Chaewoo Lee

The Slotted-LBT: A RFID Reader Medium Access Scheme in Dense Reader Environments

RFID technology as a core technology for realizing ubiquitous environment is emerged. Although it was developed rapidly in the past few years, the read rate is still a concern in the RFID technology adoption. At the same time it is also a technical issue which must be resolved. In order to increase the read rate, a number of researches have focused on the air protocol method and the medium access method. In this paper, we propose a distributed Slotted-LBT method to increase the number of readers which can read tags simultaneously, to provide a stable channel access time, and to reduce the interference among readers by using a channel zone. From the results in this research, compared with the existing normal LBT method, the proposed Slotted-LBT method shows that the coefficient of variation for the channel access time is reduced from 96% to 38% and the effect of interference is reduced by 28.48%. Besides, since each channel can be controlled separately, we can use categorized channels according to demanding features of manifold applications.

Energy consumption and lifetime analysis in clustered multi-hop wireless sensor networks using the probabilistic cluster-head selection method

Clustering sensor nodes into groups is an effective way of reducing the transmission of duplicated information in energy-constraint wireless sensor networks (WSNs). The performance of clustering is greatly influenced by the selection of cluster-heads, which are in charge of creating clusters and controlling member nodes. In selecting cluster-heads, a probabilistic method where each sensor node selects itself as a cluster-head with a given probability is often used in large-scale and dense WSNs because it enables all nodes to independently decide their roles while keeping the signaling overhead low. In this method, the probability of being a cluster-head should be optimally chosen to maximize the energy efficiency of the nodes. In this article, we propose a novel energy model to estimate the energy consumed in a multi-hop WSN clustered with probabilistic cluster-head selection. Then, based on our model, we determine optimal probability that maximizes the lifetime of a network. Simulation results achieved by the Monte Carlo method show that our model estimates well in energy consumption from a network and also predicts the optimal clustering probability accurately.

An Efficient Flooding Algorithm for Position-Based Wireless Ad Hoc Networks

A flooding which is one of the packet transmission methods broadcasts a packet to all nodes within a transmission range and can guarantee a short delay. However, the fundamental flooding algorithm has a shortcoming that causes excessive traffic because all nodes transmit a packet at least once. In this paper, we propose a totally fresh approach to constrain duplicate transmission by searching neighboring nodes that already received the identical packet by using nodes geographical information. Additionally, to reduce a delay, we propose a novel flooding algorithm where a node which receives a broadcasted packet chooses and allocates a priority to one of its neighbor nodes and then the node which has a priority broadcasts the packet promptly to its neighboring nodes. The simulation results show that the proposed algorithm can distribute packets through a lower number of total packet transmissions and faster delivery time than the existing algorithm.

Reliable anchor node based range-free localization algorithm in anisotropic wireless sensor networks

In the wireless sensor networks, location based applications require an accurate localization algorithm. To estimate location, each normal node, which do not know its own location, uses estimated distances to anchor nodes which have their own location. Hence, the estimation of distance is a key issue in the wireless sensor networks localization. Most previous works assume isotropic networks where approximate the shortest path distances to the Euclidian distances. These approaches cannot obtain accurate distance estimations in anisotropic networks where the shortest path distances are not linearly proportion to the Euclidian distances. In the anisotropic networks, the shortest path between two nodes may be detoured and its length may be estimated much larger than the corresponding Euclidean distance. Because of the phenomenon, it is important to select reliable anchor nodes which offer the precisely estimated distance. In this paper, we propose a reliable anchor node selection algorithm in the anisotropic networks. Each normal node selects the three anchor nodes with Triangular rule to enhance localization accuracy in the proposed algorithm. We also show that our scheme is reasonable through mathematical observation.

Mobile Gateway for Ubiquitous Health Care System Using ZigBee and Bluetooth

A ubiquitous health care system takes the advantage of portability and small size of wireless sensor nodes to provide remote health care services and real-time health monitoring. A gateway is needed to mediate communication between a local sensor network and remote data consumers. In current implementations of ubiquitous health care systems ZigBee-based sensors are often used to gather vital sign data such as ECG and heart rate. Transferring large quantities of vital signs from a ZigBee-based sensor sink node to a gateway requires a bandwidth that ZigBee alone is not able to provide. In this paper, we present a technical design of a Bluetooth-based mobile gateway that bridges the connection between a sensor network and the Internet. Our system enables ubiquitous health care experience while providing a platform for additional services such as alarms, notifications and analysis of medical data. Controlling a sensor network from the mobile gateway is also possible. The flexible design of the system does not restrict its usage only to health care services - the gateway can be configured to work with any kind of sensor network having a sink node with Bluetooth capability.

