• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.84-92
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• 2018

For large wireless sensor networks running on battery power, the time synchronization of all sensor nodes is becoming a crucial task for waking up sensor nodes with exact timing and controlling transmission and reception timing. However, as network size increases, this synchronization process tends to require long processing time consume significant power. Furthermore, a naïve synchronization scheduler may leave some nodes unsynchronized. This paper proposes a power-efficient scheduling algorithm for time synchronization utilizing the notion of density, which is defined by the number of neighboring nodes within wireless range. The proposed scheduling algorithm elects a sequence of minimal reference nodes that can complete the synchronization with the smallest possible number of hops and lowest possible power consumption. Additionally, it ensures coverage of all sensor nodes utilizing a two-pass synchronization scheduling process. We implemented the proposed synchronization algorithm in a network simulator. Extensive simulation results demonstrate that the proposed algorithm can reduce the power consumption required for the periodic synchronization process by up to 40% for large sensor networks compared to a simplistic multi-hop synchronization method.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.911-923
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• 2010

In wireless sensor networks (WSNs), cluster based data routing protocols have the advantages of reducing energy consumption and link maintenance cost. Unfortunately, most of clustering protocols have been designed for uniformly distributed sensor networks. However, some urgent situations do not allow thousands of sensor nodes being deployed uniformly. For example, air vehicles or balloons may take the responsibility for deploying sensor nodes hence leading a normally distributed topology. In order to improve energy efficiency in such sensor networks, in this paper, we propose a new cluster formation algorithm named DAEEC (Density Aware Energy-Efficient Clustering). In this algorithm, we define two kinds of clusters: Low Density (LD) clusters and High Density (HD) clusters. They are determined by the number of nodes participated in one cluster. During the data routing period, the HD clusters help the neighbor LD clusters to forward the sensed data to the central base station. Thus, DAEEC can distribute the energy dissipation evenly among all sensor nodes by considering the deployment density to improve network lifetime and average energy savings. Moreover, because the HD clusters are densely deployed they can work in a manner of our former algorithm EEVAR (Energy Efficient Variable Area Routing Protocol) to save energy. According to the performance analysis result, DAEEC outperforms the conventional data routing schemes in terms of energy consumption and network lifetime.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.32-38
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• 2012

Each sensor node can know its location in several ways, if the node process the information based on its geographical position in sensor networks. In the localization scheme using GPS, there could be nodes that don't know their locations because the scheme requires line of sight to radio wave. Moreover, this scheme is high costly and consumes a lot of power. The localization scheme without GPS uses a sophisticated mathematical algorithm estimating location of sensor nodes that may be inaccurate. AHLoS(Ad Hoc Localization System) is a hybrid scheme using both GPS and location estimation algorithm. In AHLoS, the GPS node, which can receive its location from GPS, broadcasts its location to adjacent normal nodes which are not GPS devices. Normal nodes can estimate their location by using iterative triangulation algorithms if they receive at least three beacons which contain the position informations of neighbor nodes. But, there are some cases that a normal node receives less than two beacons by geographical conditions, network density, movements of nodes in sensor networks. We propose an indirect localization scheme for low-density sensor nodes which are difficult to receive directly at least three beacons from GPS nodes in wireless network.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.81-84
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• 2005

Various design schemes for network using wireless sensor nodes have been widely studied on the several application areas ranging from the real world information collection to environmental monitor. Currently, the schemes are focused on the design of sensor network for low power consumption, power-aware routing protocol, micro miniature operating system and sensor network middleware. The indoor localization system that identifies the location of the distributed nodes in a wireless sensor network requires features dealing with mobility, plurality and other environmental constraints of a sensor node. In this paper, we present an efficient location system to cope with mobility of multiple mobile nodes by designing a location handler that processes location information selectively depending on the nodes' density in a specific region. In order to resolve plurality of multiple mobile nodes, a routing method for the location system is also proposed to avoid the occurrence of overlapped location data.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.55-66
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• 2012

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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.832-844
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• 2008

