to improve sensor data processing performance. simulation study shows that the proposed sensor tag filtering algorithm outperforms the conventional filtering algorithm in terms of the processing time, the size of required data storage memory and accuracy of error and event detection rate.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.157-161
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• 2009

In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.1014-1021
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• 2009

In an environment of home network where a number of technologies including heterogeneous hardware platforms, networking and protocols, middleware systems, and etc, exist, OSGi provides a platform for deployment and sharing of services managed in hardware and guarantees compatibility among applications. However, only simple control and processing of event data are considered in a home network using OSGi, and the consideration about real time processing of data stream generated by sensors is not enough. Therefore, researches allowing users to effectively develop OSGi applications by using various kinds of sensors generating data streams in the home network environment using OSGi are needed. In this paper, we propose an effective method of processing various types of real time data streams supplied to OSGi applications, including filtering, grouping, and counting, etc.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.718-720
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• 2008

In this paper, the study focus on continuous query in EPC Information Services(EPCIS) middleware which is a component of RFID system. We can consider EPCIS as a data stream system with a repository. In our work continuous query is implemented in two query execution model. One is standing query model another is traditional query execution model in which continuous query run over database periodically. Furthermore a balance strategy is presented. It is used to determine which continuous query implementation model is suitable for the query. Finally we conclude our work and issue some research topic for future work.