Dong-Ook Seong

Disjointed Multipath Routing for Real-Time Data in Wireless Multimedia Sensor Networks

Wireless multimedia sensor networks with sensing and processing abilities of multimedia data have recently emerged as one of the most important technologies for high quality monitoring. The routing scheme for multimedia data is an important research issue addressed in wireless multimedia sensor networks. In this paper, we propose a disjointed multipath routing scheme for real-time data transmission in wireless multimedia sensor networks. The proposed scheme uses a hybrid routing protocol based on Bluetooth and Zigbee in order to overcome the limitation of low bandwidth in conventional sensor networks. The proposed scheme also performs disjointed multipath routing based on competition to alleviate the delay of routing path setup. To show the superiority of our proposed scheme, we compare it with the existing scheme through performance evaluation. Our experimental results show that our proposed scheme reduces the end-to-end delay by about 30% and the routing path setup costs by about 22% over the existing scheme. Our scheme also increases data reception rates by about 690% over the existing scheme on average.

Data-aware top-k monitoring in wireless sensor networks

Top-k queries are important to many wireless sensor applications. Conventional Top-k query processing algorithms install a filter at each sensor node and suppress unnecessary sensor updates. However, they have some drawbacks that the sensor nodes consume energy extremely to probe sensor reading or update filters. Especially, it becomes worse, when the variation ratio of top-k result is higher. In this paper, we propose a novel top-k query processing algorithm for energy-efficiency. First, each sensor determines its priority as the order of data gathering. Next, sensor nodes that have higher priority transmit their sensor readings to the base station until gathering k sensor readings. In order to show the superiority of our query processing algorithm, we simulate the performance with the existing query processing algorithms. As a result, our experimental results show that the network lifetime of our method is prolonged largely over the existing method.

Sensor Positioning Scheme using Density Probability Models in Non-uniform Wireless Sensor Networks

In wireless sensor networks, a positioning scheme is one of core technologies for sensor applications such as disaster monitoring and environment monitoring. The One of the most positioning scheme, called DV-HOP does not consider non-uniform sensor networks that are actual distributed environments. Therefore, the accuracy of the existing positioning scheme is low in non-uniform network environments. Moreover, because it requires many anchor nodes for high accuracy in non-uniform network environments, it is expensive to construct the network. To overcome this problem, we propose a novel sensor positioning scheme using density probability models in non-uniform wireless sensor networks. The proposed scheme consists of the density probability model using the deployment characteristics of sensor nodes and the distance refinement algorithm for high accuracy. By doing so, the proposed scheme ensures the high accuracy of sensor positioning in non-uniform networks. To show the superiority of our proposed scheme, we compare it with the existing scheme. Our experimental results show that our proposed scheme improves about 44% accuracy of sensor positioning over the existing scheme on average even in non-uniform sensor networks.

Huffman coding algorithm for compression of sensor data in wireless sensor networks

Sensor data exhibit strong correlation in both space and time. Many algorithms have been proposed to utilize these characteristics. However, each sensor just utilizes neighboring information, because its communication range is restrained. Information that includes the distribution and characteristics of whole sensor data provides other opportunities to enhance the compression technique. In this paper, we propose an orthogonal approach for compressing sensor readings based on a novel feedback technique. That is, the base station or a super node generates Huffman code for the compression of sensor data and broadcasts it into sensor networks as feedback information. All sensor nodes that have received the information compress their sensor data and transmit them to the base station. We call this approach as feedback-diffusion and this modified Huffman coding as sHuffman coding. In order to show the superiority of our approach, we compare it with the existing data compression algorithms in terms of the lifetime of the sensor network. As a result, our experimental results show that the whole network lifetime was prolonged by about 30%.

A Sensor Positioning Scheme with High Accuracy in Nonuniform Wireless Sensor Networks

In wireless sensor networks, a geographical positioning scheme is one of core technologies for sensor applications such as disaster monitoring, environment monitoring, and military services. For this reason, the research for range-free positioning schemes had progressing actively. And a density probability scheme based on the central limit theorem and normal distribution theory has been proposed to improve the location accuracy in nonuniform sensor network environments. The density probability scheme estimates 1-hop distance by using communication between nodes. After that, it estimates the final position of an unknown node. But the density probability scheme has a problem that it has equivalent 1-hop distance for all of nodes in the same area. To overcome this problem, we propose a novel sensor positioning scheme in non-uniform wireless sensor networks. As a result, the proposed scheme ensures the high accuracy of sensor positioning in non-uniform networks. To show the superiority of our proposed scheme, we compare it with the existing scheme such as DV-based position scheme. Our experimental results show that the proposed scheme improves by about 36% sensor positioning accuracy over the existing scheme on average even in non-uniform wireless sensor networks.

