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An Intelligent Adaptive Algorithm for Servers Balancing and Tasks Scheduling over Mobile Fog Computing Networks

Xuejing Li, Yajuan Qin, Huachun Zhou, Du Chen, Shujie Yang, Zhewei Zhang
2020 Wireless Communications and Mobile Computing  
to generate intelligent adaptive strategies related with load balancing of collaborative servers and dynamic scheduling of sequential tasks.  ...  Based on the proposed algorithm and software-defined networking technology, the tasks can be executed cooperatively by the user device and the servers in the MFC network.  ...  The Proposed Intelligent Adaptive Algorithm In this section, we propose an intelligent adaptive algorithm (IAA) to generate strategies to achieve load balancing of collaborative servers and dynamic scheduling  ... 
doi:10.1155/2020/8863865 fatcat:o7acjlgsgbffdo7g5hbb4lku5y

Optimized Task Group Aggregation-Based Overflow Handling on Fog Computing Environment Using Neural Computing

Harwant Singh Arri, Ramandeep Singh Khosa, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Ill Chul Doo
2021 Mathematics  
Using Machine Learning as a component of neural computing, we developed an improved Task Group Aggregation (TGA) overflow handling system for fog computing environments.  ...  Fog computing, for example, demonstrates how artificial intelligence-based systems can be made more efficient.  ...  The issue of resource scheduling and task overflow handling in fog computing can be handled by reducing response time and balancing the load on servers.  ... 
doi:10.3390/math9192522 fatcat:qfwgbpwbfrg2ristcmpvmzpkde

QoS-Aware Placement of Tasks on a Fog Cluster in an Edge Computing Environment

Elarbi Badidi
2020 Journal of Ubiquitous Systems and Pervasive Networks  
With increasing deployments of fog nodes and fog clusters, we propose an architecture for the placement of IoT applications tasks on a cluster of fog nodes in the vicinity of the application's data sources  ...  Fog computing-based solutions for these services are increasingly becoming attractive because of the low latency they can guarantee.  ...  Acknowledgements This work is supported by the UAEU Program for Advanced Research Grant N. G00003443.  ... 
doi:10.5383/juspn.13.01.002 fatcat:qeuep5eiefdplpz6vtlhyvluci

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

Hongjing Ji, Osama Alfarraj, Amr Tolba
2020 IEEE Access  
Artificial intelligence (AI) technology can adapt to rapidly changing dynamic environments to provide multiple task requirements for resource allocation, computational task scheduling, and vehicle trajectory  ...  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.  ...  The task offloading scheme is analyzed in the scenario of an independent mobile edge computing device server and in the scenario of a collaborative mobile edge computing device server.  ... 
doi:10.1109/access.2020.2983609 fatcat:b45abdrxbracnbfpvtvtu5uxui

New Application Task Offloading Algorithms for Edge, Fog, and Cloud Computing Paradigms

Sungwook Kim, Miguel Garcia-Pineda
2020 Wireless Communications and Mobile Computing  
In this study, we design a new task offloading scheme by considering the challenges of future edge, fog and cloud computing paradigms.  ...  The primary advantage of our bargaining-based approach is to provide an axiom-based strategic solution for the task offloading problem while dynamically responding to the current network environments.  ...  At the remote cloud, resources are dispatched and allocated dynamically based on traffic adaptation using a cognitive engine and an intelligent mobile-traffic module to balance the network load.  ... 
doi:10.1155/2020/8888074 fatcat:z46x2myvprat5pfvrvwa5yg754

Intelligent Load-Balancing Framework for Fog-Enabled Communication in Healthcare

Swati Malik, Kamali Gupta, Deepali Gupta, Aman Singh, Muhammad Ibrahim, Arturo Ortega-Mansilla, Nitin Goyal, Habib Hamam
2022 Electronics  
Thus, in this paper, a fog-based framework is proposed that can balance the load among fog nodes for handling the challenging communication and processing requirements of intelligent real-time applications  ...  using sensor-enabled smart and intelligent IoT devices for providing extensive care to patients relative to the symmetric concept.  ...  [24] proposed an energy-aware load balancing and scheduling solution based on the fog network.  ... 
doi:10.3390/electronics11040566 fatcat:t5ylrak2vnbhhkqfdi6a4t7dnm

Scheduling in Cloud and Fog Architecture: Identification of Limitations and Suggestion of Improvement Perspectives

Celestino Barros, Vítor Rocio, André Sousa, Hugo Paredes
2020 Journal of Information Systems Engineering & Management  
In this paper, we conducted a systematic review of the literature on the main task by: scheduling algorithms in the existing cloud and fog architecture; studying and discussing their limitations, and we  ...  explored and suggested some perspectives for improvement.  ...  Zhu et al. (2015) Priority-Based Two- Phase Min-Min Scheduling Policy (PTMM) Oueis, Strinati, and Barbarossa (2015) Algorithm Designed for Cluster Formation and Load Balancing for Fog Computing  ... 
doi:10.29333/jisem/8429 fatcat:y7swypxmovainkd6dgucpoby3q

Guest Editorial Emerging Computing Offloading for IoTs: Architectures, Technologies, and Applications

