1. Prashant Shenoy Lab Description Seminar 2009
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
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 Centers
Large 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 Advantages
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. Sensor Networks as a Distributed System
Structure/Machinery
Monitoring
Hierarchical wireless networks composed of low power sensors.
Enables densely and closely monitoring of phenomena.
Tracking
Surveillance

8. Emerging Rich Sensor Networks
Radar 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, Amherst
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 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)