• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.4
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• pp.245-251
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• 2014

Wireless Sensor Networks(WSNs) are applied to many monitoring applications. Present sensor nodes can perform many functions at the same time and contain complex software. During the lifetime of sensor nodes, they are required to reprogram their software because of their new functions, software, software bug fixes. The nodes are inaccessible physically or it is very difficult to upgrade their software by one by one. To upgrade the software of sensor nodes in WSNs remotely, this paper presents an energy efficient method by selecting an optimal relay node. The CHR(Cluster Head Relay) method is compared with SPIN and RANDOM method. Three methods are simulated in NS-2 with the same environmental parameters. Simulation results show that CHR shows faster update time and less power consumption compared with other two methods.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.237-241
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• 2012

In wireless sensor networks, the importance of transporting data correctly with reliability is increasing gradually along with the need to support communications between the nodes and sink. Data flow from the sink to the nodes requires reliability for control or management that is very sensitive and intolerant of error; however, data flow from the nodes to the sink is relatively tolerant. In this paper, with emphasis on the data flow from the sink to the nodes, we propose a mechanism that considers accurate transport with reliability hop-by-hop. During the process of sending the data, if errors occur or data is missing, the proposed mechanism supports error recovery using a fixed window with selective acknowledgment. In addition, this mechanism supports congestion control depending on the buffer condition. Through the simulation, we show that this mechanism is accurate, reliable, and proper for transport in wireless sensor networks.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.197-200
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• 2008

In most sensor networks, nodes can be easily compromised by adversaries due to hostile environments. Adversaries may use compromised nodes to inject false reports into the sensor networks. Such false report attacks will cause false alarms that can waste real-world response effort, and draining the finite amount of energy resource in the battery-powered network. A dynamic enroute scheme proposed by Yu and Guan can detect and drop such false reports during the forwarding phase. In this scheme, choosing a threshold value is very important, as it trades off between security power and energy consumption. In this paper, we propose a threshold determining method which uses the fuzzy rule-based system. The base station periodically determines a threshold value though the fuzzy rule-based system. The number of cluster nodes, the value of the key dissemination limit, and the remaining energy of nodes are used to determine the threshold value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4271-4294
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• 2018

Communication cost is the most important factor in Wireless Sensor Networks (WSNs), as exchanging control keying messages consumes a large amount of energy from the constituent sensor nodes. Time-based Dynamic Keying and En-Route Filtering (TICK) can reduce the communication costs by utilizing local time values of the en-route nodes to generate one-time dynamic keys that are used to encrypt reports in a manner that further avoids the regular keying or re-keying of messages. Although TICK is more energy efficient, it employs no re-encryption operation strategy that cannot determine whether a healthy report might be considered as malicious if the clock drift between the source node and the forwarding node is too large. Secure SOurce-BAsed Loose Synchronization (SOBAS) employs a selective encryption en-route in which fixed nodes are selected to re-encrypt the data. Therefore, the selection of encryption nodes is non-adaptive, and the dynamic network conditions (i.e., The residual energy of en-route nodes, hop count, and false positive rate) are also not focused in SOBAS. We propose an energy efficient selection of re-encryption nodes based on fuzzy logic. Simulation results indicate that the proposed method achieves better energy conservation at the en-route nodes along the path when compared to TICK and SOBAS.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1307-1313
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• 2017

Sensor networks are composed of provide low powered, inexpensive distributed devices which can be deployed over enormous physical spaces. Coordination between sensor devices is required to achieve a common communication. In low cost, low power and short-range wireless environment, sensor networks cope with significant resource constraints. Security is one of main issues in wireless sensor networks because of potential adversaries. Several security protocols and models have been implemented for communication on computing devices but deployment these models and protocols into the sensor networks is not easy because of the resource constraints mentioned. Memory intensive encryption algorithms as well as high volume of packet transmission cannot be applied to sensor devices due to its low computational speed and memory. Deployment of sensor networks without security mechanism makes sensor nodes vulnerable to potential attacks. Therefore, attackers compromise the network to accept malicious sensor nodes as legitimate nodes. This paper provides the different security models as a metric, which can then be used to make pertinent security decisions for securing wireless sensor network communication.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.431-439
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• 2021

