• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4269-4292
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• 2014

Currently, increasing numbers of access points (AP) are being deployed in enterprise offices, campuses and municipal downtowns for flexible Internet connectivity, but most of these access points are idle or redundant most of the time, which causes significant energy waste. Therefore, with respect to power conservation, applying energy efficient strategies in WIFI networks is strongly advocated. One feasible method is dynamically managing network resources, particularly APs, by powering devices on or off. However, when an AP is powered on, the device is initialized through a long boot time, during which period clients cannot be associated with it; therefore, the network performance would be greatly impacted. In this paper, based on a global view of an entire WLAN, we propose an AP selection technology, known as Temporary Access Selection (TAS). The criterion of TAS is a fusion metric consisting of two evaluation indexes which are based on throughput and battery life, respectively. TAS is both service and clients' preference specific through balancing the data rate, battery life and packet size. TAS also works well independently in traditional WLANs in which no energy efficient strategy is deployed. Moreover, this paper demonstrates the feasibility and performance of TAS through experiments and simulations with Network Simulator version 3 (NS3).

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.52-58
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• 2012

Green cloud computing refers to the green ambient benefits that information technology services delivered over the Internet can offer for the society. The green meaning environment friendly and cloud computing is a traditional symbol for the Internet and a type of service provider. Cloud computing has drastically increased the number of datacenters and the energy consumption of data centers and that has become a critical issue which is extremely important in green ambience. These days the cloud data center needs high energy resources that leads to high operational cost and also maximizes CO2 - carbon footprint that pollutes the ambience which is not to be considered as green ambience. So we need to provide a way that leads us to green ambience. Cloud computing for the green ambience should be designed in a way which will utilize less energy resources and to minimize the CO2 -carbon footprint, known as green cloud. In this paper we discuss various elements of Clouds which contributes to minimize the total energy consumption and the carbon emission so as to enable green ambience through green cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5712-5728
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• 2017

Recently, there are many studies, that considering green wireless cellular networks, have taken the energy consumption of the base station (BS) into consideration. In this work, we first introduce an energy consumption model of multi-mode sharing BS powered by multiple energy sources including renewable energy, local storage and power grid. Then communication load requests of the BS are transformed to energy demand queues, and battery energy level and worst-case delay constraints are considered into the virtual queue to ensure the network QoS when our objective is to minimize the long term electricity cost of BSs. Lyapunov optimization method is applied to work out the optimization objective without knowing the future information of the communication load, real-time electricity market price and renewable energy availability. Finally, linear programming is used, and the corresponding energy efficient scheduling policy is obtained. The performance analysis of our proposed online algorithm based on real-world traces demonstrates that it can greatly reduce one day's electricity cost of individual BS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2170-2187
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• 2023

The general interference is the imperative trouble for simultaneous wireless information and power transfer (SWIPT) system. Although interference has bad influences on the performance of the system, it carries energy simultaneously. In this paper, the energy-constrained relay of the SWIPT system needs to spend much time on energy collecting (EC) in the information transmission (IT) period. Therefore, we propose the scheme of interference signal energy collecting (ISEC) when the interference is strong, and the SWIPT system does not carry out IT. The relay of the system continues to collect energy and stores it until the interference has minimal impact on IT. Then the system performs IT. We divide the collected interference energy equally into several parts, and each IT block receives one part. The proposed scheme is appealing because it can reduce the time of EC in IT period to make the relay spends more time forwarding the received signal in order to improve the performance of the system throughput. Furthermore, we propose a time-switching (TS) protocol based on EC at the relay. And it allows the relay forwarding signal at an appropriate power. Under the protocol, the time of EC can be flexible according to the forwarding power that we give so that the collected energy can be used more efficiently. We give the expressions of the system throughput according to the proposed scheme and protocol. Moreover, the influence of the interference power on the system throughput is also studied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1359-1375
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• 2015

