Block-D2D: Blockchain-enabled Cooperative D2D-assisted Fog Computing Scheme under Imperfect CSI

Author(s):  
Rajesh Gupta ◽  
Tejal Rathod ◽  
Sudeep Tanwar
2018 ◽  
Vol 7 (2.27) ◽  
pp. 82
Author(s):  
Tejinder Pal Singh ◽  
Er. Nitika Kapoor

The vehicular adhoc network is the data oriented in network in which information should be passed with least delay. The vehicle adhoc network is the decentralized type of network in which vehicles to vehicle and vehicle to road side communication is possible. The Fog computing is the advance computing scheme to store small amount of data. The routing is the major issue of vehicular adhoc network due to high mobility of the vehicle nodes. In this research work, multicasting based routing scheme is proposed for path establishment from source to destination. In the proposed scheme root vehicles are selected for path establishment from source to destination. When the data will be received on the road side unit then k-mean clustering will be applied which divide data into clusters which define that either it can be saved on cloud or on fog server based on quantity of data. The performance of proposed scheme is testing in NS2 and proposed scheme performs well in terms of PDR and route lifetime  


2020 ◽  
Vol 69 (5) ◽  
pp. 5481-5493
Author(s):  
Chuan Lin ◽  
Guangjie Han ◽  
Xingyue Qi ◽  
Mohsen Guizani ◽  
Lei Shu

2020 ◽  
Vol 5 (3) ◽  
pp. 142-149
Author(s):  
Bui Quoc Doanh ◽  
Ta Chi Hieu ◽  
Truong Sy Nam ◽  
Pham Thi Phuong Anh ◽  
Pham Thanh Hiep

Author(s):  
Istabraq M. Al-Joboury ◽  
Emad H. Al-Hemiary

Fog Computing is a new concept made by Cisco to provide same functionalities of Cloud Computing but near to Things to enhance performance such as reduce delay and response time. Packet loss may occur on single Fog server over a huge number of messages from Things because of several factors like limited bandwidth and capacity of queues in server. In this paper, Internet of Things based Fog-to-Cloud architecture is proposed to solve the problem of packet loss on Fog server using Load Balancing and virtualization. The architecture consists of 5 layers, namely: Things, gateway, Fog, Cloud, and application. Fog layer is virtualized to specified number of Fog servers using Graphical Network Simulator-3 and VirtualBox on local physical server. Server Load Balancing router is configured to distribute the huge traffic in Weighted Round Robin technique using Message Queue Telemetry Transport protocol. Then, maximum message from Fog layer are selected and sent to Cloud layer and the rest of messages are deleted within 1 hour using our proposed Data-in-Motion technique for storage, processing, and monitoring of messages. Thus, improving the performance of the Fog layer for storage and processing of messages, as well as reducing the packet loss to half and increasing throughput to 4 times than using single Fog server.


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