Since the sensor nodes are randomly arranged in the region of interest, it may happen that the sensor network area is separated or there is no sensor node in some area. In addition, after the sensor nodes are deployed in the sensor network, a coverage hole may occur due to the exhaustion of energy or physical destruction of the sensor nodes. The coverage hole can greatly affect the overall performance of the sensor network, such as reducing the data reliability of the sensor network, changing the network topology, disconnecting the data link, and worsening the transmission load. Therefore, sensor network coverage hole recovery has been studied. Existing coverage hole recovery studies present very complex geometric methods and procedures in the two-step process of finding a coverage hole and recovering a coverage hole. This study proposes a method for discovering and recovering a coverage hole in a sensor network, discovering that the sensor node is a boundary node by itself, and determining the location of a mobile node to be added. The proposed method is expected to have better efficiency in terms of complexity and message transmission compared to previous methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.27-37
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• 2009

Sensor nodes forming a sensor network have limited energy capacity such as small batteries and when these nodes are placed in a specific field, it is important to research minimizing sensor nodes' energy consumption because of difficulty in supplying additional energy for the sensor nodes. Clustering has been in the limelight as one of efficient techniques to reduce sensor nodes' energy consumption in sensor networks. However, energy saving results can vary greatly depending on election of cluster heads, the number and size of clusters and the distance among the sensor nodes. /This research has an aim to find the optimal set of clusters which can reduce sensor nodes' energy consumption. We use a Genetic Algorithm(GA), a stochastic search technique used in computing, to find optimal solutions. GA performs searching through evolution processes to find optimal clusters in terms of energy efficiency. Our results show that GA is more efficient than LEACH which is a clustering algorithm without evolution processes. The two-dimensional GA (2D-GA) proposed in this research can perform more efficient gene evolution than one-dimensional GA(1D-GA)by giving unique location information to each node existing in chromosomes. As a result, the 2D-GA can find rapidly and effectively optimal clusters to maximize lifetime of the sensor networks.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.355-357
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• 2005

This paper describes the architecture and modeling of adaptive and reconfigurable OS in wireless distributed sensor networks. Before initial sensor nodes are deployed in a sensor field, minimum functions including basic OS and routing algorithms are required for these nodes to send request messages for dynamic reconfigurations and receive response messages from a task manager. When the downloading is finished, each sensor node can reconfigure the initial state and be ready to start its functions. By applying this reconfigurable modeling, sensor nodes can be easily deployed in the sensor field and dynamically programmed during a bootstrap process.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.361-367
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• 2014

This paper introduces balancing energy and memory consumption for lifetime increase of wireless sensor network. In cluster-based wireless sensor network, sensor nodes adjacent of cluster heads have a tendency to deplete their own battery energy and cluster heads occupy memory space significantly. If the nodes close to region where events occur frequently consume their energy and memory fully, network might be destroyed even though most of nodes are still alive. Therefore, it needs to balance network energy and memory with consideration of event occurrence probability so that network lifetime is increased. We show a method of balancing wireless sensor network energy and memory to organize cluster groups and elect cluster heads in terms of event occurrence probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1357-1378
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• 2013

Energy constraint of wireless sensor networks makes energy saving and prolonging the network lifetime become the most important goals of routing protocols. In this paper, we propose an Energy Efficient Chain-based Routing Protocol (EECRP) for wireless sensor networks to minimize energy consumption and transmission delay. EECRP organizes sensor nodes into a set of horizontal chains and a vertical chain. Chain heads are elected based on the residual energy of nodes and distance from the header of upper level. In each horizontal chain, sensor nodes transmit their data to their own chain head based on chain routing mechanism. EECRP also adopts a chain-based data transmission mechanism for sending data packets from the chain heads to the base station. The simulation results show that EECRP outperforms LEACH, PEGASIS and ECCP in terms of network lifetime, energy consumption, number of data messages received at the base station, transmission delay and especially energy${\times}$delay metric.