Real-time Task Offloading for Data and Computation Intensive Services in Vehicular Fog Computing Environments

Author(s):  
Chunhui Liu ◽  
Kai Liu ◽  
Xincao Xu ◽  
Hualing Ren ◽  
Feiyu Jin ◽  
...  
2018 ◽  
Vol 87 ◽  
pp. 198-212 ◽  
Author(s):  
Juan Luis Pérez ◽  
Alberto Gutierrez-Torre ◽  
Josep Ll. Berral ◽  
David Carrera

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2830 ◽  
Author(s):  
Long Mai ◽  
Nhu-Ngoc Dao ◽  
Minho Park

The emerging fog computing technology is characterized by an ultralow latency response, which benefits a massive number of time-sensitive services and applications in the Internet of things (IoT) era. To this end, the fog computing infrastructure must minimize latencies for both service delivery and execution phases. While the transmission latency significantly depends on external factors (e.g., channel bandwidth, communication resources, and interferences), the computation latency can be considered as an internal issue that the fog computing infrastructure could actively self-handle. From this view point, we propose a reinforcement learning approach that utilizes the evolution strategies for real-time task assignment among fog servers to minimize the total computation latency during a long-term period. Experimental results demonstrate that the proposed approach reduces the latency by approximately 16.1% compared to the existing methods. Additionally, the proposed learning algorithm has low computational complexity and an effectively parallel operation; therefore, it is especially appropriate to be implemented in modern heterogeneous computing platforms.


2022 ◽  
pp. 245-261
Author(s):  
Geetha J. J. ◽  
Jaya Lakshmi D. S. ◽  
Keerthana Ningaraju L. N.

Distributed caching is one such system used by dynamic high-traffic websites to process the incoming user requests to perform the required tasks in an efficient way. Distributed caching is currently employing hashing algorithm in order to serve its purpose. A significant drawback of hashing in this circumstance is the addition of new servers that would result in a change in the previous hashing method (rehashing), hence, goes into a rigmarole. Thus, we need an effective algorithm to address the problem. This technique has served as a solution for distributed and rehashing problems. Most of upcoming internet of things will have to be latency aware and will not afford the data transmission and computation time in the cloud servers. The real-time processing in proximal distance device would be much needed. Hence, the authors aim to employ a real-time task scheduling algorithm. Computations referring to the user requests that are to be handled by the servers can be efficiently handled by consistent hashing algorithms.


Telecom ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 489-517
Author(s):  
Eliza Gomes ◽  
Felipe Costa ◽  
Carlos De Rolt ◽  
Patricia Plentz ◽  
Mario Dantas

In this article, we present a comprehensive survey on time-sensitive applications implemented in fog computing environments. The goal is to research what applications are being implemented in fog computing architectures and how the temporal requirements of these applications are being addressed. We also carried out a comprehensive analysis of the articles surveyed and separate them into categories, according to a pattern found in them. Our research is important for the area of real-time systems since the concept of systems that respond in real time has presented various understandings and concepts. This variability of concept has been due to the growing requirements for fast data communication and processing. Therefore, we present different concepts of real-time and near real-time systems found in the literature and currently accepted by the academic-scientific community. Finally, we conduct an analytical discussion of the characteristics and proposal of articles.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3715
Author(s):  
Ioan Ungurean ◽  
Nicoleta Cristina Gaitan

In the design and development process of fog computing solutions for the Industrial Internet of Things (IIoT), we need to take into consideration the characteristics of the industrial environment that must be met. These include low latency, predictability, response time, and operating with hard real-time compiling. A starting point may be the reference fog architecture released by the OpenFog Consortium (now part of the Industrial Internet Consortium), but it has a high abstraction level and does not define how to integrate the fieldbuses and devices into the fog system. Therefore, the biggest challenges in the design and implementation of fog solutions for IIoT is the diversity of fieldbuses and devices used in the industrial field and ensuring compliance with all constraints in terms of real-time compiling, low latency, and predictability. Thus, this paper proposes a solution for a fog node that addresses these issues and integrates industrial fieldbuses. For practical implementation, there are specialized systems on chips (SoCs) that provides support for real-time communication with the fieldbuses through specialized coprocessors and peripherals. In this paper, we describe the implementation of the fog node on a system based on Xilinx Zynq UltraScale+ MPSoC ZU3EG A484 SoC.


Sign in / Sign up

Export Citation Format

Share Document