Jiannong Cao, Deyu Zhang, Haibo Zhou, Peng-Jun Wan
2019 IEEE Internet of Things Journal  
We hope that the special issue can serve as a good reference for scientists, engineers, and academicians in the area of computation offloading in IoTs. JIANNONG CAO  ...  We also would like to thank all the reviewers who dedicated their efforts in reviewing the papers, and for their valuable comments and constructive suggestions to significantly improve the quality of the  ...  detect coverage holes and schedule to offload the communication-intensive and computing-intensive tasks from IoT nodes to edge servers.  ... 
doi:10.1109/jiot.2019.2921217 fatcat:yxc2v2whm5gtzhpefivtgt5uxy

A Comparative Study of Various Machine Learning Algorithms in Fog Computing

2021 International Journal of Advanced Trends in Computer Science and Engineering  
Hence, machine-learning algorithms occupy central place in visualizing robust and effective Fog networks.  ...  Cloud services face the down side of connectivity and latency. Fog computing, as a complementing technology for Cloud answers the issues of latency and connectivity in the Cloud.  ...  The optimal design for load balancing and task scheduling is greatly applicable in Vehicle Adhoc Networks (VANETs).  ... 
doi:10.30534/ijatcse/2021/155032021 fatcat:qwyp4mecobantjdsol5uwfii2i

SDN Based Fog Computing: A Review

Shavan Askar, Baydaa Hassan Husain, Tarik A. Rashid
2021 Zenodo  
While Software Defined Networking (SDN) is a network engineering technique that permits network control and 'programming' through software applications in an intelligent and centralized way.  ...  Fog Computing (FC) is a system that connects cloud computing (CC) with the Internet of Things (IoT).  ...  Fog network nodes based on SDN, An energy-conscious load and preparation system balances for mixed job robotics, allows for optimum scheduling and load control.  ... 
doi:10.5281/zenodo.5221036 fatcat:5giirjyygbhf3kywwiizaysfv4

SDN Based Fog Computing: A Review

Shavan Askar, Baydaa Hassan Husain, Tarik A. Rashid
2021 Zenodo  
While Software Defined Networking (SDN) is a network engineering technique that permits network control and 'programming' through software applications in an intelligent and centralized way.  ...  Fog Computing (FC) is a system that connects cloud computing (CC) with the Internet of Things (IoT).  ...  Fog network nodes based on SDN, An energy-conscious load and preparation system balances for mixed job robotics, allows for optimum scheduling and load control.  ... 
doi:10.5281/zenodo.5221688 fatcat:3jahl3hwdzdc5jdu3cgp5c44ku

Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm

Wenjuan Li, Shihua Cao, Keyong Hu, Jian Cao, Rajkumar Buyya, Honghao Gao
2021 Security and Communication Networks  
Furthermore, in order to fully consider the reasonability and load balance in service coordination and task scheduling, Berger's model and the conception of service justice are introduced to perform reasonable  ...  The cloud-fog-edge hybrid system is the evolution of the traditional centralized cloud computing model.  ...  Algorithm 2 shows how task scheduler (running on an access point) chooses the suitable resources/servers for mobile tasks triggered by a user or a smart thing.  ... 
doi:10.1155/2021/5563312 fatcat:h4t5wzxfibcorknahfm2utxq5u

Comprehensive Analysis of Resource Allocation and Service Placement in Fog and Cloud Computing

A. S. Gowri, P.Shanthi Bala, Immanuel Zion
2021 International Journal of Advanced Computer Science and Applications  
To withstand such demands, Cloud and Fog computing architectures are the viable solutions, due to their utility kind and accessibility nature.  ...  The survey recommends techniques like Reinforcement Learning (RL) and Energy Efficient Computing (EEC) in Fog and Cloud to escalate the efficacy of RASP.  ...  over-provisioning approach, scheduling algorithm, rate-limiting Simulated with 10-50 cloudlets (tasks) scale and tolerate dynamism of servers, additional mechanism to enforce SLA enforcement period used  ... 
doi:10.14569/ijacsa.2021.0120308 fatcat:mmftlutfa5dstphhsaxfvvu6ti

IEEE Access Special Section Editorial: Communication and Fog/Edge Computing Toward Intelligent Connected Vehicles (ICVS)

Lei Shu, Junhui Zhao, Yi Gong, Changqing Luo, Tim Gordon
2021 IEEE Access  
These kinds of applications typically require significant computing power to perform computation-intensive and latency-sensitive tasks generated by the vehicle sensors for low-latency response.  ...  To tackle the challenge, fog/edge computing is proposed as innovative computing paradigms to extend computing capacity to the network edge to meet the requirements.  ...  Specifically, leveraging the idea of task scalability, a model for balancing computing quality and resource consumption is introduced to exploit the computational resources fully.  ... 
doi:10.1109/access.2021.3071260 doaj:3c15b73f232c41a199e81c178ee3a34d fatcat:c5xvpfeh3zf5fgyzkpzmdkw3jy

Machine Learning-Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks

Shuchen Zhou, Waqas Jadoon, Junaid Shuja, Zhihan Lv
2021 Complexity  
This paper presents an in-depth study and analysis of offloading strategies for lightweight user mobile edge computing tasks using a machine learning approach.  ...  Subsequently, two optimization algorithms are designed: for the relaxation optimization problem, an iterative optimization algorithm based on the Lagrange dual method is designed; based on the branch-and-bound  ...  on the quality of service of tasks and the efficiency of using computational resources of fog nodes. erefore, the task scheduling algorithm and the computational resource allocation algorithm of the fog  ... 
doi:10.1155/2021/6455617 fatcat:gs3fdutosjfrvj63k7hlpkajzm
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