SocialEdge: Enabling trusted data processing workflow in smart communities

In typical commercial cloud and edge providers data collection and processing nodes might be owned by a single trusted entity. In contrast, in a voluntary infrastructure, ownership is distributed. In such a setup, while individuals contributing data might demand constraints on how their data is accessed and used, volunteers of compute resources might want assurance that their resources are used only for intended purposes. These significant differences motivate SocialEdge, an edge orchestration framework that 1) leverages online social network for bootstrapping and permissioned block chain for information assurance, 2) exploits recursive containerization for enabling secure data access, ensuring only intended workloads are run and enforcing fine-grained resource control, and 3) leverages components from Kubernetes to instantiate and manage an ephemeral cluster composed of volunteered resources. In this paper we describe the design and prototype implementation of SocialEdge and model the problem of orchestrating the on-demand data processing infrastructure under data access constraints as a variant of the multi-commodity flow problem. We propose and evaluate mixed integer programming and greedy heuristic approaches, and characterize recursive containerized environment experimentally using benchmarks.

Recommended citation: S. Aditya and R. Figueiredo, "SocialEdge: Enabling Trusted Data Processing Workflow in Smart Communities," 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Sydney, NSW, Australia, 2019, pp. 231-238, doi: 10.1109/CloudCom.2019.00042 https://ieeexplore.ieee.org/document/8968844