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From Cloud Computing to Sensor Networks: Distributed Computing Research at LASS

From Cloud Computing to Sensor Networks: Distributed Computing Research at LASS. Prashant Shenoy Lab Description Seminar 2009. Internet-enabled Applications. Proliferation of web-enabled and networked applications Increased use in consumer and business worlds. Brokerage/ banking.

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From Cloud Computing to Sensor Networks: Distributed Computing Research at LASS

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  1. From Cloud Computing to Sensor Networks: Distributed Computing Research at LASS Prashant Shenoy Lab Description Seminar 2009

  2. Internet-enabled Applications Proliferation of web-enabled and networked applications Increased use in consumer and business worlds Brokerage/ banking online game online store Growing significance in personal, business affairs Focus: networked server applications

  3. Data Centers Networked apps run on data centers Data Centers Large clusters of servers Networked storage devices Allocate resources to meet application needs Modern data centers are increasingly virtualized

  4. Cloud Computing • Hosted applications • Rent server resources (on-demand) • Run applications on rented servers • SLA: contract between server and app provider • Examples • Amazon Elastic computing cloud (EC2) • Google App Engine • Advantages • No need to maintain expensive infrastructure • Scale on demand

  5. Ongoing Research • Dynamic capacity provisioning • Adaptive monitoring in data centers • Modeling data center applications and systems • Fault-tolerant cloud applications

  6. Green Computing • Green computing • Greening of computing • Computing for greening • Use virtualization to design green data centers • Nano data centers powered using wind/solar • Sensors and modeling for greening of smart buildings

  7. Tracking Structure/Machinery Monitoring Sensor Networks as a Distributed System • Hierarchical wireless networks composed of low power sensors. • Enables densely and closely monitoring of phenomena. Surveillance

  8. Emerging Rich Sensor Networks Radar Sensor Network Camera Sensor Network • Richer energy • Tethered power • High data rate • Many MB/second • Diverse users/applications needs • E.g. First responders, Commuters, Insurance, for traffic monitoring

  9. Sensor Virtualization “rich” sensors will need to serve multiple users Virtualize the network to enable concurrent use Remote Management of sensor networks Remote deployments require remote management capability Management plane that separates control from data Energy harvesting in Solar-powered Networks Ongoing Research

  10. River Sensor Network • Application: • Monitor river dynamics (e.g: seasonal, flood events), ecological status, water quantity and quality information. • Sensors: • Water quality sensors, underwater cameras, etc. • Research: • Design of wide-area, remote wireless sensor network infrastructure. Initial Deployment site: 12 mile stretch of Fort River, Amherst Collaboration between faculty at Mt. Holyoke, NSM and Engineering at UMass, and Hampshire College.

  11. Research Methodology • Typical experience for research student • Approach to advising • Mailing list: lass@cs.umass.edu, sensors@cs.umass.edu • Lass Alumni • Combination of academia and industry • 5 in academia: Abhishek (Minnesota), Bhuvan (Penn State), Puru (IIT Bombay), Huan (Beihang U), Peter (Northeastern) • 2 in Industry: Vijay (Microsoft), Xiaotao (EMC)

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