scholarly journals Improved Health Care System in Fog Computing and WSN

2019 ◽  
Vol 9 (1) ◽  
pp. 4269-4271
Keyword(s):  
Health Care ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
The Novel ◽  
Distributed Network ◽  
Task Scheduling Algorithm ◽  
The One ◽  
Advanced Computing ◽  
Present World ◽  
The Internet Of Things

Fog computing is most widely used in many applications. This is the most advanced computing of the various services in the cloud. Fog is considered as another layer that is a distributed network and is similarly having an association with cloud computing and the internet of things (IoT). Health care is the one of the dominating domain in present world. The healthcare with IoT has some of the drawbacks such as limited storage, computing and accessing. To improve the performance the task scheduling algorithm is implemented. To overcome this, in this paper, the novel healthcare system with fog computing and WSN is implemented. Results show the performance of the proposed system.

scholarly journals Fog Task Scheduling using Clustering based Randomized Round Robin

2021 ◽  
Vol 22 (3) ◽  
pp. 295-302
Author(s):  
Shahid Sultan Hajam ◽  
Shabir Ahmad Sofi
Keyword(s):  
Internet Of Things ◽  
Task Scheduling ◽  
Clustering Algorithm ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Round Robin ◽  
The Internet ◽  
Delay Sensitive ◽  
Task Scheduling Algorithm ◽  
The Internet Of Things

Fog computing serves the delay-sensitive applications of the Internet of Things (IoT) in more efficient means than the cloud. The heterogeneity of the tasks and the limited fog resources make task scheduling a complicated job. This paper proposes a clustering based task scheduling algorithm. Specifically, the K-Means++ clustering algorithm is used for clustering the fog nodes. Randomized round robin, a task scheduling algorithm is applied to each cluster. The results show that the proposed algorithm reduces the system's average waiting time.

scholarly journals Fog computing scheduling algorithm for smart city

2021 ◽  
Vol 11 (3) ◽  
pp. 2219
Author(s):  
Ahmad Mohammad Alsmadi ◽  
Roba Mahmoud Ali Aloglah ◽  
Nisrein Jamal sanad Abu-darwish ◽  
Ahmad Al Smadi ◽  
Muneerah Alshabanah ◽  
...  
Keyword(s):  
Smart Cities ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Smart Devices ◽  
The Internet ◽  
5G Networks ◽  
Sustainable Infrastructure ◽  
Time Latency ◽  
The Internet Of Things ◽  
Fast Transmission

With the advent of the number of smart devices across the globe, increasing the number of users using the Internet. The main aim of the fog computing (FC) paradigm is to connect huge number of smart objects (billions of object) that can make a bright future for smart cities. Due to the large deployments of smart devices, devices are expected to generate huge amounts of data and forward the data through the Internet. FC also refers to an edge computing framework that mitigates the issue by applying the process of knowledge discovery using a data analysis approach to the edges. Thus, the FC approaches can work together with the internet of things (IoT) world, which can build a sustainable infrastructure for smart cities. In this paper, we propose a scheduling algorithm namely the weighted round-robin (WRR) scheduling algorithm to execute the task from one fog node (FN) to another fog node to the cloud. Firstly, a fog simulator is used with the emergent concept of FC to design IoT infrastructure for smart cities. Then, spanning-tree routing (STP) protocol is used for data collection and routing. Further, 5G networks are proposed to establish fast transmission and communication between users. Finally, the performance of our proposed system is evaluated in terms of response time, latency, and amount of data used.

scholarly journals Task Scheduling Algorithm Based on Improved Firework Algorithm in Fog Computing

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 32385-32394 ◽  
Author(s):  
Shudong Wang ◽  
Tianyu Zhao ◽  
Shanchen Pang
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Task Scheduling Algorithm

Optimization of makespan and resource utilization in the fog computing environment through task scheduling algorithm

2020 ◽  
Vol 18 (01) ◽  
pp. 1941025
Author(s):  
R. Vijayalakshmi ◽  
V. Vasudevan ◽  
Seifedine Kadry ◽  
R. Lakshmana Kumar
Keyword(s):  
Resource Utilization ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Utilization Rate ◽  
Test Results ◽  
Computing Environment ◽  
Computing Model ◽  
Task Scheduling Algorithm ◽  
The Mean

