Yoon G. Kim

Vehicle Identification using Discrete Spectrums in Wireless Sensor Networks

We studied the possibility of using wireless sensor networks for vehicle identification in a large open field. This is exciting research in that it not only presents a challenge but has practicality. The challenge here is to develop algorithms and/or protocols for sensor nodes to execute a given task. Since each sensor node has limited computation and communication capabilities, these limitations prohibit the use of algorithms and/or protocols developed for conventional computers and networks. Each sensor is dispensable and easily deployable, it can do meaningful work when it is collaborated as a networked cluster; therefore it is very practical in application. Our goal is to identify vehicles in real time using acoustic signal sensors and wireless networks. Our contribution in this paper is three fold. First, we developed a simple vehicle sound identification algorithm enough to be implemented for capacity limited sensor nodes. Second, we proposed architecture and protocols of wireless sensor networks for vehicle identification using this developed sound classification algorithm. Third, we proposed a cooperation model among sensors to expedite the classification process. Our preliminary results show the proposed architecture and protocols are promising.

Vehicle identification using wireless sensor networks

We studied the possibility of using wireless sensor networks for vehicle identification. It is interesting because it is not only challenging but also practical. It is challenging to develop algorithms and/or protocols for sensor nodes to execute since each sensor node has limited computation and communication capabilities, and these limitations prohibit the use of algorithms and/or protocols developed for conventional computer and networks. It is practical since each sensor is dispensable and easily deployable, yet it can do meaningful works when it is collaborated as a networked cluster. Our goal is to identify vehicles in real time using acoustic signal sensors and wireless networks. Our contribution in this paper is two fold. First, we develop a simple vehicle sound identification algorithm enough to be implemented on capacity limited sensor nodes. Second, we propose architecture and protocols of wireless sensor networks for vehicle identification using this developed sound classification algorithm. Our preliminary results show the proposed architecture and protocols are promising.

Congestion Prediction of Self-Similar Network through Parameter Estimation

In a state of emergency, in complex and dynamic situations where packet delay increases and congestion builds up, certain network nodes may not to able to handle the traffic load. To avoid the congestion build-up in advance, it is mission critical to predict the symptoms of network traffic and to preemptively alter the routing paths to allow a smooth and efficient flow of data packets for effective situation management. In this paper, we have developed a practical methodology for estimation of key parameters of self-similar network traffic using index of dispersion for counts and coefficient of determination. Self-similarity causes performance degradation in the queueing delay and buffer overflow at routers and at switches. We proved the impact of Hurst parameter and fractal onset time on the average queueing delay and the waiting-time distribution of self-similar traffic, utilizing experimental queueing analysis. Based on the understanding obtained, we can predict the congestion of data network in advance through estimation of traffic parameters. In addition, the results of this study on the delay provide a practical means of finding a lower delay path in data networks under the self-similarity

On the prediction of average queueing delay with self-similar traffic

Recent studies on a wide range of network traffic measurements including LAN and WAN have revealed the presence of self-similarity. These types of traffic hold statistical similarity across multiple time scales. Burstiness is retained even with the aggregating self-similar traffic. This property degrades the performance of a network. The queueing delay is one of the performance measures. In this study, a G/M/1 queueing model is used to model a network with self-similar traffic. The results of this study demonstrate that the delay exhibits a rise as degree of self-similarity increases. We compare an analytic average queueing delay of the self-similar traffic to the delay of simulated model to obtain a useful method for the delay prediction. By adjusting a single parameter of the truncated power-tail (TPT) distributions, we can make the analytic curve follow the simulation results. This allows us to predict the delay by computing the TPT once we measure the Hurst parameter of an input traffic and its arrival rate, and the utilization of a router. Our results can benefit control, design, and resource allocation of high-speed networks.

Prediction-based routing through least cost delay constraint

Summary form only given. To control data network for a delay constraint application, it is necessary to understand the behavior of packet delay and the network traffic. In data network, the type of service (TOS) bits are included in the IP header to allow a router to construct various shortest path first (SPF) trees on various quality of service (QoS) needs (e.g., minimum delay). The average queueing delay is a major contributor to the packet delay due to the fact that the queueing delay increases rapidly as the utilization of a router increases. A number of studies of traffic measurements have established the presence of self-similarity that causes performance degradation including amplified queueing delay. A cost function is proposed to determine a metric in a routing table through the prediction of the average queueing delay. From this, the end-to-end packet delays in a simple data network are analyzed by applying prediction-based routing through a cost function using least cost delay constraint. By comparing the average packet delay of TOS 0 (default) routing with that of prediction-based TOS 16 (minimize delay) routing, we can demonstrate the performance improvement on the average packet delay with the presence of self-similar traffic.

