• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3494-3510
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• 2019

Wireless sensor networks encounter energy saving as a major issue as the sensor nodes having no rechargeable batteries and also the resources are limited. Clustering of sensors play a pivotal role in energy saving of the deployed sensor nodes. However, in the cluster based wireless sensor network, the cluster heads tend to consume more energy for additional functions such as reception of data, aggregation and transmission of the received data to the base station. So, careful selection of cluster head and formation of cluster plays vital role in energy conservation and enhancement of lifetime of the wireless sensor networks. This study proposes a new mutation chemical reaction optimization (MCRO) which is an algorithm based energy efficient clustering protocol termed as MCRO-ECP, for wireless sensor networks. The proposed protocol is extensively developed with effective methods such as potential energy function and molecular structure encoding for cluster head selection and cluster formation. While developing potential functions for energy conservation, the following parameters are taken into account: neighbor node distance, base station distance, ratio of energy, intra-cluster distance, and CH node degree to make the MCRO-ECP protocol to be potential energy conserver. The proposed protocol is studied extensively and tested elaborately on NS2.35 Simulator under various senarios like varying the number of sensor nodes and CHs. A comparative study between the simulation results derived from the proposed MCRO-ECP protocol and the results of the already existing protocol, shows that MCRO-ECP protocol produces significantly better results in energy conservation, increase network life time, packets received by the BS and the convergence rate.

• Smart Media Journal
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• v.4 no.1
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• pp.25-32
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• 2015

Powering wireless sensors with energy harvested from the environment is coming of age due to the increasing power densities of both storage and harvesting devices and the electronics performing energy efficient energy conversion. In order to maximize the functionality of the wireless sensor network, minimize missing packets, minimize latency and prevent the waste of energy, problems like congestion and inefficient energy usage must be addressed. Many sleep-awake protocols and efficient message priority techniques have been developed to properly manage the energy of the nodes and to minimize congestion. For a WSN that is operating in a strictly energy constrained environment, an energy-efficient transmission strategy is necessary. In this paper, we present a novel transmission priority decision scheme for a heterogeneous body sensor network composed of normal nodes and an energy harvesting node that acts as a cluster head. The energy harvesting node's decision whether or not to clear a normal node for sending is based on a set of metrics which includes the energy harvesting node's remaining energy, the total harvested energy, the type of message in a normal node's queue and finally, the implementation context of the wireless sensor network.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.497-498
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• 2007

The most of important thing when we design a Wireless Sensor Network is resources. You have to consider energy efficient operation When you design Wireless Sensor Network. Because Sensor devices have a limited resources. In this paper, we proposed energy efficiency localization technique in Wireless Sensor Network. We used Cell ID technique for location search. This method can reduce power consumption and the network life time will be extension.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.949-966
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• 2013

Recently, Wireless Body Area Network (WBAN) has promise to revolutionize human daily life. The need for multiple sensors and constant monitoring lead these systems to be energy hungry and expensive with short operating lifetimes. In this paper, we offer a review of existing work of WBAN and focus on energy-aware management in it. We emphasize that nodes computation, wireless communication, topology deployment and energy scavenging are main domains for making a long-lived WBAN. We study the popular power management technique Dynamic Voltage and Frequency Scaling (DVFS) and identify the impact of slack time in Dynamic Power Management (DPM), and finally propose an enhanced dynamic power management method to schedule scaled jobs at slack time with the goal of saving energy and keeping system reliability. Theoretical and experimental evaluations exhibit the effectiveness and efficiency of the proposed method.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.2
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• pp.53-69
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• 2010

This paper proposes an ant-based routing algorithm, Ant System-Routing in wireless Senor Networks(AS-RSN), for wireless sensor networks. Using a transition rule in Ant System, sensors can spread data traffic over the whole network to achieve energy balance, and consequently, maximize the lifetime of sensor networks. The transition rule advances one of the original Ant System by re-defining link cost which is a metric devised to consider energy-sufficiency as well as energy-efficiency. This metric gives rise to the design of the AS-RSN algorithm devised to balance the data traffic of sensor networks in a decentralized manner and consequently prolong the lifetime of the networks. Therefore, AS-RSN is scalable in the number of sensors and also robust to the variations in the dynamics of event generation. We demonstrate the effectiveness of the proposed algorithm by comparing three existing routing algorithms: Direct Communication Approach, Minimum Transmission Energy, and Self-Organized Routing and find that energy balance should be considered to extend lifetime of sensor network and increase robustness of sensor network for diverse event generation patterns.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.295-306
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• 2010

