MeFoRE: QoE based resource estimation at Fog to enhance QoS in IoT
Abstract
Internet of Things (IoT) is now transitioning from theory to practice. This means that a lot of data will be generated and the management of this data is going to be a big challenge. To transform IoT into reality and build upon realistic and more useful services, better resource management is required at the perception layer. In this regard, Fog computing plays a very vital role. With the advent of Vehicular Ad hoc Networks (VANET) and remote healthcare and monitoring, quick response time and latency minimization are required. However, the receiving nodes have a very fluctuating behavior in resource consumption especially if they are mobile. Fog, a localized cloud placed close to the underlying IoTs, provides the means to cater such issues by analyzing the behavior of the nodes and estimating resources accordingly. Similarly, Service Level Agreement (SLA) management and meeting the Quality of Service (QoS) requirements also become issues. In this paper, we devise a methodology, referred to as MEdia FOg Resource Estimation (MeFoRE), to provide resource estimation on the basis of service give-up ratio, also called Relinquish Rate (RR), and enhance QoS on the basis of previous Quality of Experience (QoE) and Net Promoter Score (NPS) records. The algorithms are implemented using CloudSim and applied on real IoT traces on the basis of Amazon EC2 resource pricing.
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- Authors
- Aazam, M., St-Hilaire, M., Lung, C.-H., & Lambadaris, I.
- Affiliations
- Carleton University (CA)
- Venue
- 2016 23rd International Conference on Telecommunications (ICT)
- Publisher
- IEEE
- Published
- 2016-05
- Pages
- 1-5
- OpenAlex
- W2473031807
- Cited by
- 96
- References
- 15
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 5 · 2022: 15 · 2021: 9 · 2020: 19 · 2019: 16 · 2018: 16 · 2017: 9 · 2016: 1
- FWCI
- 11.96
- Type
- conference paper
- Language
- en
- Open access
- closed
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Keywords
- fog computing, Internet of Things, resource estimation, quality of experience, quality of service, Net Promoter Score, service level agreements, vehicular ad hoc networks, remote patient monitoring, latency reduction
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