Sharing Pandemic Vaccination Certificates through Blockchain: Case Study and Performance Evaluation

During 2021, different worldwide initiatives have been established for the development of digital vaccination certificates to alleviate the restrictions associated with the COVID-19 pandemic to vaccinated individuals. Although diverse technologies can be considered for the deployment of such certificates, the use of blockchain has been suggested as a promising approach due to its decentralization and transparency features. However, the proposed solutions often lack realistic experimental evaluation that could help to determine possible practical challenges for the deployment of a blockchain platform for this purpose. To fill this gap, this work introduces a scalable, blockchain-based platform for the secure sharing of COVID-19 or other disease vaccination certificates. As an indicative use case, we emulate a large-scale deployment by considering the countries of the European Union. The platform is evaluated through extensive experiments measuring computing resource usage, network response time, and bandwidth. Based on the results, the proposed scheme shows satisfactory performance across all major evaluation criteria, suggesting that it can set the pace for real implementations. Vis-à-vis the related work, the proposed platform is novel, especially through the prism of a large-scale, full-fledged implementation and its assessment.

Opportunistic Edge Computing Architecture for Smart Healthcare Systems

Some of the largest global industries that is driving smart city environments are anywhere and anytime health monitoring applications. Smart healthcare systems need to be more preventive and responsive as they deal with sensitive data. Even though cloud computing provides solutions to the smart healthcare applications, the major challenge imposed on cloud computing is how could the centralized traditional cloud computing handle voluminous data. The existing models may encounter problems related to network resource utilization, overheads in network response time, and communication latency. As a solution to these problems, edge-oriented computing has emerged as a new computing paradigm through localized computing. Edge computing expands the compute, storage, and networking capabilities to the edge of the network which will respond to the above-mentioned issues. Based on cloud computing and edge computing, in this chapter an opportunistic edge computing architecture is introduced for smart provisioning of healthcare data.

Engineering a Functional small RNA Negative Autoregulation Network with Model-guided Design

RNA regulators are powerful components of the synthetic biology toolbox. Here, we expand the repertoire of synthetic gene networks built from these regulators by constructing a transcriptional negative autoregulation (NAR) network out of small RNAs (sRNAs). NAR network motifs are core motifs of natural genetic networks, and are known for reducing network response time and steady state signal noise. Here we use cell-free transcription-translation (TX-TL) reactions and a computational model to design and prototype sRNA NAR constructs. Using parameter sensitivity analysis, we design a simple set of experiments that allow us to accurately predict NAR function in TX-TL. We transfer successful network designs in vivo and show that our sRNA transcriptional network reduces both network response time and noise in steady-state gene expression. This work broadens our ability to construct increasingly sophisticated RNA genetic networks with predictable function.