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Guest Editorial Special Issue on Edge-Cloud Interplay Based on SDN and NFV for Next-Generation IoT Applications

Sahil Garg, Song Guo, Vincenzo Piuri, Kim-Kwang Raymond Choo, Balasubramanian Raman
2020 IEEE Internet of Things Journal  
In "Waiting time minimized charging and discharging strategy based on mobile edge computing supported by software-defined network," the authors proposed a mobileedge-computing-enabled charging and discharging  ...  scheme for electric vehicles, which aims to minimize the maximal waiting time of the charging stations.  ... 
doi:10.1109/jiot.2020.2999798 fatcat:sbfruvc4djh7haw3scb4u2jxku

Table of contents

2020 IEEE Internet of Things Journal  
Tanwar 6078 Waiting Time Minimized Charging and Discharging Strategy Based on Mobile Edge Computing Supported by Software-Defined Network .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Vijayakumar, and D. He 6056 On the Lifetime of Asynchronous Software-Defined Wireless Sensor Networks .. . . . . . . . . . . . A. Pal and A.  ... 
doi:10.1109/jiot.2020.3002639 fatcat:uyvmuopvtfgg5hz3xqekobi4ri

Green Internet of Vehicles (IoV) in the 6G Era: Toward Sustainable Vehicular Communications and Networking [article]

Junhua Wang, Kun Zhu, Ekram Hossain
2021 arXiv   pre-print
In this paper, we present the main considerations for green IoV from five different scenarios, including the communication, computation, traffic, Electric Vehicles (EVs), and energy harvesting management  ...  With the emergence of the sixth generation (6G) communications technologies, massive network infrastructures will be densely deployed and the number of network nodes will increase exponentially, leading  ...  As a key enabling technique, the software-defined networking (SDN) philosophy has been widely adopted in designing 5G-enabled vehicular networks.  ... 
arXiv:2108.11879v1 fatcat:l3fidzspwbhi5mmw55dds7vddu

Artificial Intelligence-Empowered Edge of Vehicles: Architecture, Enabling Technologies, and Applications

Hongjing Ji, Osama Alfarraj, Amr Tolba
2020 IEEE Access  
On this basis, combined with MEC technology and AI technology, computing and storage resources are placed on the edge of the network to provide real-time data processing while providing more efficient  ...  Therefore, mobile edge computing (MEC) has the advantages of effectively utilizing idle computing and storage resources at the edge of the network and reducing the network transmission delay.  ...  Reference [68] studied the optimal utility task offloading scheme in a heterogeneous vehicle network with multiple mobile edge computing servers under constraints on the reliability and waiting time  ... 
doi:10.1109/access.2020.2983609 fatcat:b45abdrxbracnbfpvtvtu5uxui

Smart power management for mobile handsets

Nachi K. Nithi, Adriaan J. de Lind van Wijngaarden
2011 Bell Labs technical journal  
The hardware has to simultaneously support applications that have varying run-times and varying communication and computation requirements.  ...  A network-based power manager can help determine when and how to support power-intensive applications, and may provide the handset with location-based coverage information and adjust the communication  ...  These models are based on parameters whose values are affected by numerous factors such as discharge rate, history of charge-discharge cycles, and operating temperature.  ... 
doi:10.1002/bltj.20478 fatcat:hlkgzvmejrdxblmuddvjvs7xs4

Energy-Aware Mobile Learning:Opportunities and Challenges

Arghir-Nicolae Moldovan, Stephan Weibelzahl, Cristina Hava Muntean
2014 IEEE Communications Surveys and Tutorials  
Discussions on the applicability and limitations of these approaches for mobile learning are also provided.  ...  However, while various energy saving solutions have been proposed in order to provide mobile users with extended device usage time, the areas of adaptive mobile learning and energy conservation in wireless  ...  ) that can be passive (i.e., pre-defined) or active (i.e., change in time based on content).  ... 
doi:10.1109/surv.2013.071913.00194 fatcat:lb46ka43yjefjdeusvuyphjj7q

Characterizing application scheduling on edge, fog, and cloud computing resources

Prateeksha Varshney, Yogesh Simmhan
2019 Software, Practice & Experience  
More recently, Edge and Fog computing resources have emerged on the wide-area network as part of Internet of Things (IoT) deployments.  ...  , based on a literature review.  ...  Preliminary surveys on Mobile Edge Computing (MEC), review task offloading strategies adopted by mobile edge devices that coexist with cloud resources, motivated by the growth in smart phones [6, 96]  ... 
doi:10.1002/spe.2699 fatcat:ywvul6s2j5hgthectdnbh7mnbq

2020 Index IEEE Internet of Things Journal Vol. 7

2020 IEEE Internet of Things Journal  
., and Bose, R., Rateless-Code-Based Secure Cooperative Transmission Scheme for Industrial IoT; JIoT July 2020 6550-6565 Jamalipour, A., see Murali, S., JIoT Jan. 2020 379-388 James, L.A., see Wanasinghe  ...  ., +, JIoT Oct. 2020 9870-9883 Waiting Time Minimized Charging and Discharging Strategy Based on Mobile Edge Computing Supported by Software-Defined Network.  ...  ., +, JIoT Sept. 2020 8590-8599 Waiting Time Minimized Charging and Discharging Strategy Based on Mobile Edge Computing Supported by Software-Defined Network.  ... 
doi:10.1109/jiot.2020.3046055 fatcat:wpyblbhkrbcyxpnajhiz5pj74a

Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

Leandro do C. Martins, Rafael D. Tordecilla, Juliana Castaneda, Angel A. Juan, Javier Faulin
2021 Energies  
In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems.  ...  These limitations impose additional driving range constraints when optimizing the distribution and mobility plans.  ...  Acknowledgments: This work has been partially supported by the Spanish Ministry of Science, Innovation, and Universities (PID2019-111100RB-C21-C22/AEI/10.13039/501100011033, RED2018-102642-T), the SEPIE  ... 
doi:10.3390/en14165131 fatcat:txzytoz5q5h3lj6at5i3nfhscu

Scheduling Strategies for Mobile D evices in BOINC

Arturo García, Mariela Curiel
2021 Zenodo  
Executing tasks on mobile devices brings some challenges that must be addressed, such as device heterogeneity, limited CPU power, limited memory, short battery life, mobility, and intermittent disconnections  ...  BOINC (Berkeley Open Infrastructure for Network Computing), the platform chosen in our research project that aims to process medical images using mobile phones, does not completely solve these challenges  ...  We propose to rewrite it to compute the amount of energy consumed from a particular mobile node using the discharge rate as defined by the SEAS strategy multiplied by the total time taken to complete the  ... 
doi:10.5281/zenodo.4445242 fatcat:qrfzecegrvgx3ghvob7bkwq5yq

Impact of Interdisciplinary Research on Planning, Running, and Managing Electromobility as a Smart Grid Extension

Alfredo D'elia, Fabio Viola, Federico Montori, Marco Di Felice, Luca Bedogni, Luciano Bononi, Alberto Borghetti, Paolo Azzoni, Paolo Bellavista, Daniele Tarchi, Randolf Mock, Tullio Salmon Cinotti
2015 IEEE Access  
Information, Internet of Energy, and Internet of Things) with edge computing capabilities supported by cloud-level services and with clean mapping between the logical and physical entities involved and  ...  In particular, this paper presents some of the results obtained by us in several European projects that refer to the development of a traffic and power network co-simulation tool for electro mobility planning  ...  Riverbed software has been used thanks to the Riverbed University Program.  ... 
doi:10.1109/access.2015.2499118 fatcat:vws5dwokwndefpcwriajc22axy

A survey of adaptation techniques in computation offloading

Arani Bhattacharya, Pradipta De
2017 Journal of Network and Computer Applications  
Computation offloading is a method of saving energy and time on resource-constrained mobile devices by executing some tasks on the cloud.  ...  The offloading decision problem depends on various parameters, like application characteristics, network conditions, hardware features, that influence the operating environment of an offloading system.  ...  for providing feedback on a draft of the manuscript.  ... 
doi:10.1016/j.jnca.2016.10.023 fatcat:dq2fjhlku5h4jbv5wm2cozvgdu

Efficient Energy Optimization Day-Ahead Energy Forecasting in Smart Grid Considering Demand Response and Microgrids

Fahad R. Albogamy, Ghulam Hafeez, Imran Khan, Sheraz Khan, Hend I. Alkhammash, Faheem Ali, Gul Rukh
2021 Sustainability  
Peak load, peak to average ratio, cost, energy cost, and carbon emission operation of appliances are reduced by the charging/discharging of electric vehicles, and energy storage systems are scheduled using  ...  In contrast, the emergence of bidirectional communication and power transfer technology enables electric vehicles (EVs) charging/discharging scheduling, load shifting/scheduling, and optimal energy sharing  ...  Acknowledgments: The authors would like to acknowledge the support from Taif University Researchers Supporting Project Number (TURSP-2020/264), Taif University, Taif, Saudi Arabia.  ... 
doi:10.3390/su132011429 fatcat:3t5vnngm4vdsxbaq46ch3kqspa

Reinforcement Learning Based EV Charging Management Systems – A review

Heba M. Abdullah, Adel Gastli, Lazhar Ben-Brahim
2021 IEEE Access  
This article reviews the existing literature related to the RL-based framework, objectives, and architecture for the charging coordination strategies of electric vehicles in the power systems.  ...  Unlike other machine learning approaches, the RL technique is based on maximizing the cumulative reward.  ...  The charging rates are defined based on the power system to avoid congestion, voltage violations, and overloading of electrical network equipment.  ... 
doi:10.1109/access.2021.3064354 fatcat:ap66p3hnnng25dp65e6agsjmbq

Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey [article]

Rudzidatul Akmam Dziyauddin, Dusit Niyato, Nguyen Cong Luong, Mohd Azri Mohd Izhar, Marwan Hadhari, Salwani Daud
2019 arXiv   pre-print
Since the mobility is critical on the VEC performance, the mobility model used in the VEC scenario is also discussed.  ...  As a solution, the computing capability has been recently proposed at the edge of vehicular networks, which is known as Vehicle Edge Computing (VEC).  ...  proposed the EV demands (i.e., charging and discharging) using a calendar policy whereby the calendars were scheduled by the appropriate fog data center based on the vehicle's location.  ... 
arXiv:1912.07803v1 fatcat:lup7y4n4wjeg7evw6h7rvovlu4
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