Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/30722
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dc.contributor.authorBajalcaliev, Kostadinen_US
dc.contributor.authorMileski, Dimitaren_US
dc.contributor.authorGushev, Panoen_US
dc.contributor.authorGusev, Marjanen_US
dc.contributor.authorJakimovski, Boroen_US
dc.date.accessioned2024-06-20T07:41:44Z-
dc.date.available2024-06-20T07:41:44Z-
dc.date.issued2024-05-20-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/30722-
dc.description.abstractThis paper explores the transformation of electrocardiogram (ECG) monitoring from traditional offline to Real-Time analysis, enabled by high-speed mobile networks and affordable data plans. The transition to live monitoring presents challenges in data streaming and processing and the necessity of balancing immediacy with accuracy. We optimize two critical aspects of cloud architecture and scalability under the broader umbrella of cloud efficiency by evaluating the architecture’s components and their contribution to overall efficiency. The focus is on accommodating over a thousand concurrent patients streaming ECG data while maintaining cost-effectiveness, constrained by Near Real-Time Round Trip Time (RTT) of ≤ 3 seconds, achieving a throughput of ≥ 333.333 (msgs/s).en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectcloud efficiency, scalable, cost-effective, near real-time, ECGen_US
dc.titleOptimal Scalable Real-Time ECG Monitoring of Thousands of Concurrent Patientsen_US
dc.typeProceeding articleen_US
dc.relation.conference2024 47th MIPRO ICT and Electronics Convention (MIPRO)en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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