• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1133-1151
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• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1451-1457
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• 2013

Recently, new concept of energy systems such as microgrid, smart grid, supergrid, and energy network has been introducing. In this paper, the concept of the centralized micro-energy network, which is an energy community of a building group without district heating system, is introduced. In addition, a mathematical model for optimal operation of the micro-energy network as a main function of an energy management system (EMS) for the micro-energy network is proposed. In order to show the validation, the proposed model is tested through the simulation and analyzed.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.109-118
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• 2023

Energy awareness is an essential design flaw in wireless sensor network. Clustering is the most highly regarded energy-efficient technique that offers various benefits such as energy efficiency and network lifetime. Clusters create hierarchical WSNs that introduce the efficient use of limited sensor node resources and thus enhance the life of the network. The goal of this paper is to provide an analysis of the various energy efficient clustering algorithms. Analysis is based on the energy efficiency and network lifetime. This review paper provides an analysis of different energy-efficient clustering algorithms for WSNs.

• East Asian Economic Review
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• v.28 no.1
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• pp.3-35
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• 2024

This paper utilizes social network analysis to examine the structural characteristics and trade dynamics of the renewable energy (hydropower, wind energy, and solar energy) trade network within the RCEP region from 2011 to 2020. The findings reveal: (1) The renewable energy trade network within the RCEP exhibits dynamism, heterogeneity, and an uneven development. The solar energy network is the most balanced and stable, while the wind energy network lags and shows marked fluctuations, with the hydropower network falling between these two. This demonstrates the diversity of energy trade within the region. (2) China, Singapore, and Japan are identified as the key exporting and importing countries, with Vietnam showing substantial growth potential. Individual analyses shed light on the stark disparities in trade status among nations, reflecting the diverse roles and future potential of member countries. (3) The QAP regression analysis reveals a significant influence of environmental pressure, particularly carbon dioxide emissions, on the renewable energy trade network. This study contributes to promoting environmental sustainability and energy security in the RCEP region and provides empirical evidence for global renewable energy trade strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.446-458
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• 2013

Recently, energy-efficient cellular transmission has received considerable research attention to improve the energy efficiency of wireless communication. In this paper, we consider a cellular network consisting of one base station (BS) and multiple user terminals and explore the network coding for enhancing the energy efficiency of cellular downlink transmission from BS to users. We propose the network coded cellular transmission scheme and conduct its energy consumption analysis with target outage probability and data rate requirements in Rayleigh fading environments. Then, the energy efficiency in Bits-per-Joule is further defined and analyzed to evaluate the number of bits delivered per Joule of energy cost. Numerical results show that the network coded cellular transmission significantly outperforms the traditional cellular transmission in terms of energy efficiency, implying that given a Joule of energy cost, the network coded cellular transmission scheme can deliver more bits than the traditional cellular transmission.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.45-49
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• 2015

In this paper, we proposed not specturm sensing but also save energy without consume energy of secondary network that spectrum sensing of cognitive applied energy harvesting scheme. Algorithms of sensing and harvesting is determine active or idle of primary network, compares the amount of energy that is harvested by energy harvesting scheme with the threshold. If secondary network to send a message and primary network is active, by changing frequency to use the spectrum. Further, if secondary network have no message, continues energy harvest. Therefore, spectrum sensing applied energy harvesting scheme, energy of secondary network is remove waste and charge energy, efficiency and utilization of cognitive network can be increase.

• 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.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.713-724
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• 2016

Energy consumption has become a main problem of sustainable development in communication networks and how to communicate with high energy efficiency is a significant topic that researchers and network operators commonly concern. In this paper, an energy-efficient multicast algorithm in multi-hop wireless networks is proposed aiming at new generation wireless communications. Traditional multi-hop wireless network design only considers either network efficiency or minimum energy consumption of networks, but rarely the maximum energy efficiency of networks. Different from previous methods, the paper targets maximizing energy efficiency of networks. In order to get optimal energy efficiency to build network multicast, our proposed method tries to maximize network throughput and minimize networks' energy consumption by exploiting network coding and sleeping scheme. Simulation results show that the proposed algorithm has better energy efficiency and performance improvements compared with existing methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.73-76
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• 2015

In this paper, we propose energy harvesting apply to spectrum sensing. In this case, we can be spectrum sensing without consume energy. Algorithms of sensing and harvesting are determine active or idle of primary network, Compares with the threshold energy and the amount of energy that is harvested by energy harvesting scheme. If the secondary network want to send a message while the primary network is active, secondary users will change frequency to use the spectrum. Further, if the secondary network has not message, it will continues harvest energy. Therefore, spectrum sensing applied the energy harvesting method, energy of secondary network is remove waste and charge energy. So, efficiency and utilization of cognitive network can be increase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.626-648
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• 2011

Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.