Network lifetime is a critical issue in Wireless Sensor Networks (WSNs). In which, a large number of sensor nodes communicate together to perform a predetermined sensing task. In such networks, the network life time depends mainly on the lifetime of the sensor nodes constituting the network. Therefore, it is essential to balance the energy consumption among all sensor nodes to ensure the network connectivity. In this paper, we propose an energy-efficient data routing protocol for wireless sensor networks. Contrary to the protocol proposed in [6], that always selects the path with minimum hop count to the base station, our proposed routing protocol may choose a longer path that will provide better distribution of the energy consumption among the sensor nodes. Simulation results indicate clearly that compared to the routing protocol proposed in [6], our proposed protocol evenly distributes the energy consumption among the network nodes thus maximizing the network life time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4044-4062
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• 2016

We investigate the optimization of energy consumption in Mobile Cloud environment in this paper. In order to optimize the energy consumed by the CPUs in mobile devices, we put forward using the asymptotic time complexity (ATC) method to distinguish the computational complexities of the applications when they are executed in mobile devices. We propose a multi-scale scheme to quantize the channel gain and provide an improved dynamic transmission scheduling algorithm when offloading the applications to the cloud center, which has been proved to be helpful for reducing the mobile devices energy consumption. We give the energy estimation methods in both mobile execution model and cloud execution model. The numerical results suggest that energy consumed by the mobile devices can be remarkably saved with our proposed multi-scale scheme. Moreover, the results can be used as a guideline for the mobile devices to choose whether executing the application locally or offloading it to the cloud center.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1357-1372
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• 2017

Energy harvesting techniques, particularly radio frequency energy harvesting (RF-EH) techniques, which are known to provide feasible solutions to enhance the performance of energy constrained wireless communication systems, have gained increasing attention. In this paper, we consider a wireless-powered cooperative communication network (WPCCN) for transferring energy in the downlink and forwarding signals in the uplink. The objective is to maximize the average transmission rate of the system, subject to the total network power constraint. We formulate such a problem as a form of wireless energy transmission based on resource allocation that searches for the joint subcarrier pairing and the time and power allocation, and this can be solved by using a dual approach. Simulation results show that the proposed joint optimal scheme can efficiently improve system performance with an increase in the number of subcarriers and relays.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.115-122
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• 2017

In this paper, we propose an adaptive data aggregation and compression scheme for wireless sensor networks with energy-harvesting nodes, which increases the amount of data arrived at the sink node by efficient use of the harvested energy. In energy-harvesting wireless sensor networks, sensor nodes can have more than necessary energy because they harvest energy from environments continuously. In the proposed scheme, when a node judges that there is surplus energy by estimating its residual energy, the node compresses and transmits the aggregated data so far. Conversely, if the residual energy is estimated to be depleted, the node turns off its transceiver and collects only its own sensory data to reduce its energy consumption. As a result, this scheme increases the amount of data collected at the sink node by preventing the blackout of relay nodes and facilitating data transmission. Through simulation, we show that the proposed scheme suppresses the occurrence of blackout nodes and collect the largest amount of data at the sink node compared to previous schemes.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.98-105
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• 2019

Energy autonomy is a system that is sustained by energy from an independent and distributed source such as renewable energy. In this paper, we propose a robotic energy autonomy in which a robot obtains energy from a renewable energy source with a limited storage capacity. As an energy transfer method, wireless power transfer is used to solve the problem of the conventional contact charging method, mechanical complexity, and to obtain high energy transfer efficiency, the image information is used to align the transmitting and receiving coils accurately. A small scale thermoelectric energy source with boost converter, battery charger, and wireless power transfer coil is constructed and an actual charging experiment is conducted to verify the proposed autonomy system.