• Journal of KIISE:Databases
• /
• v.33 no.2
• /
• pp.163-174
• /
• 2006

In distributed wireless sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. We propose a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes input as a sliding window of multivariate stream data and discretizes the data in the window into a string of symbols that characterize the signal changes. In the classification step, it uses a standard text classification algorithm to classify the discretized data in the window. We evaluated both supervised and unsupervised classification algorithms. For supervised, we tested Bayesian classifier and SVM, and for unsupervised, we tested Jaccard, TFIDF Jaro and Jaro Winkler. In our experiments, SVM and TFIDF outperformed other classification methods. In particular, we observed that classification accuracy is improved when the correlation of attributes is also considered along with the n-gram tokens of symbols.

• Proceedings of the Korea Contents Association Conference
• /
• 2007.11a
• /
• pp.135-139
• /
• 2007

Recently Data Centric Storage (DCS) schemes are variously studied for several applications (e.g. natural environment investigation, military application systems and environmental changes monitoring). In DCS scheme, data is stored at nodes within the network by name. There are several drawbacks in the existing schemes. The first is the inefficiency of the range query processing on not considered the locality of store point. the second is the non-homogeneity of store load of each sensors in case of the sensor distribution density is non-uniformed. In this paper, we propose a novel data centric storage scheme with the sensor distribution density which satisfied with the locality of data store location. This scheme divides whole sensor network area using grid and distributes the density bit map witch consist of the sensor density information of each cell. sensors use the density bit map for storing and searching the data. We evaluate our scheme with existing schemes. As a result, we show improved load balancing and more efficient range query processing than existing schemes in environment which sensors are distributed non-uniform.

• The KIPS Transactions:PartD
• /
• v.13D no.7 s.110
• /
• pp.889-900
• /
• 2006

Even though sensor networks are different in user requests and data characteristics depending on each application area, the existing researches on stream data transmission problem focus on the performance improvement of their methods rather than considering the original characteristic of stream data. In this paper, we introduce a hierarchical or distributed sensor network architecture and data model, and then evaluate the multivariate data reduction methods suitable for user requirements and data features so as to apply reduction methods alternatively. To assess the relative performance of the proposed multivariate data reduction methods, we used the conventional techniques, such as Wavelet, HCL(Hierarchical Clustering), Sampling and SVD (Singular Value Decomposition) as well as the experimental data sets, such as multivariate time series, synthetic data and robot execution failure data. The experimental results shows that SVD and Sampling method are superior to Wavelet and HCL ia respect to the relative error ratio and execution time. Especially, since relative error ratio of each data reduction method is different according to data characteristic, it shows a good performance using the selective data reduction method for the experimental data set. The findings reported in this paper can serve as a useful guideline for sensor network application design and construction including multivariate stream data.

• The Journal of the Korea Contents Association
• /
• v.12 no.4
• /
• pp.60-68
• /
• 2012

In recent years, the requirements on the high quality environment monitoring by using the sensor nodes which can handle the multimedia data in WSN have been increased. However, because the volume of multimedia data is tremendous, the limited bandwidth of a wireless channel may incur the bottleneck of a system. To solve such a problem, most of the existing distributed multi-path routing protocols based on multimedia data just focused on overcoming the limited bandwidth in order to enhance the energy efficiency and the transmission rate. However, because the existing methods can not apply a key-based technique to encrypt the multimedia data, they are very weak for the security. In this paper, we propose a secure disjointed multipath routing scheme for multimedia data transmission. Since our proposed scheme divides multimedia data(eg. image) into pixels and sends them through disjointed multipath routing, it can provide security to the whole network without using the key-based method. Our experimental results show that our proposed scheme reduces about 10% the amount of the energy consumption and about 65% the amount of the missed data packets caused by malicious nodes over the existing methods on average.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.18 no.5
• /
• pp.3-16
• /
• 2008

A Wireless Sensor Network (WSN for short) is a wireless network consisting of distributed small devices which are called sensor nodes or motes. Recently, there has been an extensive research on WSN and also on its security. For secure storage and secure transmission of the sensed information, sensor nodes should be equipped with cryptographic algorithms. Moreover, these algorithms should be efficiently implemented since sensor nodes are highly resource-constrained devices. There are already some existing algorithms applicable to sensor nodes, including public key ciphers such as TinyECC and standard block ciphers such as AES. Stream ciphers, however, are still to be analyzed, since they were only recently standardized in the eSTREAM project. In this paper, we implement over the MicaZ platform nine software-based stream ciphers out of the ten in the second and final phases of the eSTREAM project, and we evaluate their performance. Especially, we apply several optimization techniques to six ciphers including SOSEMANUK, Salsa20 and Rabbit, which have survived after the final phase of the eSTREAM project. We also present the implementation results of hardware-oriented stream ciphers and AES-CFB fur reference. According to our experiment, the encryption speeds of these software-based stream ciphers are in the range of 31-406Kbps, thus most of these ciphers are fairly acceptable fur sensor nodes. In particular, the survivors, SOSEMANUK, Salsa20 and Rabbit, show the throughputs of 406Kbps, 176Kbps and 121Kbps using 70KB, 14KB and 22KB of ROM and 2811B, 799B and 755B of RAM, respectively. From the viewpoint of encryption speed, the performances of these ciphers are much better than that of the software-based AES, which shows the speed of 106Kbps.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.6
• /
• pp.565-570
• /
• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.

