U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 ViSE: Virtualized Sensing Environment David Irwin, Mike Zink, Prashant Shenoy.

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U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 ViSE: Virtualized Sensing Environment David Irwin, Mike Zink, Prashant Shenoy Jim Kurose, and Deepak Ganesan GENI Spiral 1: Cluster D/Orca

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Background GENI and Sensor Networks: “…in 10 years, most computers…will be small sensors and actuators…to monitor health, traffic, weather, pollution, science experiments, surveillance, etc.” “It would seem odd if in 10 years we were still living with an Internet that did not take into account the needs of the majority of the computers then deployed.”

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Sensing and Actuators ac-tu-a-tor n. A mechanism that causes a device to be turned on or off, adjusted or moved. Nearly every device has actuator(s) E.g., CPUs, NICs, disks, sensors Essence of “deeply programmable” Actuation key for sensors: Determines data type, quality, quantity, etc. E.g., Sampling rate, Steering, Power Indirectly affects resource usage E.g., energy, bandwidth, storage, processing

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Broad Range of Sensor Networks radar/weather satellite observation (EODIS) auto traffic monitoring video surveillance vehicle tracking in sensor field habitat monitoring microclimate monitoring animal tracking network traffic monitoring underwater sensing Many differences, but also many commonalities CASA-NSF ERC

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 ViSE Testbed Overview Experiment with Actuation In addition to slivering CPU, memory, network, etc…. ….goal is to virtualize and sliver sensors Infrastructure 3 nodes - weatherproof, solar-powered Network - long-distance b/g Sensors - radar, Weather Station, Camera Backplane - cellular + embedded node

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Sparse, high-power radar  sensing gap: earth curvature effects prevent 72% of the troposphere below 1 km from being observed  coarse resolution 10,000 ft tornado wind earth surface snow 3.05 km RANGE (km) Horz. Scale: 1” = 50 km Vert. Scale: 1” -=- 2 km 5.4 km 1 km 2 km 4 km gap “There is insufficient knowledge about what is actually happening (or is likely to happen) at the Earth’s surface where people live.” [NRC 1998] Example: Weather Radars

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008  finer spatial resolution  beam focus: more energy into sensed volume  multiple looks: sense volume with most appropriate radars instead of this…. This: Benefits of Better Actuation

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Real-world CASA Example FLUS74 KOUN AWUOUN AREA WEATHER UPDATE NATIONAL WEATHER SERVICE NORMAN OK 742 PM CDT TUE APR WARNING DECISION UPDATE THIS WARNING DECISION UPDATE CONCERNS COMANCHE AND GRADY COUNTIES. MESOCYCLONE NEAR STERLING CONTINUES TO STRENGTHEN PER TWO RADAR VIEWS. CASA NETWORK ALSO SHOWING PRONOUNCED HOOK. STORM WILL ENCOUNTER WARM FRONT...WITH POSSIBLE ENHANCED LOW LEVEL SHEAR JUST EAST OF STERLING AND WEST OF RUSH SPRINGS. TORNADO WARNING IS POSSIBLE IF NOT LIKELY TO BE ISSUED AS STORM REACHES SOUTHWEST GRADY COUNTY. BURKE FLUS74 KOUN AWUOUN AREA WEATHER UPDATE NATIONAL WEATHER SERVICE NORMAN OK 742 PM CDT TUE APR WARNING DECISION UPDATE THIS WARNING DECISION UPDATE CONCERNS COMANCHE AND GRADY COUNTIES. MESOCYCLONE NEAR STERLING CONTINUES TO STRENGTHEN PER TWO RADAR VIEWS. CASA NETWORK ALSO SHOWING PRONOUNCED HOOK. STORM WILL ENCOUNTER WARM FRONT...WITH POSSIBLE ENHANCED LOW LEVEL SHEAR JUST EAST OF STERLING AND WEST OF RUSH SPRINGS. TORNADO WARNING IS POSSIBLE IF NOT LIKELY TO BE ISSUED AS STORM REACHES SOUTHWEST GRADY COUNTY. BURKE Note: not policy 4/10/07: first CASA data citation by NWS 5/8/07: circulations in testbed © KSWO TV 7:21pm 8:15 pm

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Orca: Cluster D Orca Provides: Basic GENI Structure/Interfaces Federation Basic VM and Slivering Mechanisms (Xen) Basic Scheduling Policies Management/Portal Infrastructure

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Orca: Cluster D Vise Focus: Physical Infrastructure Virtualized Actuators (Xen) Orca Integration New VM/Slivering Mechanisms Augmented Policies Publicly-available Testbed

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Integration Plans ViSE is a self-contained testbed Federate through Orca clearinghouse Some interaction with other Cluster D projects New slivering mechanisms/policies Integrate into Orca framework Experiment/portal services Slice controllers, Gush (Williams) Interfaces Experiment/Data Plane: virtual sensor interface Control Plane: GENI/Orca Operations & Management: GENI/Orca

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Timeline: Year 1 Demo - GEC4 (~March ‘09) Infrastructure deployed and operational Reflectivity Overlay using Google Maps Initial Orca Integration Web portal; request slices of Xen VMs Demo - GEC5 (~July ‘09) End-to-end slices across ViSE and compute cluster

U NIVERSITY OF M ASSACHUSETTS A MHERST Department of Computer Science 2008 Questions?