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 EngineeringThe 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-motesProvides user interaction mediumCan localize cooperative objects

Room occupancy networkElevator 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 ManagerIndependent decoupled networksSense, communicate physical phenomenaNeed not share state with other fabrics

APIs Communicate via standardized APIs

Client

Applications that access fabrics via servicesGranted 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