Dae-Wha Seo

Intrusion detection based on traffic analysis in wireless sensor networks

This paper proposes a lightweight, fast, and efficient traffic intensity-based intrusion detection method for wireless sensor networks (WSNs), containing a large number of nodes which transmit data periodically. Intrusion detection method is based on analysis of neighbors behavior and thresholding technique, applied to selected parameters: the number of received packets in a time window of a given length and inter-arrival time of packets. It does not require installation of any additional hardware and extra communication costs; its computational requirements are negligible. The proposed technique ma be used in both hierarchical and flat WSNs. The paper contains recommendations to the choice of threshold value for each traffic parameter. The results of evaluation, which was performed in Castalia simulator for WSNs, demonstrate that the proposed intrusion detection technique has better accuracy in comparison to the common algorithms.

ATS-DA: Adaptive Timeout Scheduling for Data Aggregation in Wireless Sensor Networks

In wireless sensor networks, the timeout scheduling of data aggregation controls the time each sensor node has to wait to receive data from its child nodes. This paper proposes a new timeout scheduling scheme for data aggregation, the ATS-DA, which adaptively configures its length of timeout according to changing data patterns. The ATS-DA decreases the timeout when the variance of the received data (data variation) from children is lower than a pre-defined threshold because there are not any noticeable events, which reduces the consumed power and improves transmission latency. The ATS-DA, however, increases the timeout when data variation is more than the pre-defined threshold in order to fulfill more accurate data aggregation. Extensive simulation work under various workloads has revealed that ATS-DA not only enhances data accuracy by 33%, but also it improves power consumption and transmission latency by 5% and 58% respectively, as compared with the previous cascading timeout scheduling scheme.

An energy-efficient k-disjoint-path routing algorithm for reliable wireless sensor networks

Wireless sensor networks are subject to sensor node and link failures due to various reasons. This paper proposes an energy-efficient, k-disjoint-path routing algorithm that adaptively varies the number of disjoint paths (k) according to changing data patterns and a target-delivery ratio of critical events. The proposed algorithm sends packets through a single path (k=1) under no occurrence of critical events, whereas it sends through k disjoint paths (k>1) under the occurrence of critical events, where k is computed from a welldefined fault model and the target delivery ratio. Note that the proposed algorithm detects the occurrence of critical events by monitoring changing data patterns. Our simulations reveal that the proposed algorithm not only guarantees the target delivery ratio as much as a multi-path routing algorithm, but also makes energy consumption and average delay as low as a single-path routing algorithm.

A Lightweight and Effective Jamming Detection in Electronic Shelf Label Systems

Modern retailers use electronic shelf label (ESL) systems to display and automatically update price information in supermarkets, thus, reducing manual labor and maintenance expenses. ESL systems usually consist of thousands of devices periodically communicating via radio channel in 2.4 GHz ISM band. Since ESLs are deployed in open environment, they are susceptible to many attacks that threaten to wireless sensor networks (WSNs) operation. The paper is devoted to the analysis of different jamming strategies, threatening to ESL system environment, and proposes fast, reliable and lightweight jamming detection method, suitable for the ESL systems. The suggested technique does not use additional hardware or require extra communication costs; its computational requirements are negligible. Its performance was evaluated by extensive simulations in Castalia-1.3 simulator.

Reliable data aggregation protocol for ad-hoc sensor network environments

In sensor network environments, sensor nodes have limited power because of their resource constraints. Therefore it is important to efficiently use their power in sensor networks. Power consumption of sensor node is closely related to its communication operation. So, we need to reduce the communication operation in order to minimize the power consumption. And sensor networks are inherently unreliable because radio transmission can easily fail, nodes can move, and so on. In this paper, we propose a reliable data aggregation protocol in order to overcome these problems. This protocol performs the routing and the query insertion process at the same time to minimize the packet loss caused by network changes. Also, this protocol removes the communication operations caused by the periodic routing without query

Biologically Motivated Trainable Selective Attention Model Using Adaptive Resonance Theory Network

In this paper, we propose a trainable selective attention model that can inhibit an unwanted salient area and only focus on an interesting area in a static natural scene. The proposed model was implemented by the bottom-up saliency map model in conjunction with the adaptive resonance theory (ART) network. The bottom-up saliency map model generates a salient area based on intensity, edge, color and symmetry feature maps, and human supervisor decides whether the selected salient area is important. If the selected area is not interesting, the ART network trains and memorizes that area, and also generates an inhibit signal so that the bottom-up saliency map model does not have attention to an area with similar characteristic in subsequent visual search process. Computer simulation results show that the proposed model successfully generates the plausible sequence of salient region that does not give an attention to an unwanted area.

Mono-camera based side vehicle detection for blind spot detection systems

This paper proposes a vision-based side vehicle detection for blind spot detection systems. The proposed algorithm uses a HoG cascade classifier in order to detect vehicles, and tracks the detected vehicles with Kalman filter. The proposed algorithm performs a periodical vehicle detection instead of every frame vehicle detection. And the proposed algorithm reduces the detecting image size by downscaling the original image and setting the region of interest where vehicles can exist. As a result, we can reduce the processing time for vehicle detection. Also, the proposed algorithm uses a false alarm reducing methods by control the reliability points at vehicle tracking. We evaluated the performance of the proposed algorithm in terms of processing time and detection ratio. At target board, the proposed algorithm has 40 frames per second, which meets the real time requirements of the ADAS systems. The detection ratio of the proposed algorithm is over 96 % at both original image size and downscale image size.

Table-comparison prefetching in VIA-based parallel file system

Abstract : A parallel file system is normally used to support excessive file requests from parallel applications in a cluster system, whereas prefetching is useful for improving the file system performance. This paper proposes a table-comparison prefetching policy that is particularly suitable for parallel scientific applications and multimedia web services in a VIA-based parallel file system. VIA relieves the communi-cation overhead of traditional communication protocols, such as TCP/IP. The proposed policy introduces a table-comparison method to predict data for prefetching. In ad-dition, it includes an algorithm to determine whether and when prefetching is performed using the current available I/O bandwidth. Experimental results confirmed that the use of the proposed prefetching policy in a VIA-based parallel file system produced a higher file system performance.

Health Monitoring System based on Wireless Sensor Network for Weapon Asset

This paper introduces a health monitoring system based on a wireless sensor network for weapon asset. This system can estimate the remaining lifetime and decide what should be done and when should it be done using the environmental conditions such as temperature, humidity and shock for weapon assets by sensor tag. And we describes its operating scenario and routing method for this system. Finally we introduce the developments of the sensor tag, portable reader, gateway and monitoring server.

Seamless multimedia streaming services with the two-tiered proxy system

In this paper, we propose the two-tiered proxy system(TOPS) that supports seamless multimedia service in mobile computing environment. TOPS is composed of a media proxy and mobile proxy. The media proxies are responsible for media streaming service. The mobile proxies support the wireless communication and mobility of the mobile host. The media proxy manages all media services in its management domain. Therefore, the handoff delay and multiple-transmission problem do not happen in the TOPS. We show that the initial delay of media service, handoff delay, and network traffic is reduced in our simulation