Keynote Speech 1: Leveraging Cloud and Fog Computing for Real-Time Applications: Resource Allocation and Scheduling Issues

2021 ◽  
Author(s):  
Helen D. Karatza
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Fog Computing ◽  
Keynote Speech ◽  
Real Time Applications

ENPP: Extended Non-preemptive PP-aware Scheduling for Real-time Cloud Services

2016 ◽  
Vol 6 (5) ◽  
pp. 2291
Author(s):  
Fereshteh Hoseini ◽  
Mostafa Ghobaei Arani ◽  
Alireza Taghizadeh
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Processing Time ◽  
Resource Constraints ◽  
Cloud Services ◽  
Scheduling Problems ◽  
Hard Problems ◽  
Real Time Applications ◽  
Simulation Results ◽  
Np Hard Problems

<p class="Abstract">By increasing the use of cloud services and the number of requests to processing tasks with minimum time and costs, the resource allocation and scheduling, especially in real-time applications become more challenging. The problem of resource scheduling, is one of the most important scheduling problems in the area of NP-hard problems. In this paper, we propose an efficient algorithm is proposed to schedule real-time cloud services by considering the resource constraints. The simulation results show that the proposed algorithm shorten the processing time of tasks and decrease the number of canceled tasks.</p>

Expounding the Edge/Fog Computing Infrastructures for Data Science

2018 ◽  
pp. 1-32 ◽  
Author(s):  
Pethuru Raj ◽  
Pushpa J.
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Analytical Methods ◽  
Data Analytics ◽  
Data Science ◽  
Storage Systems ◽  
Fog Computing ◽  
Next Generation ◽  
Distributed Source ◽  
Real Time Applications

Data is the new fuel for any system to deliver smart and sophisticated services. Data is being touted as the strategic asset for any organization to plan ahead and provide next-generation capabilities with all the clarity and confidence. Whether data is internally sourced or aggregated from different and distributed source, it is essential for all kinds of data to be continuously and consciously collected, transmitted, cleansed, and hosted on storage systems. There are several types of analytical methods and machines to do deeper and decisive analytics on those curated and consolidated data to extract actionable insights in real-time. Precise and concise analytics guarantee perfect decision-making and action. We need competent and highly integrated analytics platform for speeding up, simplifying and streamlining data analytics, which is becoming a hard nut to crack due to the multi-structured and massive quantities of data. On the infrastructure front, we need highly optimized compute, storage and network infrastructure for achieving data analytics with ease. Another noteworthy point is that there are batch, real-time, and interactive processing of data. Most of the personal and professional applications need real-time insights in order to produce real-time applications. That is, real-time capture, processing, and decision-making are being insisted and hence the edge or fog computing concept has become very popular. This chapter is exclusively designed in order to tell all on how to accomplish real-time analytics on fog devices data.

scholarly journals An experimental study of fog and cloud computing in CEP-based Real-Time IoT applications

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Giovanny Mondragón-Ruiz ◽  
Alonso Tenorio-Trigoso ◽  
Manuel Castillo-Cara ◽  
Blanca Caminero ◽  
Carmen Carrión
Keyword(s):  
Real Time ◽  
Event Detection ◽  
Low Cost ◽  
Fog Computing ◽  
Iot Applications ◽  
Local Resources ◽  
Latency Analysis ◽  
Real Time Applications ◽  
Time Required ◽  
Processing Architecture

AbstractInternet of Things (IoT) has posed new requirements to the underlying processing architecture, specially for real-time applications, such as event-detection services. Complex Event Processing (CEP) engines provide a powerful tool to implement these services. Fog computing has raised as a solution to support IoT real-time applications, in contrast to the Cloud-based approach. This work is aimed at analysing a CEP-based Fog architecture for real-time IoT applications that uses a publish-subscribe protocol. A testbed has been developed with low-cost and local resources to verify the suitability of CEP-engines to low-cost computing resources. To assess performance we have analysed the effectiveness and cost of the proposal in terms of latency and resource usage, respectively. Results show that the fog computing architecture reduces event-detection latencies up to 35%, while the available computing resources are being used more efficiently, when compared to a Cloud deployment. Performance evaluation also identifies the communication between the CEP-engine and the final users as the most time consuming component of latency. Moreover, the latency analysis concludes that the time required by CEP-engine is related to the compute resources, but is nonlinear dependent of the number of things connected.

Sign in / Sign up

Export Citation Format

Share Document