Distributed localization algorithms are necessary for large-scale wireless sensor network applications. In this paper, we introduce an efficient node distribution based localization algorithm that emphasizes simple refinement and low system load for low-cost and low-rate wireless sensors. Each node adaptively chooses neighbor nodes for sensors, update its position estimate by minimizing a local cost function and then passes this update to the neighbor nodes. The update process considers a distribution of nodes for large-scale networks which have same density in a unit area for optimizing the system performance. Neighbor nodes are selected within a range which provides the smallest received signal strength error based on the real experiments. MATLAB simulation showed that the proposed algorithm is more accurate than trilateration and les complex than multidimensional scaling. The implementation on MicaZ using TinyOS-2.x confirmed the practicality of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.77-85
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• 2015

Recently, wireless sensor network(WSN) have been used in various fields to implement ubiquitous computing environment. WSN uses small, low cost and low power sensors in order to collect information from the sensor field. This paper proposes a clustering algorithm for energy efficiency of sensor nodes. The proposed algorithm is based on conventional LEACH, the representative clustering protocol for WSN and it prolongs network and nodes life time using sleep technique and changable transmission mode. The nodes of the proposed algorithm first calculate their clustering participation value based on the distance to the neighbor nodes. The nodes located in high density area will have clustering participation value and it can turn to sleep mode. Besides, proposed algorithm can change transmission method from conventional single-hop transmission to multi-hop transmission according to the energy level of cluster head. Simulation results show that the proposed clustering algorithm outperforms conventional LEACH, especially non-uniformly deployed network.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.68-73
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• 2007

Recently, WSN(wireless sensor networks) consists of several sensor nodes in sensor field. And each sensors have the enforced energy constraint. Therefore, it is important to manage energy efficiently. In WSN application system, FEC(Forward error correction) increases the energy efficiency and data reliability of the data transmission. LDPC(Low density parity check) code is one of the FEC code. It needs more encoding operation than other FEC code by growing codeword length. But this code can approach the Shannon capacity limit and it is also can be used to increase the data reliability and decrease the transmission energy. In this paper, the author adopt Linear-Congruence method at generating parity check matrix of LDPC(Low density parity check) codes to reduce the complexity of encoding process and to enhance the energy efficiency in the WSN. As a result, the proposed algorithm can increase the encoding energy efficiency and the data reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.96-116
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• 2016

Sensing coverage is a fundamental issue for Wireless Sensor Networks (WSNs). Several coverage configuration protocols have been developed; most of them presume the availability of precise knowledge about each node location via GPS receivers. However, equipping each sensor node with a GPS is very expensive in terms of both energy and cost. On the other hand, several GPS-less localization algorithms that aim at obtaining nodes locations with a low cost have been proposed. Although their deep correlation, sensing coverage and localization have long been treated separately. In this paper, we analyze, design and evaluate a novel integrated framework providing both localization and coverage guarantees for WSNs. We integrate the well-known Coverage Configuration Protocol CCP with an improved version of the localization algorithm AT-Dist. We enhanced the original specification of AT-Dist in order to guarantee the necessary localization accuracy required by CCP. In our proposed framework, a few number of nodes are assumed to know their exact positions and dynamically vary their transmission ranges. The remaining sensors positions are derived, as accurately as possible, using this little initial location information. All nodes positions (exact and derived) are then used as an input for the coverage module. Extensive simulation results show that, even with a very low anchor density, our proposal reaches the same performance and efficiency as the ideal CCP based on complete and precise knowledge of sensors coordinates.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.54-64
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• 2010

Localization is the most important feature in the sensor network environment because it is a basic element enabling people and things to aware the circumference environment. Existing localization methods can be categorized as either range-based or range-free. While range-based is known to be not suitable because of the irregularity of radio propagation and the additional device requirement. range-free is much appropriated for the resource constrained sensor network because it can actively locate by means of the communication radio. But its location accuracy is just depended on the density of circumference nodes; it is very low in low-density sensor network environment. This paper proposes a mobile object tracking method, named DRTS(Distributed Range-hybrid Tracking Scheme), with combining range-based and range-free. It is optimally making use of the location, communication range, and received signal strength from circumference nodes. Especially, it can greatly improve the mobile tracking accuracy by adapting a new prediction method, named EGP(Estimative Gird Points) into the proposed location estimation method. The simulation results show that our method outperforms the other localization and tracking methods in the tracking accuracy point of view.