• Journal of Digital Contents Society
• /
• v.18 no.3
• /
• pp.567-575
• /
• 2017

Location-based services play an important role in many applications such as disaster warning systems and recommendation systems. These applications often require not only location information (e.g., name, latitude, longitude, etc.) but also the impact of events (e.g., earthquake, typhoon, etc.) on locations. Recently, to provide the impact of an event on a location, how to calculate location trustiness by using multimodal information such as earthquake information and disaster sensor data is researched. In the previous approach, the linear decrement of impact value of an event is applied to obtain the location trustiness of a specific location. In this paper, we propose a new approach to enrich location trustiness, that is, the impact of an event on a location, by using social media information additionally. Firstly, we design a collecting system for earthquake information and social media data. Secondly, we present an approach of location trustiness calculation based on earthquake information. Finally, we propose a new approach to enrich location trustiness by augmenting the trustiness in spatially distributed manner based on social media.

• Journal of Communications and Networks
• /
• v.18 no.3
• /
• pp.387-396
• /
• 2016

Multiuser communication has been an important research area of underwater acoustic communications and networking. This paper studies the use of adaptive orthogonal frequency-division multiple access (OFDMA) in a downlink scenario, where a central node sends data to multiple distributed nodes simultaneously. In practical implementations, the instantaneous channel state information (CSI) cannot be perfectly known by the central node in time-varying underwater acoustic (UWA) channels, due to the long propagation delays resulting from the low sound speed. In this paper, we explore the CSI feedback for resource allocation. An adaptive power-bit loading algorithm is presented, which assigns subcarriers to different users and allocates power and bits to each subcarrier, aiming to minimize the bit error rate (BER) under power and throughput constraints. Simulation results show considerable performance gains due to adaptive subcarrier allocation and further improvement through power and bit loading, as compared to the non-adaptive interleave subcarrier allocation scheme. In a lake experiment, channel feedback reduction is implemented through subcarrier clustering and uniform quantization. Although the performance gains are not as large as expected, experiment results confirm that adaptive subcarrier allocation schemes based on delayed channel feedback or long term statistics outperform the interleave subcarrier allocation scheme.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.2
• /
• pp.395-400
• /
• 2017

The paper discussed the air-to-fuel ratio control of automotive fuel-injection systems using the cerebellar model articulation controller(CMAC) neural network. Because of the internal combustion engines and fuel-injection's dynamics is extremely nonlinear, it leads to the discontinuous of the fuel-injection and the traditional method of control based on table look up has the question of control accuracy low. The advantages about CMAC neural network are distributed storage information, parallel processing information, self-organizing and self-educated function. The unique structure of CMAC neural network and the processing method lets it have extensive application. In addition, by analyzing the output characteristics of oxygen sensor, calculating the rate of fuel-injection to maintain the air-to-fuel ratio. The CMAC may easily compensate for time delay. Experimental results proved that the way is more good than traditional for petrol control and the CMAC fuel-injection controller can keep ideal mixing ratio (A/F) for engine at any working conditions. The performance of power and economy is evidently improved.

• Journal of Korea Multimedia Society
• /
• v.25 no.10
• /
• pp.1404-1415
• /
• 2022

The 2-dimensional arrangement method of nodes has been used in most of RF (Radio Frequency) based communication network simulations. However, this method is not useful for the an none-obstacle 3-dimensional space networks in which the propagation delay speed in communication is very slow and, moreover, the values of performance factors such as the communication speed and the error rate change on the depth of node. Such a typical example is an underwater communication network. The 2-dimensional arrangement method is also not useful for the RF based network like some WSNs (Wireless Sensor Networks), IBSs (Intelligent Building Systems), or smart homes, in which the distance between nodes is short or some of nodes can be arranged overlapping with their different heights in similar planar location. In such cases, the 2-dimensional network simulation results are highly inaccurate and unbelievable so that they lead to user's erroneous predictions and judgments. For these reasons, in this paper, we propose a method to place uniformly and randomly communication nodes in 3-dimensional network space, making the wireless link with neighbor node possible. In this method, based on the communication rage of the node, blocks are generated to construct the 3-dimensional network and a node per one block is generated and placed within a block area. In this paper, we also introduce an algorithm based on this method and we show the performance results and evaluations on the average time in a node generation and arrangement, and the arrangement time and scatter-plotted visualization time of all nodes according to the number of them. In addition, comparison with previous studies is conducted. As a result of evaluating the performance of the algorithm, it was found that the processing time of the algorithm was proportional to the number of nodes to be created, and the average generation time of one node was between 0.238 and 0.28 us. ultimately, There is no problem even if a simulation network with a large number of nodes is created, so it can be sufficiently introduced at the time of simulation.