Autonomic IoT Battery Management with Fog Computing

2019 ◽  
pp. 89-103 ◽  
Author(s):  
Hugo Vaz Sampaio ◽  
Ana Luiza Cordova de Jesus ◽  
Ricardo do Nascimento Boing ◽  
Carlos Becker Westphall
Keyword(s):  
Fog Computing ◽  
Battery Management

scholarly journals Battery Management in a Green Fog-Computing Node: a Reinforcement-Learning Approach

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 21126-21138 ◽  
Author(s):  
Stefania Conti ◽  
Giuseppe Faraci ◽  
Rosario Nicolosi ◽  
Santi Agatino Rizzo ◽  
Giovanni Schembra
Keyword(s):  
Reinforcement Learning ◽  
Fog Computing ◽  
Learning Approach ◽  
Battery Management ◽  
Computing Node

Virtualized Fog Network with Load Balancing for IoT based Fog-to-Cloud

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Istabraq M. Al-Joboury ◽  
Emad H. Al-Hemiary
Keyword(s):  
Load Balancing ◽  
Packet Loss ◽  
Fog Computing ◽  
Transport Protocol ◽  
Network Simulator ◽  
Huge Number ◽  
Message Queue ◽  
Limited Bandwidth ◽  
Cloud Architecture ◽  
Fog Network

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.

Simulation and Emulation Tools for Fog Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Simar Preet Singh ◽  
Rajesh Kumar ◽  
Anju Sharma ◽  
S. Raji Reddy ◽  
Priyanka Vashisht
Keyword(s):  
Quality Of Service ◽  
Programming Languages ◽  
Traffic Management ◽  
Fog Computing ◽  
Research Work ◽  
Research Experience ◽  
Computing Paradigm ◽  
Quality Of Service Parameters ◽  
User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

scholarly journals Evaluating TCP performance of routing protocols for traffic exchange in street-parked vehicles based fog computing infrastructure

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Awangku Muhammad Iqbal Yura ◽  
S. H. Shah Newaz ◽  
Fatin Hamadah Rahman ◽  
Thien Wan Au ◽  
Gyu Myoung Lee ◽  
...  
Keyword(s):  
Routing Protocols ◽  
Fog Computing ◽  
Tcp Performance ◽  
Computing Infrastructure
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