RFID events are a large volume of stream data that continuously come out for tracking and monitoring objects. Many studies have been done to detect a complex event in the RFID stream. However, the existing studies have many problems which increase unnecessary operations when complex events do not satisfy minimum conditions. In this paper, we propose a new scheme to detect complex events when the minimum conditions are satisfied to remove unnecessary operations. To check the minimum conditions of the complex events, we register complex queries in a query index. We detect complex events using the query index and bitmap. To demonstrate the superiority of the proposed method, we compare it with the existing methods through various experiments. As a result, it is shown that the proposed method outperforms the existing methods as a whole.
We propose an energy-efficient security scheme in wireless sensor networks. The proposed scheme converts sensing data using TinyMD5, which is a variation of MD5, a one-way hash function, and can solve the collision problem of hash value that occurs when MD5 is modified. In addition, it strengthens security capabilities by transmitting data through multiple paths after conversion with TinyMD5 and divides the data to make decryption of the original data difficult. To show the superiority of the proposed algorithm, we compare it with the existing schemes through simulations. The performance evaluation results show that the proposed scheme maintains security better than the existing scheme, improving the communication cost and the network lifetime.
SUMMARYIn this paper, we propose a continuous range query processing method over moving objects. To efficiently process continuous range queries, we design a main-memory-based query index that uses smaller storage and significantly reduces the query processing time. We show through performance evaluation that the proposed method outperforms the existing methods.
The popular route recommendation and traffic monitoring over the road networks have become important in the location-based services. The schemes to find out the congested routes were proposed by considering the number of vehicles in a road segment. However, the existing schemes do not consider the features of each road segment such as width, length, and direction in a road network. Furthermore, the existing schemes fail to consider the average moving speed of vehicles. Therefore, they can detect the incorrect density routes. To overcome such problems, we propose a new discovering scheme of congested routes through the analysis of vehicle trajectories in a road network. The proposed scheme divides each road into segments with different width and length in a road network. And then, the congested road segment is detected through the saturation degree of the road segment and the average moving speed of vehicles in the road segment. Finally, we compute the final congested routes by using a clustering scheme. The experimental results have shown that the proposed scheme can efficiently discover the congested routes in the different directions of the roads.
Recently, with the development of wireless communication technology and the wide usage of mobile devices such as PDAs, netbooks, and smart phones, interests on mobile P2P networks have been increased. Location based routing schemes considering the mobility of mobile devices in order to provide mobile P2P services were proposed. However, the existing schemes cause high communication costs since they broadcast the messages to a whole network to create routing paths. In this paper, we propose a new location based routing scheme to efficiently create routing paths along with the mobility of mobile devices. The proposed scheme maintains the information of peers within 2-hop in order to reduce the costs of routing path searches. The proposed scheme searches the routing path considering the directionality of the destination peer and maintains it using the connectivity of peers. It was shown through performance evaluation that the proposed scheme outperforms the existing schemes.
-On road networks, the clustering of moving objects is important for traffic monitoring and routes recommendation. The existing schemes find out density route by considering the number of vehicles in a road segment. Since they don't consider the features of each road segment such as width, length, and directions in a road network, the results are not correct in some real road networks. To overcome such problems, we propose a clustering method for congested routes discovering from the trajectories of moving objects on road networks. The proposed scheme can be divided into three steps. First, it divides each road network into segments with different width, length, and directions. Second, the congested road segments are detected through analyzing the trajectories of moving objects on the road network. The saturation degree of each road segment and the average moving speed of vehicles in a road segment are computed to detect the congested road segments. Finally, we compute the final congested routes by using a clustering scheme. The experimental results showed that the proposed scheme can efficiently discover the congested routes in different directions of the roads.
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