Abstract
Modern environmental monitoring and decision support systems are based on complex IT infrastructures comprising multiple hardware and software subsystems that need to provide a variety of Quality of Service (QoS) guarantees required for urgent computing services, essential in emergency situations. Such IT infrastructures need to be managed in order to maintain the quality of service, which–especially when operating in the urgent mode–involves optimization of multiple, often conflicting, objectives and making trade-offs between them. Existing approaches do not solve this issue optimally because they focus on delivering quality of service within individual subsystems in isolation. We propose a holistic approach to system management which takes into account knowledge about the system as a whole—in particular the interplay of conflicting objectives and configuration options across all subsystems. We argue that such an approach produces a better configuration of the involved subsystems, improving the resolution of trade-offs between cost, energy and performance objectives, leading to their better overall fulfillment in comparison with the non-holistic approach in which individual subsystems are managed in isolation. We validate our approach using a prototype implementation of the holistic optimization algorithm—the Holistic Computing Controller, and applying it to a smart levee monitoring and flood decision support system.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.