| Title | An Edge Computing Paradigm for Time-Sensitive Applications |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Jain, Arpit, Jat, Dharm Singh |
| Conference Name | 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4) |
| Date Published | jul |
| Keywords | cloud computing, Computational modeling, Computer architecture, delays, edge computing, Fog Computing, IoT, pubcrawl, QoS, quality of service, resilience, Resiliency, Sensors, Stochastic Computing Security |
| Abstract | Edge computing (EC) is a new developing computing technology where data are collected, and analysed nearer to the edge or sources of the data. Cloud to the edge, intelligent applications and analytics are part of the IoT applications and technology. Edge computing technology aims to bring cloud computing features near to edge devices. For time-sensitive applications in cloud computing, architecture massive volume of data is generated at the edge and stored and analysed in the cloud. Cloud infrastructure is a composition of data centres and large-scale networks, which provides reliable services to users. Traditional cloud computing is inefficient due to delay in response, network delay and congestion as simultaneous transactions to the cloud, which is a centralised system. This paper presents a literature review on cloud-based edge computing technologies for delay-sensitive applications and suggests a conceptual model of edge computing architecture. Further, the paper also presents the implementation of QoS support edge computing paradigm in Python for further research to improve the latency and throughput for time-sensitive applications. |
| DOI | 10.1109/WorldS450073.2020.9210325 |
| Citation Key | jain_edge_2020 |
An Edge Computing Paradigm for Time-Sensitive Applications