• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.37-44
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• 2017

Wireless sensor networks are composed of many wireless sensor nodes that are sensing the environments. These networks have many constraints that are resource constraints, wireless communication, self-construction, etc. But they have many applications that are monitoring environment, tracking the object, etc. In this paper, a mechanism of finding QoS Satisfied multi-path is proposed in wireless sensor networks. In order to satisfy the QoS requirement, the proposed mechanism extends the AODV protocol to find multiple paths from a source node to a destination node by using the additional AODV message types that are proposed. This mechanism will be used to support many QoS applications such as minimum delay time, the better reliability and the better throughput by using the QoS satisfied multi-path. Overheads of the proposed mechanism are evaluated using simulation, and it is showed that QoS satisfied multiple paths are found with a little more overhead than the AODV mechanism.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.212-218
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• 2010

In wireless sensor networks (WSNs), both efficient energy management and Quality of Service (QoS) are important issues for some applications. For creating robust networks, real-time services are usually employed to satisfy the QoS requirements. In this paper, we proposed a hierarchical real-time MAC (medium access control) protocol for (m,k)-firm constraint in wireless sensor networks shortly called HRTS-MAC. The proposed HRTS-MAC protocol is based on a dynamic priority assignment by (m,k)-firm constraint. In a tree structure topology, the scheduling algorithm assigns uniform transmitting opportunities to each node. The paper also provides experimental results and comparison of the proposed protocol with E_DBP scheduling algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.895-896
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• 2015

With the development of sensor, wireless mobile communication, embedded system and cloud computing, the technologies of Internet of Things have been widely used in logistics, Smart devices security, intelligent building and o on. Bridging between wireless sensor networks with traditional communication networks or Internet, IoT gateway plays n important role in IoT applications, which facilitates the integration of wireless sensor networks and mobile communication networks or Internet, and the management and control with wireless sensor networks. The IoT Gateway is a key component in IoT application systems but It has lot of security issues. We analyzed the trends of security and privacy matters.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.341-346
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• 2011

Wireless sensor networks (WSNs) are formed by a great quantity of sensor nodes, which are consisted of battery-powered and some tiny devices. In WSN, both efficient energy management and Quality of Service (QoS) are important issues for some applications. Real-time services are usually employed to satisfy QoS requirements in critical environment. This paper proposes a real-time MAC (Medium Access Control) protocol with extended backoff scheme for wireless sensor networks. The basic idea of the proposed protocol employs (m,k)-firm constraint scheduling which is to adjust the contention window (CW) around the optimal value for decreasing the dynamic failure and reducing collisions DBP (Distant Based Priority). In the proposed protocol, the scheduling algorithm dynamically assigns uniform transmitting opportunities to each node. Numerical results reveal the effect of the proposed backoff mechanism.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.21-26
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• 2012

As the new requirements for wireless sensor networks are emerging, real-time communications is becoming a major research challenge because resource-constrained sensor nodes are not powerful enough to accommodate the complexity of the protocol. In addition, an efficient energy management scheme has naturally been a concern in wireless sensor networks for a long time. However, the existing schemes are limited to meeting one of these two requirements. To address the two factors together, we propose real-time communications with two approaches, a protocol for satisfied conditions and one for unsatisfied. Under the satisfied requirement, existing real-time protocol is employed. On the other hand, for the unsatisfied requirement, the newly developed scheme replaces the existing scheme by adjusting the transmission range of some surplus nodes. By expanding the transmission range, the end-to-end delay is shortened because the number of intermediate nodes decreases. These nodes conserve their energy for real-time communications by avoiding other activities such as sensing, forwarding, and computing. Finally, simulation results are given to demonstrate the feasibility of the proposed scheme in high traffic environments.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.212-221
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• 2009

This paper proposes a novel centralized clustering algorithm, "RLCA : Relative Location based Clustering Algorithm for Wireless Sensor Networks," for constructing geographically well-distributed clusters in general WSNs. RLCA does not use GPS and controls selection-rate of cluster-head based on distances between sensors and BS. We empirically show that RLCA's energy efficiency is higher than LEACH's.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.177-179
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• 2006

This paper presents an analysis architecture of embedded operating systems for wireless sensor network. Wireless multi-hop sensor networks use battery-operated computing and sensing device. We expect sensor networks to be deployed in an ad hoc fashion, with very high energy constraints. These characteristics of multi-hop wireless sensor networks and applications motivate an operating system that is different from traditional embedded operating system. These days new wireless sensor network embedded operating system come out with some advances compared with previous ones. The analysis is focusing on understanding differences of dominant wireless sensor network OS, such as TinyOS 2.0 with TinyOS 1.x.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.619-639
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• 2010

There is increasing interest in using structural monitoring as a cost effective way of managing risks once an area of concern has been identified. However, it is challenging to deploy an effective, reliable, large-scale, long-term and real-time monitoring system in an underground railway environment (subway / metro). The use of wireless sensor technology allows for rapid deployment of a monitoring scheme and thus has significant potential benefits as the time available for access is often severely limited. This paper identifies the critical factors that should be considered in the design of a wireless sensor network, including the availability of electrical power and communications networks. Various issues facing underground deployment of wireless sensor networks will also be discussed, in particular for two field case studies involving networks deployed for structural monitoring in the Prague Metro and the London Underground. The paper describes the network design, the radio propagation, the network topology as well as the practical issues involved in deploying a wireless sensor network in these two tunnels.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Journal of Computing Science and Engineering
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• v.9 no.4
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• pp.163-176
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• 2015

Self-organization of distributed wireless sensor nodes is a critical issue in wireless sensor networks (WSNs), since each sensor node has limited energy, bandwidth, and scalability. These issues prevent sensor nodes from actively collaborating with the other types of sensor nodes deployed in a typical heterogeneous and somewhat hostile environment. The automated self-organization of a WSN becomes more challenging as the number of sensor nodes increases in the network. In this paper, we propose a dynamic self-organized architecture that combines tree topology with a drawn-grid algorithm to automate the self-organization process for WSNs. In order to make our proposed architecture scalable, we assume that all participating active sensor nodes are unaware of their primary locations. In particular, this paper presents two algorithms called active-tree and drawn-grid. The proposed active-tree algorithm uses a tree topology to assign node IDs and define different roles to each participating sensor node. On the other hand, the drawn-grid algorithm divides the sensor nodes into cells with respect to the radio coverage area and the specific roles assigned by the active-tree algorithm. Thus, both proposed algorithms collaborate with each other to automate the self-organizing process for WSNs. The numerical and simulation results demonstrate that the proposed dynamic architecture performs much better than a static architecture in terms of the self-organization of wireless sensor nodes and energy consumption.