The Fog computing is rising as a dominant and modern computing model to deliver Internet of Things (IoT) computations, which is an addition to the cloud computing standard to get it probable to perform the IoT requests in the network of edge. In those above independent and dispersed environment, resource allocation is vital. Therefore, scheduling will be a test to enhance potency and allot resources properly to the tasks. This paper offers a distinct task scheduling algorithm in the fog computing environment that tries to depreciate the makespan and maximize resource utilization. This algorithm catalogues the task based on the mean Suffrage value. The suggested algorithm gives much resource utilization and diminishes makespan. Our offered algorithm is compared with different alive scheduling for performance investigation, and test results confirm that our algorithm has a more significant resource utilization rate and low makespan than other familiar algorithms.

scholarly journals A collaborative cloud-edge computing framework in distributed neural network

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shihao Xu ◽  
Zhenjiang Zhang ◽  
Michel Kadoch ◽  
Mohamed Cheriet
Keyword(s):  
Neural Network ◽  
Ant Colony Algorithm ◽  
Scheduling Algorithm ◽  
Task Assignment ◽  
Edge Computing ◽  
Network Training ◽  
Task Scheduling Algorithm ◽  
Current Task ◽  
Computing Framework ◽  
The Internet Of Things

Abstract The emergence of edge computing provides a new solution to big data processing in the Internet of Things (IoT) environment. By combining edge computing with deep neural network, it can make better use of the advantages of multi-layer architecture of the network. However, the current task offloading and scheduling frameworks for edge computing are not well applicable to neural network training tasks. In this paper, we propose a task model offloading algorithm by considering how to optimally deploy neural network model into the edge nodes. An adaptive task scheduling algorithm is also designed to adaptively optimize the task assignment by using the improved ant colony algorithm. Based on them, a collaborative cloud-edge computing framework is proposed, which can be used in the distributed neural network. Moreover, this framework sets up some mechanisms so that the cloud can collaborate with edge computing in the work. The simulation results show that the framework can reduce time delay and energy consumption, and improve task accuracy.

scholarly journals A Task Scheduling Algorithm Based on Classification Mining in Fog Computing Environment

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lindong Liu ◽  
Deyu Qi ◽  
Naqin Zhou ◽  
Yilin Wu
Keyword(s):  
Task Scheduling ◽  
Completion Time ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Apriori Algorithm ◽  
Distributed Environment ◽  
Data Mining Technique ◽  
Task Scheduling Algorithm ◽  
Increase Productivity ◽  
Minimum Completion Time

Fog computing (FC) is an emerging paradigm that extends computation, communication, and storage facilities towards the edge of a network. In this heterogeneous and distributed environment, resource allocation is very important. Hence, scheduling will be a challenge to increase productivity and allocate resources appropriately to the tasks. We schedule tasks in fog computing devices based on classification data mining technique. A key contribution is that a novel classification mining algorithm I-Apriori is proposed based on the Apriori algorithm. Another contribution is that we propose a novel task scheduling model and a TSFC (Task Scheduling in Fog Computing) algorithm based on the I-Apriori algorithm. Association rules generated by the I-Apriori algorithm are combined with the minimum completion time of every task in the task set. Furthermore, the task with the minimum completion time is selected to be executed at the fog node with the minimum completion time. We finally evaluate the performance of I-Apriori and TSFC algorithm through experimental simulations. The experimental results show that TSFC algorithm has better performance on reducing the total execution time of tasks and average waiting time.

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

Elementy poetyki ludowej w powieści Rzeczy uprzyjemniające. Utopia T. Bołdak-Janowskiej

2020 ◽  
pp. 182-197
Author(s):  
Agnieszka Goral
Keyword(s):  
Fairy Tales ◽  
Text Analysis ◽  
Literary Text ◽  
Source Material ◽  
Human Existence ◽  
The Other ◽  
The Novel ◽  
Literary Works ◽  
The One ◽  
Cultural Features

The aim of the article is to analyse the elements of folk poetics in the novel Pleasant things. Utopia by T. Bołdak-Janowska. The category of folklore is understood in a rather narrow way, and at the same time it is most often used in critical and literary works as meaning a set of cultural features (customs and rituals, beliefs and rituals, symbols, beliefs and stereotypes) whose carrier is the rural folk. The analysis covers such elements of the work as place, plot, heroes, folk system of values, folk rituals, customs, and symbols. The description is conducted based on the analysis of source material as well as selected works in the field of literary text analysis and ethnolinguistics. The analysis shows that folk poetics was creatively associated with the elements of fairy tales and fantasy in the studied work, and its role consists of – on the one hand – presenting the folk world represented and – on the other – presenting a message about the meaning of human existence.

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