Abstract
This study proposes a Client-Fog-Cloud (CFC) multilayer data processing and aggregation framework that is designed to promote latency-sensitive applications in an IoT context. The framework is designed to address the current IoT-based challenges: wide distribution, massive uploading, low latency, and real-time interaction. The proposed framework consists of the device gateway, the fog server and the cloud. The device gateway collects data from clients and uploads it to the nearest fog node. Received data will be pre-processed and filtered by the fog server before being transferred to the cloud for further processing or storage. An abduction alert fog-based service was implemented to evaluate the proposed framework. Performance was evaluated by comparing the response time and the delay time of the proposed architecture with the traditional cloud computing architecture. Additionally, the aggregation rate was evaluated by simulating the speed of bike riding as well as the walking speed of young adults and elderly. Results show that comparing with the traditional cloud, our proposal noticeably reduces the average response time and the delay time (i.e., whether the newest data or the historical data are being queried). Results indicate the capability of the proposed framework to reduce the response time by 32% and the data transferred to the cloud by 30%.
Highlights
Fog computing is as a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awarenessInternet of Things (IoT) services [1,2,3,4,5,6,7]
Fog computing enables an innovative mixture of IoT-based services and applications for end-users as it effectively reduces both the service delay and the traffic load by empowering end User Equipment (UE) with multitier computing or service
Results show that the average response time for querying the newest data from the proposed framework is very low
Summary
Fog computing is as a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awarenessInternet of Things (IoT) services [1,2,3,4,5,6,7]. The emergence of latency-sensitive and location-aware IoT services issues additional challenges as the distant cloud is not suitable to meet the ultra-low latency requirements of these services, support location-aware applications, or scale to the magnitude of the data that these applications produce [9]. To address these challenges, fog computing extends the paradigm of the cloud by utilizing the capabilities of edge devices and users’ clients to compute, store, and exchange data among each other and with the cloud [10]. Data can be processed, and services can be provided flexibly at different tiers that are closer to UEs
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