Weave: An architecture for tailoring urban sensing applications across multiple sensor fabrics V. Kulathumani, M. Sridharan, R. Ramnath, A. Arora Dept. of Computer Science and Engineering The Ohio State University

Motivating scenario: campus surveillance Track suspicious persons across campus – outdoors and indoors Outdoor surveillance by building mounted camera network  Monitors suspicious activity such as stopped car Indoor surveillance by motion triggered camera network  Should only monitor suspicious persons  Should be cued to operate by outdoor network

Motivating scenario: locality queries Variety of networks deployed to monitor local environment PeopleNet – Cellphones + Psi-motes Provides user interaction medium Can localize cooperative objects Room occupancy network Elevator status network Users ask locality specific queries; Where is Anish? Where is elevator?

Developing applications on already existing networks  Example: programming detector for “stopped car near entrances”  Users who write applications may be different from network designers Composing applications across independent, varied networks  Example: indoor network cued by outdoor network Rapid prototyping despite retrieving semantically different data  ‘Events’ of interest not known a priori or change quickly  Numerous networks, each sensing “different” data  Need unified way to retrieve Challenges

Contributions Architecture for urban sensing systems (Weave)  Individual networks viewed as programmable fabrics  Fabrics are independently managed  Fabrics need not share data  Fabrics conform to APIs Generic (Standard across fabrics) Domain specific Domain specific API for class of Search applications Illustrating use of Weave in composing  Campus surveillance application  Locality query applications

System components Sensing Fabric Fabric Manager Independent decoupled networks Sense, communicate physical phenomena Need not share state with other fabrics APIs Communicate via standardized APIs Client Applications that access fabrics via services Granted access via access manager Access Manager Directory Maintain directory of services offered Grants access rights for fabric Communication Network APIs Sensing Fabric Fabric Manager

System components Specific to Search applications Object types  Defined by predicates on physical phenomenon  Cooperative / non-cooperative  Attributes such as location and velocity Objects  Instances of object types Detector  Associated with each object type  Implemented by Fabric designer Client

Generic APIs in Weave Register FabricSession Register(Fabric F, Client C) Handles authentication FabricSession used in future references Contains expiration

Generic APIs in Weave Instantiate Boolean Instantiate(FabricSession, Detector, Shareable) Program client’s detector on fabric User should be aware of internal fabric APIs Made available to other Clients using Shareable Security o Run in isolation o Restrict hardware APIs

Vertical APIs for Search class Search SearchSession Search (FabricSession, ObjectType, Object, Locations, Parameters, Persistence, Duration, Periodicity, SearchListener) Operates in following modes o Find if object exists o Search temporally o Search spatially SearchListener is call back provided by Client

Locality specific querying Register with fabrics: CSE peopleNet and RPAC PeopleNet Where is Anish? Search CSE PeopleNet fabric and Recreation Center fabric FabricSession_cse Register(CSE_peopleNet, Client) FabricSession_rec Register(REC_peopleNet, Client)

Locality-specific querying Search PeopleNet CSE for Anish Result_cse Search (FabricSession_cse, ADVERTISED, ANISH, LOCATION_ALL, Parameters, ONCE, NOW, NULL, SearchListener) CSE building PeopleNet tracking

Campus surveillance scenario Register with fabrics: Outdoor camera, Indoor motion triggered camera FabricSession_m Register(OutdoorFabric, Client) FabricSession_ca Register(IndoorCamera, Client) Instantiate detector for stopped car near entrance on outdoor fabric Result_m Instantiate(FabricSession_m, stoppedCar, YES)

Campus surveillance scenario Search for StoppedCar object type Result_m Search (FabricSession_m, StoppedCar, NULL, LOCATIONALL, Parameters, PERSISTENT, 0, FOREVER, SearchListener) Calls SearchListener whenever new object is detected Stopped car detected This will cue indoor fabric

Campus surveillance scenario Outdoor fabric cues indoor camera using time and location LOCATIONS set to near entrance of building; ObjectType is ANY Duration - next 120 seconds; Periodicity - return results at 1 second interval Result_ca Search (FabricSession_ca, ANY, NULL, LOCATIONS, Parameters, PERSISTENT, 120, 1, SearchListener) Indoor camera takes picture

Related work Simplifying application design across heterogeneous networks  Senserweb Push based model  GENI All services in or architecture compatible with GENI user services We do not force isolation Viewing network as database of queryable object  TinyDB Queries on raw data We operate on semantic values exposed by fabric Focus on optimizing querying in a single network

Current work Implement low level services necessary for fabric model  Power management  Secure scheduling services Security  Jamming detection  Restricted set of hardware APIs accessible to client