1 Prashant Shenoy Lab Description Seminar 2009From Cloud Computing to Sensor Networks: Distributed Computing Research at LASS Prashant Shenoy Lab Description Seminar 2009
2 Internet-enabled ApplicationsProliferation of web-enabled and networked applications Increased use in consumer and business worlds Brokerage/ banking online game online store A wide variety of Internet applications have become popular during the last decade or so. Ex of such applications include online auction sites, gaming sites, online retail stores and so on. We have come to increasingly rely on such applications for conducting both our personal and business affairs. These applications typically provide a web-based interface to their clients. The focus of my research is on Internet server applications. -- Web based interface -- abrupt Growing significance in personal, business affairs Focus: networked server applications 2
3 Data Centers Networked apps run on data centers Data CentersLarge clusters of servers Networked storage devices Allocate resources to meet application needs Modern data centers are increasingly virtualized 3
4 Cloud Computing Hosted applications Examples AdvantagesRent 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 provisioningAdaptive monitoring in data centers Modeling data center applications and systems Fault-tolerant cloud applications
6 Green Computing Green computingGreening 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 Sensor Networks as a Distributed SystemStructure/Machinery Monitoring Hierarchical wireless networks composed of low power sensors. Enables densely and closely monitoring of phenomena. Tracking Surveillance
8 Emerging Rich Sensor NetworksRadar Sensor Network Camera Sensor Network Many of the talks you have heard at this conference have been about small or portable sensors. Here I will talk about another end of the sensor network spectrum—rich sensor networks. The technology trends towards lower power, and more compact electronics has also benefited traditionally large, high-end sensors. For example, previously large weather radars that weighs several tons and consume thousands of watts of power can be replaced by portable short range radars that weigh tens of pounds and run on solar panels. Another example is camera sensors, for example in traffic monitoring, and numerous low-power camera sensor nodes are already in wide use. The challenges in such rich sensor networks may not be the same as on mote-class devices. In some cases, energy may not be the biggest concern since the nodes are tethered. Rich sensors like radars and cameras are also data-rich, so bandwidth can be a critical concern. Another important issue is that these networks are often deployed with many types of end users and applications in mind, as opposed to being optimized for single, specific application Richer energy Tethered power High data rate Many MB/second Diverse users/applications needs E.g. First responders, Commuters, Insurance, for traffic monitoring
9 Ongoing Research 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
10 Initial Deployment site: 12 mile stretch of Fort River, AmherstRiver 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 studentApproach to advising Mailing list: 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)