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Serverless computing for cloud-based power grid emergency generation dispatch

ABSTRACT: Highlights • Event-driven serverless architecture requiring low cost and maintenance effort.• Data processing, storage, visualization and sharing on fault-tolerant cloud services.• Backup grid monitoring and control given access to secure Internet connection.• Cloud-hosted operation logging simplies auditing and responsibility tracking.• Cyber security mechanism that complies with CIP requirements for the power grid. Operating a modern power grid reliably in case of SCADA/EMS failure or amid difficult times like COVID-19 pandemic is a challenging task for grid operators. In [11], a PMU-based emergency generation dispatch scheme has been proposed to help the system operators with the supply and demand balancing; however, its realization highly relies on the control center infrastructure for computing and communication. This work, rather than using the on-premises server and dispatch communication system, proposes and implements a cloud-centric serverless architecture to ensure the operation continuity regardless of local infrastructure’s availability and accessibility. Through its prototype implementation and evaluation at ISO New England, the solution has demonstrated two major advantages. Firstly, the cloud infrastructure is independent and fault-tolerant, providing grid monitoring and control capability even when EMS loses the corresponding functionality or when operators need to work remotely away from the control center. Secondly, the overall design is event-driven using serverless cloud services in response to the SCADA/EMS failure event. Thanks to “serverless”, the burden of the server provisioning and maintenance can be avoided from the user side. The cost of using public cloud services for this solution is extremely low since it is architected and implemented based on the event-driven Function-as-a-Service (FaaS) model. This work also develops a comprehensive cyber security mechanism to comply with critical infrastructure requirements for the power grid, which can serve as an exemplary framework for other grid operators to secure their cloud services.

SUBMITTER: Zhang S

PROVIDER: S-EPMC7377758 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Project description:BackgroundDispatch services (DS's) form an integral part of emergency medical service (EMS) systems. The role of a dispatcher has also evolved into a crucial link in patient care delivery, particularly in dispatcher assisted cardio-pulmonary resuscitation (DACPR) during out-of-hospital cardiac arrest (OHCA). Yet, there has been a paucity of research into the emerging area of dispatch science in Asia. This paper compares the characteristics of DS's, and state of implementation of DACPR within the Pan-Asian Resuscitation Outcomes (PAROS) network.MethodsA cross-sectional descriptive survey addressing population characteristics, DS structures and levels of service, state of DACPR implementation (including protocols and quality improvement programs) among PAROS DS's.Results9 DS's responded, representing a total of 23 dispatch centres from 9 countries that serve over 80 million people. Most PAROS DS's operate a tiered dispatch response, have implemented medical oversight, and tend to be staffed by dispatchers with a predominantly medical background. Almost all PAROS DS's have begun tracking key EMS indicators. 77.8% (n = 7) of PAROS DS's have introduced DACPR. Of the DS's that have rolled out DACPR, 71.4% (n = 5) provided instructions in over one language. All DS's that implemented DACPR and provided feedback to dispatchers offered feedback on missed OHCA recognition. The majority of DS's (83.3%; n = 5) that offered DACPR and provided feedback to dispatchers also implemented corrective feedback, while 66.7% (n = 4) offered positive feedback. Compression-only CPR was the standard instruction for PAROS DS's. OHCA recognition sensitivity varied widely in PAROS DS's, ranging from 32.6% (95% CI: 29.9-35.5%) to 79.2% (95% CI: 72.9-84.4%). Median time to first compression ranged from 120 s to 220 s.ConclusionsWe found notable variations in characteristics and state of DACPR implementation between PAROS DS's. These findings will lay the groundwork for future DS and DACPR studies in the PAROS network.

Project description:High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology-a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr.

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Serverless computing for cloud-based power grid emergency generation dispatch

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