Energy efficiency is critical for Wireless Sensor Networks (WSNs) since sensor nodes usually have very limited energy supply from battery. Sleep scheduling and nodes cooperation are two of the most efficient methods to achieve energy conservation in WSNs. In this paper, we propose an adaptive energy optimization approach for target tracking applications, called Energy-Efficient Node Coordination (EENC), which is based on the grid structure. EENC provides an unambiguous calculation and analysis for optimal the nodes cooperation theoretically. In EENC, the sleep schedule of sensor nodes is locally synchronized and globally unsynchronized. Locally in each grid, the sleep schedule of all nodes is synchronized by the grid head, while globally the sleep schedule of each grid is independent and is determined by the proposed scheme. For dynamic sleep scheduling in tracking state we propose a multi-level coordination algorithm to find an optimal nodes cooperation of the network to maximize the energy conservation while preserving the tracking performance. Experimental results show that EENC can achieve energy saving of at least 38.2% compared to state-of-the-art approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3064-3094
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• 2018

Currently, the Underwater Sensor Networks (UWSNs) is mainly an interesting area due to its ability to provide a technology to gather many valuable data from underwater environment such as tsunami monitoring sensor, military tactical application, environmental monitoring and many more. However, UWSNs is suffering from limited energy, high packet loss and the use of acoustic communication. In UWSNs most of the energy consumption is used during the forwarding of packet data from the source to the destination. Therefore, many researchers are eager to design energy efficient routing protocol to minimize energy consumption in UWSNs. As the opportunistic routing (OR) is the most promising method to be used in UWSNs, this paper focuses on the existing proposed energy efficient OR protocol in UWSNs. This paper reviews the existing proposed energy efficient OR protocol, classifying them into 3 categories namely sender-side-based, receiver-side-based and hybrid. Furthermore each of the protocols is reviewed in detail, and its advantages and disadvantages are discussed. Finally, we discuss potential future work research directions in UWSNs, especially for energy efficient OR protocol design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.540-546
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• 2014

Recently a new government has announced an action plan known as the government 3.0, which aims to provide customized services for individual people, generate more jobs and support creative economy. Leading on from previous similar initiatives, the new scheme seeks to focus on open, share, communicate, and collaborate. In promoting Government 3.0, the crucial factor might be how to align the core services and policies of Government 3.0 with correspoding technologies. The paper describes the concepts and features of Government 3.0, identifies emerging Internet-based technologies and services toward the initiative, and finally provides improvement plans for Government 3.0. As a result, 10 issues to be brought together include: Smart Phone Applications and Service, Mobile Internet Computing and Application, Wireless and Sensor Network, Security & Privacy in Internet, Energy-efficient Computing & Smart Grid, Multimedia & Image Processing, Data Mining and Big Data, Software Engineering, Internet Business related Policy, and Management of Internet Application.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3621-3640
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• 2016

In the process of k-coverage of the target node, there will be a lot of data redundancy forcing the phenomenon of congestion which reduces network communication capability and coverage, and accelerates network energy consumption. Therefore, this paper proposes a novel energy balanced k-coverage control algorithm based on probability model (EBKCCA). The algorithm constructs the coverage network model by using the positional relationship between the nodes. By analyzing the network model, the coverage expected value of nodes and the minimum number of nodes in the monitoring area are given. In terms of energy consumption, this paper gives the proportion of energy conversion functions between working nodes and neighboring nodes. By using the function proportional to schedule low energy nodes, we achieve the energy balance of the whole network and optimizing network resources. The last simulation experiments indicate that this algorithm can not only improve the quality of network coverage, but also completely inhibit the rapid energy consumption of node, and extend the network lifetime.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2020-2037
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• 2017

In order to improve the energy efficiency of n-Epidemic routing protocol in opportunistic networks, in which a stable end-to-end forwarding path usually does not exist, a novel adjustment strategy for parameter n is proposed using learning atuomata principle. First, nodes dynamically update the average energy level of current environment while moving around. Second, nodes with lower energy level relative to their neighbors take larger n avoiding energy consumption during message replications and vice versa. Third, nodes will only replicate messages to their neighbors when the number of neighbors reaches or exceeds the threshold n. Thus the number of message transmissions is reduced and energy is conserved accordingly. The simulation results show that, n-Epidemic routing protocol with the proposed adjustment method can efficiently reduce and balance energy consumption. Furthermore, the key metric of delivery ratio is improved compared with the original n-Epidemic routing protocol. Obviously the proposed scheme prolongs the network life time because of the equilibrium of energy consumption among nodes.