• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.187-197
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• 2005

All sensors in Ubiquitous sensor network have to communicate with limited battery If we adopt current authentication, there are difficulties to keep sensor network because heavy calculation in each sensor needs more power and lifetime of sensor could be short relatively because of the effect. This paper suggests network structure which is using RM(RegisterManarer) and AM(AuthenticationManager) to solve power Problem on authentication, and su99ests mutual-authentication protocol with low Power which supports a session key by mutual-authentication. RM and AM manage algorithm with fast calculation to keep the safety by doing key generation. encryption/decryption. authentication instead of each sensor node . Processing time to authenticate sensor node is 2.96$\%$ fast in the same subnet, and 12.91$\%$ fast in different subnet. Therefore. the suggested way Provides expanded lifetime of censor node and is more effective as sensor network size is bigger and bigger.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.165-173
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• 2011

In Mobile Ad-hoc Network(MANET), mobile nodes are operated by limited batteries. Therefore, it is very important to consume the battery power efficiently to prevent termination of the network. In this paper, we propose Energy-aware Dynamic Source Routing(EDSR) which is based on the Dynamic Source Routing(DSR) to increase the packet transmission and lifetime of the network. If the battery power of a node reaches threshold level, then the node gives up the function of relaying to save battery power except as a source and a destination node. While the conventional DSR doesn't consider the battery consumptions of the nodes, EDSR blocks the nodes from relaying whose battery powers are below the threshold level. Simulation results show the proposed EDSR is more efficient in packet transmission and network lifetime through the balanced battery consumption of the mobile nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1204-1227
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• 2020

The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.677-683
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• 2006

If a node stops functioning in an ad-hoc wireless network, routing paths involving the node will also fail, when construction of replacement routes is required. A major cause of node failure is energy exhaustion, and route replacements may in turn lead to successive node failures by making more nodes consume their energy. The result could be performance degradation of networks. Therefore it is important to ensure that nodes with limited remaining energy are not included in route construction from the beginning. In this paper we propose a new routing protocol, which takes residue energy of nodes into account in order to prevent node failures resulting from energy shortage. Our routing protocol examines the smallest value of node residue energy ($E_{m}$) from each of all possible routing paths and selects the path which has the largest value of $E_{m}$. We prove, through simulation, that our routing protocol extends the lifetime of nodes which have limited amount of energy, reducing chances of path replacement. It is also shown that our proposed protocol helps alleviate network performance degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.649-658
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• 2009

Due to limited size and limited battery lifetime of sensor node, one has to address the power saving issue in wireless sensor network. The existing power saving algorithm based on data reuse was proposed for the cluster structured wireless sensor network. We state the problem of existing power saving algorithm and propose new power saving algorithm for tree structured wireless sensor network. The proposed algorithm reduces power consumption by buffering the sensed data at the selected relay node for its data lifetime. The optimum buffering node is selected so that the power saving gain is maximized and at the same time, power consumption among sensor nodes are equally distributed in the network. With computer simulations, it is shown that the proposed algorithm outperforms the conventional algorithm in terms of power saving gain.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.73-82
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• 2007

This paper proposes how to reduce the amount of data transmitted in each sensor and cluster head in order to lengthen the lifetime of sensor network by data aggregation of the continuous queries. The most important factor of refuting the sensor's energy dissipation is to reduce the amount of messages transmitted. The method proposed is basically to combine clustering, in-network data aggregation and hierarchical filtering. Hierarchical filtering is to divide sensor network by two tiers when filtering it. First tier performs filtering when transmitting the data from cluster member to cluster head, and second tier performs filtering when transmitting the data from cluster head to base station. This method is much more efficient and effective than the previous work. We show through various experiments that our scheme reduces the network traffic significantly and increases the network's lifetime than existing methods.

• Smart Media Journal
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• v.8 no.2
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• pp.21-28
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• 2019

Recent research on energy harvesting wireless sensor networks focuses on the development of techniques to solve the limited energy resource problem and to extend the whole network life efficiently. Energy harvesting technology can increase the lifetime of a network, but data transmission becomes unavailable when it harvests energy from radio frequency, resulting longer network delay with respect to the increased time in energy harvesting. Therefore, building energy harvesting wireless sensor network should consider the possible network delay as well as the network lifetime problem. In this paper, we propose a new MAC protocol that minimizes end-to-end network delay by adjusting the data transmission time for a packet based on estimating the energy for data transmission along with the amount of traffic flowing into the network and harvested energy. For this goal, it engineers an energy management mechanism that adjusts the sleep time of the network by measuring energy harvesting time. In addition, with simulation results it shows that the proposed MAC protocol improves the performance in terms of energy consumption and end-to-end delay, compared to the existing MAC protocols.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.846-850
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• 2009

Recently, wireless sensor networks have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics such as environmental monitoring, smart spaces, medical applications, and precision agriculture. The sensor nodes are battery powered. Therefore, the energy is the most precious resource of a wireless sensor network since periodically replacing the battery of the nodes in large scale deployments is infeasible. Energy efficient mechanisms for gathering sensor readings are indispensable to prolong the lifetime of a sensor network as long as possible. There are two energy-efficient approaches to prolong the network lifetime in sensor networks. One is the compression scheme to reduce the size of sensor readings. When the communication conflict is occurred between two sensor nodes, the sender must try to retransmit its reading. The other is the MAC protocol to prevent the communication conflict. In this paper, we propose a novel approaches to reduce the size of the sensor readings in the MAC layer. The proposed scheme compresses sensor readings by allocating the time slots of the TDMA schedule to them dynamically. We also present a mathematical model to predict latency from collecting the sensor readings as the compression ratio is changed. In the simulation result, our proposed scheme reduces the communication cost by about 52% over the existing scheme.

• Journal of KIISE:Information Networking
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• v.36 no.5
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• pp.413-424
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• 2009

Wireless sensor network is based on an event driven system. Sensor nodes collect the events in surrounding environment and the sensing data are relayed into a sink node. In particular, when events are detected, the data sensing periods are likely to be shorter to get the more correct information. However, this operation causes the traffic congestion on the sensor nodes located in a routing path. Since the traffic congestion generates the data queue overflows in sensor nodes, the important information about events could be missed. In addition, since the battery energy of sensor nodes exhausts quickly for treating the traffic congestion, the entire lifetime of wireless sensor networks would be abbreviated. In this paper, a new congestion control method is proposed on the basis of genetic algorithm. To apply genetic algorithm, the data traffic rate of each sensor node is utilized as a chromosome structure. The fitness function of genetic algorithm is designed from both the average and the standard deviation of the traffic rates of sensor nodes. Based on dominant gene sets, the proposed method selects the optimal data forwarding sensor nodes for relieving the traffic congestion. In experiments, when compared with other methods to handle the traffic congestion, the proposed method shows the efficient data transmissions due to much less queue overflows and supports the fair data transmission between all sensor nodes as possible. This result not only enhances the reliability of data transmission but also distributes the energy consumptions across the network. It contributes directly to the extension of total lifetime of wireless sensor networks.