Range-free localization with isotropic distance scaling in wireless sensor networks

A number of range-free localization algorithms have been proposed for various applications and approached in wireless sensor networks. Range-free schemes use hop count information of shortest paths between nodes as a distance metric and plus scaling to estimate the physical location. However, since scaling is performed in terms of a single anchor or local topology, location errors can be introduced by scaling. In this paper, we propose a novel range-free localization algorithm to reduce errors in scaling by deriving the optimal scaling factor for one hop with respect to all anchors in the network. The scaling factor can be optimized by minimizing the sum of squares of distance errors between all anchors. We evaluate the proposed algorithm through simulations under a variety of node density and anchor ratio.

Game theory-based resource allocation strategy for clustering based wireless sensor network

We discuss the use of Nash bargaining solution (NBS) for analyzing clustering based sensor network. We model the energy consumption in the cluster members along with that for data transmission. We do not consider the energy of cluster heads and sink node because the energy consumption of cluster heads can be solved by a similar scheme with that of cluster members. Since in our model the energy transmission is achieved by single-hop, the first cluster members failure does not affect other cluster members. Therefore, the existing solution proposed in the wireless sensor networks connected by multi-hop can not be proper because of the single hop transmission of cluster members with its cluster head. In this paper, we analyze the resource allocation between clusters with NBS for a fair and efficient solution. We demonstrate that the problem of the model we deal with is convex and our solution can find an optimal point.

An MILP-Based Cross-Layer Optimization for a Multi-Reader Arbitration in the UHF RFID System

In RFID systems, the performance of each reader such as interrogation range and tag recognition rate may suffer from interferences from other readers. Since the reader interference can be mitigated by output signal power control, spectral and/or temporal separation among readers, the system performance depends on how to adapt the various reader arbitration metrics such as time, frequency, and output power to the system environment. However, complexity and difficulty of the optimization problem increase with respect to the variety of the arbitration metrics. Thus, most proposals in previous study have been suggested to primarily prevent the reader collision with consideration of one or two arbitration metrics. In this paper, we propose a novel cross-layer optimization design based on the concept of combining time division, frequency division, and power control not only to solve the reader interference problem, but also to achieve the multiple objectives such as minimum interrogation delay, maximum reader utilization, and energy efficiency. Based on the priority of the multiple objectives, our cross-layer design optimizes the system sequentially by means of the mixed-integer linear programming. In spite of the multi-stage optimization, the optimization design is formulated as a concise single mathematical form by properly assigning a weight to each objective. Numerical results demonstrate the effectiveness of the proposed optimization design.

Wireless sensor network localization with connectivity-based refinement using mass spring and Kalman filtering

Since many range-free localization algorithms depend on only a few anchors and implicit range estimations, they produce poor results. In this article, we propose a distributed range-free algorithm to improve localization accuracy by using one-hop neighbors as well as anchors. When an unknown node knows which nodes it can directly communicate with, but does not know how far they are exactly placed, the node should have a location having the average distance to all neighbors since the location minimizes the sum of squares of hop distance errors. In the proposed algorithm, each node initializes its location using the information of anchors and updates it based on mass spring method and Kalman filtering with the location estimates of one-hop neighbors until the equilibrium is achieved. Subsequently, the network has the shape of isotropic graph with minimized variance of links between one-hop neighbors. We evaluate our algorithm and compare it with other range-free algorithms through simulations under varying node density, anchor ratio, and node deployment method.

Energy Modeling for the Cluster-Based Sensor Networks

The performance of the clustering scheme is influenced by the cluster-head election method and the size or the number of clusters. Thus we should optimize these factors to maximize the energy efficiency of the clustering scheme. In this paper, we propose a new energy consumption model for the LEACH which is a well-known clustering protocol and determine the optimal number of clusters based on our model. Our model has accuracy over 80% compared with the simulation and is considerably superior to the existing model of the LEACH.