CICI: UCSS: Trusted Resource Allocation in Volunteer Edge-Cloud Computing Workflows

The unprecedented growth in networked smart edge devices (e.g., scientific instruments, edge servers, sensors) and related data sources has caused a data deluge in scientific application communities. The data processing is increasingly relying on machine learning algorithms and cloud platforms to cope with the heterogeneity, scale, and velocity of the data.

At the same time, there is an abundance of low-cost computation resources that can be used for “volunteer edge-cloud computing” (VEC), where collaborators in a community with various backgrounds contribute their resources to form a distributed infrastructure to execute scientific workflows. The VEC paradigm has the potential to benefit many scientific workflow communities in diverse disciplines (e.g., geography, neuroscience, manufacturing, agriculture).

This CICI project investigates the barriers for wider adoption of VEC caused due to lack of trust amongst the collaborating peers in terms of expected performance, and security of the VEC nodes, as well as workflow policies.

This project’s goal is to develop a VECTrust architecture and a related framework for support of trusted resource allocation in VEC environments for scientific data-intensive workflows. Driven by application community requirements for VEC in the KBCommons science gateway for multi-omics data integration, a threat model is being developed to inform the security of the resource allocation options for the collaborating peers.

In addition, a trust model is being developed that uses a two-stage probabilistic model to define trustworthiness of VEC cluster resources using metrics relevant to workflow execution factors that include: performance, agility, cost and security. Through usability studies, a prescriptive algorithm is being investigated to ensure that domain scientists who may lack the knowledge, background or resources to secure workflows can easily and seamlessly adopt VEC clusters.

Project outreach activities are focused on creation and dissemination of open-source and collaborative trust-enabling VEC resource orchestration tools, datasets and educational materials to train next-generation talent.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.