An Efficient Hierarchical Multi-Hop Clustering Scheme in Non-uniform Large Wireless Sensor Networks

In wireless sensor networks, an energy efficient data gathering scheme is one of core technologies to process a query. The cluster-based data gathering methods minimize the energy consumption of sensor nodes by maximizing the efficiency of data aggregation. However, since the existing clustering methods consider only uniform network environments, they are not suitable for the real world applications that sensor nodes can be distributed unevenly. Recently, a balanced multi-hop clustering method in non-uniform wireless sensor networks was proposed. The proposed scheme constructs a cluster based on the logical distance to the cluster head using a min-distance hop count. But this scheme also increases the occurrence of orphan nodes in case of expanding a cluster in large sensor network environments. To solve such a problem, we propose a hierarchical multi-hop clustering scheme that considers the scalability of a cluster in non-uniform large wireless sensor network environments. Our proposed scheme can decrease the number of orphan nodes and has sufficient scalability because our scheme selects member nodes by dividing an angle range in the regular hop count based on min-distance hop count. It is shown through performance evaluation that the orphan nodes of the proposed scheme decrease about 41 % on average over those of the existing methods.

An Energy-Efficient Data Compression and Transmission Scheme in Wireless Multimedia Sensor Networks

In recent years, the demand of multimedia data in wireless sensor networks has been significantly increased for the environment monitoring applications that utilize sensor nodes to collect multimedia data such as sound and video. However, the amount of multimedia data is very large. Therefore, if the data transmission schemes in traditional wireless sensor networks are applied in wireless multimedia sensor networks, the network lifetime is significantly reduced due to excessive energy consumption on particular nodes. In this paper, we propose a novel energy-efficient data compression scheme for multimedia data transmission in wireless sensor networks. The proposed scheme compresses and splits the multimedia data using the Chinese Remainder Theorem (CRT) and transmits the bit-pattern packets of the remainder to the base station. As a result, it can reduce the amount of the transmitted multimedia data. To show the superiority of our proposed scheme, we compare it with the existing scheme. Our experimental results show that our proposed scheme reduces about 71 % in the amount of transmitted data and increases about 188 % in the ratio of surviving nodes over the existing scheme on average.

An Energy-Efficient Multiple Path Data Routing Scheme Using Virtual Label in Sensor Network

The multi-path routing schemes that assigns labels to sensor nodes for the reliability of data transmission and the accuracy of an aggregation query over the sensor networks where data transfer is prone to defect have been proposed. However, the existing schemes have high costs for reassigning labels to nodes when the network topology is changed. In this paper, we propose a novel routing method that avoids duplicated data and reduces the update cost of a sensor node. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through the various experiments. Our experimental results show that our proposed method reduces about 95% the amount of the transmitted data for restoration to node failure and about 220% the amount of the transmitted data for query processing over the existing method on average.

Retracted: a data gathering method based on a mobile sink for minimizing the data loss in wireless sensor networks

The sensor nodes near to the fixed sink node suffer from the quickly exhausted energy. For this, many methods have been researched to distribute the energy consumption into all wireless sensor nodes using a mobile sink. Since the mobile sink changes its location in the network continuously, it has limited time to communicate with the sensor nodes and needs the time to move to each sensor node. Therefore, before the mobile sink approaches the sensor node, the node can collect huge data by event occurrence. It causes the memory overflow of the sensor node and then the data loss. We propose a novel data gathering method based on a mobile sink considering the data loss in wireless sensor networks. The proposed scheme actively sends the stored data to the mobile sink by considering the amount of collected data in the cluster header and the mobile patterns of the sink node. By doing so, it minimizes the data loss of each sensor node. To show the superiority, we compare it with the existing scheme. Our experimental results show that our proposed scheme minimizes the data loss and has similar network lifetime over the existing scheme based on a mobile sink.

A Positioning Scheme Using Sensing Range Control in Wireless Sensor Networks

In wireless sensor networks, the geographical positioning scheme is one of core technologies for sensor applications such as disaster monitoring and environment monitoring. For this reason, studies on range-free positioning schemes have been actively progressing. The density probability scheme based on central limit theorem and normal distribution was proposed to improve the location accuracy in non-uniform sensor network environments. The density probability scheme measures the final positions of unknown nodes by estimating distance through the sensor node communication. However, it has a problem that all of the neighboring nodes have the same 1-hop distance. In this paper, we propose an efficient sensor positioning scheme that overcomes this problem. The proposed scheme performs the second positioning step through the sensing range control after estimating the 1-hop distance of each node in order to minimize the estimation error. Our experimental results show that our proposed scheme improves the accuracy of sensor positioning by about 9% over the density probability scheme and by about 48% over the DV-HOP scheme.