Foggy: A Platform for Workload Orchestration in a Fog Computing Environment

In this paper we present Foggy, an architectural framework and software platform based on Open Source technologies. Foggy orchestrates application workload, negotiates resources and supports IoT operations for multi-tier, distributed, heterogeneous and decentralized Cloud Computing systems. Foggy is tailored for emerging domains such as 5G Networks and IoT, which demand resources and services to be distributed and located close to data sources and users following the Fog Computing paradigm. Foggy provides a platform for infrastructure owners and tenants (i.e., application providers) offering functionality of negotiation, scheduling and workload placement taking into account traditional requirements (e.g. based on RAM, CPU, disk) and non-traditional ones (e.g. based on networking) as well as diversified constraints on location and access rights. Economics and pricing of resources can also be considered by the Foggy model in a near future. The ability of Foggy to find a trade-off between infrastructure owners' and tenants' needs, in terms of efficient and optimized use of the infrastructure while satisfying the application requirements, is demonstrated through three use cases in the video surveillance and vehicle tracking contexts.

[1]  Michael Abd-El-Malek,et al.  Omega: flexible, scalable schedulers for large compute clusters , 2013, EuroSys '13.

[2]  Mahadev Satyanarayanan,et al.  OpenFace: A general-purpose face recognition library with mobile applications , 2016 .

[3]  Antonio Pescapè,et al.  Integration of Cloud computing and Internet of Things: A survey , 2016, Future Gener. Comput. Syst..

[4]  Francesco De Pellegrini,et al.  Cloud4IoT: A Heterogeneous, Distributed and Autonomic Cloud Platform for the IoT , 2016, 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom).

[5]  Rajkumar Buyya,et al.  Mobility-Aware Application Scheduling in Fog Computing , 2017, IEEE Cloud Computing.

[6]  Rajiv Ranjan,et al.  Osmotic Flow: Osmotic Computing + IoT Workflow , 2017, IEEE Cloud Computing.

[7]  Mahadev Satyanarayanan,et al.  The Emergence of Edge Computing , 2017, Computer.

[8]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.