• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.596-603
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• 2019

A reprogramming operation is necessary to update the software code of the node to change or update the functionality of the deployed node in wireless sensor networks. This paper proposes an optimization algorithm that minimizes the transmission energy of a node for the purpose of reprogramming a node in wireless sensor networks. We also design an algorithm that keeps energy consumption of all nodes balanced in order to maintain the lifetime of the network. In this paper, we propose a Tabu search algorithm with a new neighborhood generation method for minimizing transmission energy and energy consumption in wireless sensor networks with many nodes. The proposed algorithm is designed to obtain optimal results within a reasonable execution time. The performance of the proposed Tabu search algorithm was evaluated in terms of the node's transmission energy, remaining energy, and algorithm execution time. The performance evaluation results showed better performance than the previous methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.1
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• pp.39-45
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• 2010

As wireless sensor network are being deployed in a wide variety of application areas, the number of sensor nodes in a sensor filed becomes larger and larger. In the past, ISP (In-System Programming) method have been generally used for code update but the large number of sensor nodes requires a new code update method called network reprogramming. There are many challenging issues for network reprogramming since it can make an impact on the network lifetime. In this paper, a new sender selection scheme for network reprogramming protocol is proposed to decrease energy consumption for code update by minimizing overlapped area between sender nodes and reducing data contention. Simulation results show that the proposed scheme can reduce the amount of message traffic and the overall data transmission time.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.67-75
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• 2010

Network reprogramming is a technology that allows several sensor nodes deployed in sensor field to be repaired remotely. Unlike general communication in sensor network where small amount of data is transferred, network reprogramming requires reliable transfer of large amount of data. The existing network reprogramming techniques suffers high cost and large energy consumption to recover data loss in node communication. In this paper, a cluster based network reporgramming scheme is proposed for sensor network. It divides sensor field into several clusters and chooses a cluster header in charge of data relay to minimize duplicated transmission and unnecessary competition. It increases reliability by effective error recovery through status table.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.51-58
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• 2014

As WSNs(Wireless Sensor Networks) are being deployed widely in diverse application areas, their management and maintenance become more important. Recent sensor node software takes modular software architectures in pursuit of flexible software management and energy efficient reprogramming. To realize an flexible and efficient modular architecture particularly on resource constrained mote-class sensor nodes that are implemented with MCUs(Micro-Controller Units) of a single address space. an appropriate module linking model is essential to resolve and bind the inter-module global symbols. This paper identifies a design space of module linking model and respectively their implementation frameworks. We then establish a taxonomy for module linking models by exploring the design space of module linking models. Finally, we suggest an implementation framework respectively for each module linking model in the taxonomy. We expect that this work lays the foundations for systematic innovation toward more flexible and efficient modular software architectures for WSNs.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.867-875
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• 2009

A wireless sensor network inherently comprises a plurality of sensor nodes widely deployed for sensing environmental information. To add new functions or to correct some faulty functions of an existing wireless sensor network, the firmware for each sensor node needs to be updated. Firmware update would be quite troublesome if it requires the gathering, reprogramming, and redeploy of all of already deployed sensor nodes. Over-the-air programming (OTA) facilitates the firmware update process, thereby allowing convenient maintenance of an already-deployed sensor network. This paper proposes and implements a remote firmware update mechanism for a TDMA-based wireless sensor network, in which the firmware for sensor nodes constituting the TDMA-based sensor network can be easily updated and the update process can be conveniently monitored from a remote site. We verify the validity of the proposed firmware update method via experiments and introduce three wireless sensor networks installed in outdoor sites in which the proposed firmware update mechanism has been exploited.

• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.215-226
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• 2008

As sensor networks are used in various and dynamic applications, the function of sink-to-sensors reliable multicasting such as for task reprogramming is newly required. NAK-based error recovery schemes have been proposed for energy efficient reliable multicasting. However, these schemes have incompleteness problems such as the last packet loss. This paper introduces an ACK-based error recovery scheme, RM2I(Reliable Multicast with Implicit ACK and Indirect Recovery). It utilizes wireless multicast advantage in which a packet may be delivered to all of its omni-directional neighbor nodes. When a sender overhears a packet which its receiver forwards to the next nodes, it may interpret it as an ACK from the receiver. We call it an Implicit ACK. In Indirect Recovery, when a node receives a packet from neighbor nodes which are not its direct upstream node, it saves and utilizes it for error recovery. Using NS-2 simulator, we have analyzed their effects. We have also compared RM2I with the NAK-based error recovery scheme. In results, RM2I shows comparable performances to the ideal NAK-based scheme, except where Implicit ACK and Indirect Recovery do not occur at the edges of the networks.