Archive Number: 4.583
Status of Thesis: Open
Date of start: 2020-03-31
One of the biggest challenges for future trends and digital innovations like Internet of Things (IoT), embedded artificial intelligent, ubiquitous computing or 5G wireless networks is the management, storage and processing of huge amounts of data (Brogi and Forti 2017). Based on these innovations, millions of new devices, sensors and applications will be going online in the next decade. Measuring, monitoring, analyzing, processing and reacting are just a few examples of tasks that have to be done with the data flood that will be generated by them. To cope these challenges fog computing presents a new distributed architecture that helps to reduce latency and supports the storage, management and processing of huge data amounts (Bittencourt et al. 2015). In simple words it spans the continuum between the cloud and each device that measures, monitors, analyzes, processes or reacts based on data from the cloud ecosystem. The fog computing architecture allows the distribution of core functions closer to the point where the data is originated or consumed. These core functions are computing, storage, communication, controlling and decision making. But in addition to move these core functions closer to the devices that use them, these devices also can be integrated in serving these core functions. By using fog computing the consumer receives advantages like lower latency, improved location awareness, higher business agility, better support for mobility, lower transportation costs (Mahmood 2018).
Like in the context of cloud services, fog services can be made more trustworthy and secure through independent third-party certifications. To meet the requirements of certification for the turbulent environment of fog and cloud computing (new software and hardware, updates, etc.), continuous service certification (CSC) is required (Lins 2016). In contrast to traditional certifications’ manual processes, (semi-)automated data collection and analysis of cloud services’ certification-relevant data enable auditors and certification authorities to actively detect and investigate critical defects as they occur, ultimately increasing the reliability and trustworthiness of issued certifications. But: How should a CSC certification be presented to the consumer of fog services? Traditional approaches like web seals are not sufficient.
- Bittencourt LF, Lopes MM, Petri I, Rana OF Towards Virtual Machine Migration in Fog Computing. In: 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 4-6 Nov. 2015 2015. pp 1-8. doi:10.1109/3PGCIC.2015.85
- Brogi A, Forti S (2017) QoS-Aware Deployment of IoT Applications Through the Fog. IEEE Internet of Things Journal 4 (5):1185-1192. doi:10.1109/JIOT.2017.2701408
- Chen N, Yang Y, Zhang T, Zhou M, Luo X, Zao JK (2018) Fog as a Service Technology. IEEE Communications Magazine 56 (11):95-101. doi:10.1109/MCOM.2017.1700465
- Lins, S., Grochol, P., Schneider, S., & Sunyaev, A. (2016). Dynamic Certification of Cloud Services: Trust, but Verify! IEEE Security and Privacy, 14(2), 67–71.
- Lins, S., Schneider, S., Szefer, J., Ibraheem, S. & Sunyaev, A. (2019). Designing Monitoring Systems for Continuous Certification of Cloud Services: Deriving Meta-Requirements and Design Guidelines. In: Communications of the AIS, 44