Inbum Jung

Adaptive-compression based congestion control technique for wireless sensor networks.

Congestion in a wireless sensor network causes an increase in the amount of data loss and delays in data transmission. In this paper, we propose a new congestion control technique (ACT, Adaptive Compression-based congestion control Technique) based on an adaptive compression scheme for packet reduction in case of congestion. The compression techniques used in the ACT are Discrete Wavelet Transform (DWT), Adaptive Differential Pulse Code Modulation (ADPCM), and Run-Length Coding (RLC). The ACT first transforms the data from the time domain to the frequency domain, reduces the range of data by using ADPCM, and then reduces the number of packets with the help of RLC before transferring the data to the source node. It introduces the DWT for priority-based congestion control because the DWT classifies the data into four groups with different frequencies. The ACT assigns priorities to these data groups in an inverse proportion to the respective frequencies of the data groups and defines the quantization step size of ADPCM in an inverse proportion to the priorities. RLC generates a smaller number of packets for a data group with a low priority. In the relaying node, the ACT reduces the amount of packets by increasing the quantization step size of ADPCM in case of congestion. Moreover, in order to facilitate the back pressure, the queue is controlled adaptively according to the congestion state. We experimentally demonstrate that the ACT increases the network efficiency and guarantees fairness to sensor nodes, as compared with the existing methods. Moreover, it exhibits a very high ratio of the available data in the sink.

Speedy Routing Recovery Protocol for Large Failure Tolerance in Wireless Sensor Networks

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols.

Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors

Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection.

Traffic-Aware Routing Protocol for Wireless Sensor Networks

In wireless sensor networks, when a sensor node detects events in the surrounding environment, the sensing period for learning detailed information is likely to be short. However, the short sensing cycle increases the data traffic of the sensor nodes in a routing path. Since the high traffic load causes a data queue overflow in the sensor nodes, important information about urgent events could be lost. In addition, since the battery energy of the sensor nodes is quickly exhausted, the entire lifetime of wireless sensor networks would be shortened. In this paper, to address these problem issues, a new routing protocol is proposed based on a lightweight genetic algorithm. In the proposed method, the sensor nodes are aware of the data traffic rate to monitor the network congestion. In addition, the fitness function is designed from both the average and the standard deviation of the traffic rates of sensor nodes. Based on dominant gene sets in a genetic algorithm, the proposed method selects suitable data forwarding sensor nodes to avoid heavy traffic congestion. In experiments, the proposed method demonstrates efficient data transmission due to much less queue overflow and supports fair data transmission for all sensor nodes. From the results, it is evident that the proposed method not only enhances the reliability of data transmission but also distributes the energy consumption across wireless sensor networks.

Reliable Asynchronous Image Transfer Protocol in Wireless Multimedia Sensor Networks

In the paper, we propose a reliable asynchronous image transfer protocol, RAIT. RAIT applies a double sliding window method to node-to-node transfer, with one sliding window for the receiving queue, which is used to prevent packet loss caused by communication failure between nodes, and another sliding window for the sending queue, which prevents packet loss caused by network congestion. The routing node prevents packet loss between nodes by preemptive scheduling of multiple packets for a given image. RAIT implements a double sliding window method by means of a cross-layer design between the RAIT layer, routing layer, and queue layer. We demonstrate that RAIT guarantees a higher reliability of image transmission compared to the existing protocols.

Energy Effective Time Synchronization inWireless Sensor Network

Advance in processor, memory and wireless communication technique have led to an increase of economical and small wireless sensor nodes. To provide the right responses quickly for the diverse events, wireless sensor nodes have cooperation with together. For successful cooperation, the time synchronization among sensor nodes is an important requirement for application execution. In wireless sensor networks, message packets are used for the time synchronization. However, the transmission of message packets dissipates the battery energy of wireless sensor nodes. Since wireless sensor nodes works on the limited battery capacity, the excessive use of message packets has a negative impact upon their lifetime. In this paper, reference interpolation protocol is proposed for reducing the number of message packets for the time synchronization. The proposed method performs time interpolation between the time of reference packets and the global time of the base station. The proposed method completes the synchronization operation with only two message packets. Due to the simple synchronization procedure, our method greatly reduces the number of synchronization messages. From the decrease in the transmission of message packets, the convergence time among wireless sensor nodes is shortened and the lifetime of wireless sensor nodes is also prolonged as much as the amount of saved battery energy.

Traffic Information Acquisition System with Ultrasonic Sensors in Wireless Sensor Networks

Existing systems for traffic information acquisition have high costs and low scalability owing to their characteristics such as large size, wired power supplies, and wired communication. To achieve low costs and high scalability, the use of traffic information acquisition systems based on wireless sensor networks (WSNs) has been suggested. However, WSN-based systems have important issues, such as low computing power, limited battery capacity, and high transmission delay. Existing studies on WSN-based acquisition systems have not considered all three of these problems together. Moreover, most studies have focused on theoretical problems rather than practical ones. Therefore, we propose a new system that considers all three limitations of WSN-based systems. In our experiments, we installed our system on real roads for an accurate evaluation. The results show that our system has a high detection accuracy, low power consumption, and low transmission delay.

Variable Speed Limit to Improve Safety near Traffic Congestion on Urban Freeways

Recently, the convergence of information technology with biotechnology, nano-technology, or other technologies has been creating a new paradigm. In the field of transportation, intelligent transport systems (ITSs)-a convergence of information technologies and transportation systems-have been studied. The VSL is one ITS technologies that aims to improve the safety and efficiency of transportation while controlling the speed limit according to traffic circumstances. Existing studies for VSL algorithms have considered only one station to control the traffic. However, it is not appropriate for an urban freeway to be installed with many stations. In this paper, a new VSL algorithm is proposed to enhance the effectiveness of VSL for multiple stations. It is based on the cooperation of stations and the real-time road information. The proposed algorithm consists of 4 steps: first is a ”searching bottleneck station,” second is a ”calculating a size of congestion,” third is a ”calculating the number of controlled stations,” fourth is a ”calculating VSL.” In our experiments, the microscopic traffic simulator VISSIM performed our modeling works. The results show that the proposed algorithm improves safety on roads with minimum additional travel time.

Traffic measurement on multiple drive lanes with wireless ultrasonic sensors.

An automated traffic measuring system for use on multiple drive lanes is proposed in this paper. This system, which uses ultrasonic sensors and a lateral scanning method, is suitable for use on real traffic roads. The proposed system can be easily established and maintained in various roadway environments. In addition, the system can be adjusted to measure traffic volumes according to the size and number of drive lanes. This paper describes the results of an experiment that the lateral scanning method can be easily applied to real traffic roads and provide a low error rate and real-time responses. This system can play an important role in accurately measuring traffic volumes as part of an intelligent transportation system.

Load distribution strategies in cluster-based transcoding servers for mobile clients

The recent advance in wireless network technologies has enabled the streaming media service on the mobile devices such as PDAs and cellular phones. Since the wireless network has low bandwidth channels and mobile devices are actually composed of limited hardware specifications, the transcoding technology is needed to adapt streaming media to the given mobile devices. When large scale mobile clients demand the streaming service, load distribution strategies among transcoding servers highly impact on the total number of QoS streams. In this paper, the resource weighted load distribution strategy is proposed for the fair load balancing and the more scalable performance in cluster-based transcoding servers. Our proposed strategy is based on the weight of resources consumed for transcoding to classified client grades and the maximum number of QoS streams actually measured in transcoding servers. The proposed policy is implemented on cluster-based transcoding system. In experiments, we evaluate its fair load distribution and scalable performance according to the increase of transcoding servers.