Cognitive Engineering for Next Generation Computing

2021 ◽  
Keyword(s):  
Cognitive Engineering ◽  
Next Generation ◽  
Generation Computing

scholarly journals IoT-Fog A Communication Framework using Blockchain in the Internet of Things

2020 ◽  
Author(s):  
Tanweer Alam
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Fog Computing ◽  
Emerging Technology ◽  
Smart Devices ◽  
The Internet ◽  
Next Generation ◽  
Communication Framework ◽  
Generation Computing ◽  
The Internet Of Things

<p>The fog computing is the emerging technology to compute, store, control and connecting smart devices with each other using cloud computing. The Internet of Things (IoT) is an architecture of uniquely identified interrelated physical things, these physical things are able to communicate with each other and can transmit and receive information. <a>This research presents a framework of the combination of the Internet of Things (IoT) and Fog computing. The blockchain is also the emerging technology that provides a hyper, distributed, public, authentic ledger to record the transactions. Blockchains technology is a secured technology that can be a boon for the next generation computing. The combination of fog, blockchains, and IoT creates a new opportunity in this area. In this research, the author presents a middleware framework based on the blockchain, fog, and IoT. The framework is implemented and tested. The results are found positive. </a></p>

Designing a Forensic-Enabling Cloud Ecosystem

2015 ◽  
pp. 566-579
Author(s):  
Keyun Ruan
Keyword(s):  
Cloud Computing ◽  
Research And Development ◽  
Technological Innovation ◽  
Design Thinking ◽  
Legal Framework ◽  
Next Generation ◽  
Generation Computing ◽  
Major Transition ◽  
Computing Infrastructure

Cloud computing is a major transition, and it comes at a unique historical and strategic time for applying foundational design thinking to secure the next-generation computing infrastructure and enable waves of business and technological innovation. In this chapter, the researcher summarizes six key research and development areas for designing a forensic-enabling cloud ecosystem, including architecture and matrix, standardization and strategy, evidence segregation, security and forensic integration, legal framework, and privacy.

Two-dimensional materials for next-generation computing technologies

2020 ◽  
Vol 15 (7) ◽  
pp. 545-557 ◽  
Author(s):  
Chunsen Liu ◽  
Huawei Chen ◽  
Shuiyuan Wang ◽  
Qi Liu ◽  
Yu-Gang Jiang ◽  
...  
Keyword(s):  
Two Dimensional ◽  
Next Generation ◽  
Computing Technologies ◽  
Generation Computing ◽  
Two Dimensional Materials

Special issue on parallel applications for in-situ computing on the next-generation computing platforms

2018 ◽  
Vol 33 (3) ◽  
pp. 429-430
Author(s):  
Gabriele Mencagli ◽  
Felipe MG França ◽  
Cristiana Barbosa Bentes ◽  
Leandro Augusto Justen Marzulo ◽  
Mauricio Lima Pilla
Keyword(s):  
Parallel Applications ◽  
Next Generation ◽  
Special Issue ◽  
Generation Computing ◽  
Computing Platforms

scholarly journals Efficient Task and Data Scheduling Policy for Vehicular Fog Computing Based on Link Weight

2019 ◽  
Vol 8 (4) ◽  
pp. 10693-10697
Keyword(s):  
Data Dissemination ◽  
Scheduling Algorithm ◽  
Fog Computing ◽  
Vehicular Network ◽  
Next Generation ◽  
New Paradigm ◽  
Multiple Parameters ◽  
Link Weight ◽  
Time Period ◽  
Generation Computing

Vehicular network has several applications in the smart city and IoT. Recently with the advancement in the computing technology such as fog computing and its application in the vehicular network and its services, a new paradigm known as vehicular fog computing has evolved as a hot topic of investigation in the research community because of the next generation computing and communication requirements. Vehicular fog computing can be used to solve the issues of next generation computing and communication scenario. There are several issues in vehicular fog computing. Efficient task computing and data dissemination is an important issue. Several approaches are proposed by different authors to solve the issues, but none of them has addressed the service completion and failure rate which is very important in the vehicular scenario as the vehicles move very fast and its contact time with the RSU controller is limited. The task has to be completed by the vehicular server within that time period, otherwise computation will fail. Once the computation and communication fails, the RSU controller will reinitiate to form the vehicular fog resulting high overhead. In this paper we address this issue and proposed an efficient scheduling algorithm based on multiple parameters namely queue length, response time and link weight. We simulated the algorithm using java and compared with the existing algorithm showing better performance.

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