Proportional Nested Deficit Round Robin: Improving the Latency of Packet Scheduler with an O(1) Complexity

In recent years, many fair packet scheduling algorithms have been proposed for switches and routers to provide the quality of service (QoS) guarantees required by many applications. In addition to the fairness and low end-to-end delay that these algorithms have to have, simplicity and scalability are two significant factors that play an important role. In this paper, we present a new scheduling discipline called proportional nested deficit round robin (PNDRR), which has a low latency and reduces burstiness. PNDRR is a class of nested-DRR in which each DRR round is split into some smaller inner rounds. However, unlike nested-DRR, flows receive credits proportional to their deficit counters in each inner round. PNDRR takes advantage of the input traffic pattern and decreases the serving size of flows when the input traffic contains many small packets. This helps to interleave packets in many practical scenarios, such as the Internet, where the majority of packets are relatively small. The latency and fairness of PNDRR are studied and compared to other algorithms using simulation. PNDRR has a per-packet computational complexity of O(1)

Microcontroller-controlled constant current DC-DC converter modules for driving a multi-wavelength LED array

This paper presents the design and validation of constant current DC-DC converter modules which provide constant current operation for driving an LED array that is comprised of multiple wavelength LEDs. A high-power LED-based light source can provide optical energy to test solar panels indoors. For this application, the light source, whose optical spectrum and irradiance that is similar to solar rays, is required. The light source would consist of various types of LEDs whose wavelengths and intensities are different from one another and so the power source needs to supply a specific current and voltage for each LED. The described module consists of a DC-DC converter and constant current control circuits, which are controlled by a microcontroller. Both circuits of the module set the modules output current and voltage levels by adjusting the feedback resistances of the step-down controller and the DC amplifier gain. Two resistances are configured by a digital potentiometer IC through a microcontroller. To control multiple various types of LEDs efficiently the I2C serial bus is used. Up to 128 described modules can be attached and controlled by a single microcontroller. To verify the operation and performance, a printed-circuit board prototype has been built and tested; simulation and experimental results are presented. The measurement results show that the module successfully drives a high-power LED with the constant current operation controlled by a microcontroller.

Modeling and simulation of a solar simulator with multi-wavelength high-power LEDs

This paper presents the modeling and simulation of a solar simulator that is comprised of many high-power LEDs of various wavelengths. A solar simulator is a light source which can provide optical power to measure the characteristics of solar panels indoors. For this application, the light source requires an optical spectrum and irradiance that is similar to solar rays. A high-power LED-based light source is considered to provide a light-weight design, higher luminous efficacy, and longer operating life. To match the solar spectrum, the light source in the form of an LED array needs various types of LEDs whose wavelengths and intensities are different from one another. The proposed solar simulator includes a highdensity LED fixture containing a 5 by 5 array of high-intensity LEDs. The square fixture measures 2.5 inches (63.5 mm) per side. The goal of this work is to find the radiometric power and optimum layout for an array of high-power LEDs in order to generate an optical spectrum similar to solar rays with uniform irradiance. The fixture has 18 high-power LEDs of 18 different types in the 5 by 5 array. Each LED in the fixture has a specific wavelength and intensity set by a 3D optical modeling tool. This work presents the parameters that affect spectral match and uniformity of irradiance. The parameters are the number of different LEDs used, their intensities, and arrangement. The number of LEDs and their intensities for a spectral match were computed by a developed algorithm. Modeling an LED array for spectral match, color quality, and irradiance were carried out by a 3D optical modeling tool. The results include the spectral and irradiance distributions of the proposed solar simulator.

Development of a programmable DC-DC converter module for driving a scalable LED array

This paper presents programmable DC-DC converter modules which provide stable power to drive multiple high-power LEDs. When high-power LEDs are used to form a light source, which consists of various types of intensity and wavelengths, DC-DC converter modules can be used to drive the LEDs which then provide optical energy to test photovoltaic cells. To provide similar optical spectrums as seen by solar rays, the power supply for each LED will need to supply a specific voltage and current accordingly. The described module consists of a programmable controller and DC-DC power converters. Each controller manages three DC-DC converters by adjusting the feedback resistances of the converters through a microcontroller. Additional modules can be added to drive an LED array of any size. To verify the operation and performance, a prototype of six modules consisting of eighteen DC-DC converters has been built and tested. The results show that all of eighteen individual LEDs are successfully driven by six modules and eighteen converters.

Traffic Dispatching Algorithm in Three-Stage Switch

One of the challenges in a three-stage switch is how to distribute the traffic between the second stage switches. The dispatching algorithm affects the queue levels in the second stage and has a direct impact on the queueing delay. In this study, a dispatching algorithm called Stage 2 Queue Balancer (S2QB) is proposed. The proposed algorithm distributes flows packet-by-packet between the second stage switches. The results of this study demonstrate that queues in the second stage remain in balance and the delay is minimized. S2QB does not add any overhead.