• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.185-191
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• 2023

The Internet of Things (IoT) can be defined as the connection of devices, sensors, and actors via the Internet to a single network to provide services to end-users. Owing to the flexibility and simplicity of IoT devices, which impart convenience to end-users, the demand for these devices has increased significantly in the last decade. To make these systems more scalable, achieve a larger number of connected devices, and achieve greater economic success, it is vital to develop them by considering parameters such as security, cost, bandwidth, data rate, and power consumption. This study aims to improve energy efficiency and prolong the lifetime of IoT networks by proposing a new approach called the constrained application protocol CoAP45. This approach reduces the number of updates to the CoAP server using a centralized resource. The simulation results show that the proposed approach outperforms all existing protocols.

• ETRI Journal
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• v.44 no.1
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• pp.155-167
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• 2022

The Internet of Things (IoT) is a new paradigm that connects physical and virtual objects from various domains such as home automation, industrial processes, human health, and monitoring. IoT sensors receive information from their environment and forward it to their neighboring nodes. However, the large amounts of exchanged data are vulnerable to attacks that reduce the network performance. Most of the previous security methods for IoT have neglected the energy consumption of IoT, thereby affecting the performance and reducing the network lifetime. This paper presents a new multistep routing protocol based on cellular learning automata. The network lifetime is improved by a performance-based adaptive reward and fine parameters. Nodes can vote on the reliability of their neighbors, achieving network reliability and a reasonable level of security. Overall, the proposed method balances the security and reliability with the energy consumption of the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.857-872
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• 2014

Recent researches reveal that great benefit can be achieved for data gathering in wireless sensor networks (WSNs) by employing mobile data collectors. In order to balance the energy consumption at sensor nodes and prolong the network lifetime, a multi-track large-scale mobile data collection mechanism (MTDCM) is proposed in this paper. MTDCM is composed of two phases: the Energy-balance Phase and the Data Collection Phase. In this mechanism, the energy-balance trajectories, the sleep-wakeup strategy and the data collection algorithm are determined. Theoretical analysis and performance simulations indicate that MTDCM is an energy efficient mechanism. It has prominent features on balancing the energy consumption and prolonging the network lifetime.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.78-86
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• 2017

In this paper, we propose an energy-efficient scheduling scheme for real-time periodic tasks on a heterogeneous Grid computing system. The Grid system consists of heterogeneous processors providing the DVFS mechanism with a finite set of discrete clock frequencies. In order to save energy consumption, the proposed scheduling scheme assigns each real-time task to a processor with the least energy increment. Also the scheme activates a part of all available processors with unused processors powered off. Evaluation shows that the proposed scheme saves up to 70% energy consumption of the previous method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3243-3256
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• 2020

Recent years have shown a great interest of public in buying and selling of crypto/digital currency. With hundreds of digital currencies in financial market, bitcoin remains the most widely used, adapted, and accepted currency around the world. However, the critics of bitcoin still consider it a threat to modern day power usage. This paper discusses the important pitfalls, pros, and cons related to bitcoin's energy consumption. The paper begins by highlighting the flexibilities cryptocurrency can bring to online money transfers compared to traditional 'fiat' architecture. Then, the focus of the paper entirely remains on listing various facts related to bitcoin's energy utilization including a brief description of several emerging approaches for energy optimization. This paper is concluded by revealing key current challenges associated to bitcoin's energy usage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.560-574
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• 2010

In this paper, the relationship between the energy efficiency and spectrum efficiency in a two-cell cellular network is obtained, and the impact of multi-antenna on the energy efficiency of cellular network is analyzed and modeled based on two-state Markovian wireless channels. Then, the energy efficiency of multi-cell cellular networks with co-channel interference is investigated. Simulation results verify the proposed model and the energy-spectrum efficiency tradeoffs in cellular networks with multi-antenna and co-channel interference.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.9-15
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• 2018

This paper proposes an energy efficient adaptive relay station ON/OFF scheme with different frequency reuse factors (FRFs) to enhance the system throughput and reduce the transmission energy consumption for the transparent mode of 2-hop cellular relay networks (CRNs) based on orthogonal frequency division multiple access and time division duplex. In the proposed scheme, the base station turns on or off the relay stations (RSs) when they are overutilized and undertuilized based on the traffic density of the cell coverage, respectively. Through the simulation results, we show that the proposed scheme outperforms the conventional CRN in terms of the energy consumption with the same system throughput. Further, in order to increase the system throughput with low energy consumption, the best way is FRF 1 when the number of operating RSs is up to 4 and FRF 2 otherwise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.