MetroSense Project: People-Centric Sensing at Scale Shane B. Eisenman †, Nicholas D. Lane ‡,...

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MetroSense Project: People-Centric Sensing at Scale Shane B. Eisenman , Nicholas D. Lane , Emiliano Miluzzo , Ronald A. Peterson , Gahng-Seop Ahn and Andrew T. Campbell Electrical Engineering, Columbia University Computer Science, Dartmouth College With support from ISTS, Intel and Nokia. Shane Eisenman is supported by the Army Research Office (ARO) under Award W911NF- 04-1-0311 More information on the MetroSense Project, including publications, technical reports, and source code from Mobile People-centric Applications Motivation Campus Area Sensor Network MetroSense Architecture Opportunistic Delegation Model TX range sensing range direct delegation indirect delegati on Data mule sensing “space” of interest Goal is to leverage mobility when direct sensing from SAP is not possible. Scenario: application requires sensed modality ß from “space” during [t1, t2] SAP delegates sensing responsibility ß for a given time to a mobile sensor (MS) in its radio range. The MS senses the target, if possible, and carries the result back to the SAP, if possible. Direct vs. Indirect delegation If MSs available to a SAP are not fit to be direct delegates, a SAP may authorize a MS to delegate to another MS on the SAPs behalf (indirect delegation). Examples: indirect tasking, virtual sensing range extension, indirect collection = “data muling” Design challenges Limited “rendezvous” time Sensor selection challenging MetroSense is a three-tiered physical architecture: Server Tier, Sensor Access Point (SAP) Tier and Sensor Tier MetroSense comprises three main software component sets: Common Components, Core Components and Resource Components Server Tier SAP Tier Sensor Tier Mobility gives rise to opportunistic sensor networking: opportunistic tasking, opportunistic sensing, and opportunistic collection. Looking forward 10-20 years we envision Internet scale sensing where the majority of the traffic on the network is sensor data and the majority of applications used every day by the general populace integrates sensing and actuation in some form. Sensing will be people-centric. We believe the gap between the state of the art and our future vision can be bridged through the development of a new wireless sensor edge for the Internet. To be truly impactful on the daily lives of lay people, new applications must by about people and the way they interact with their surroundings. A focus on people-centric sensing shifts design challenges: no centralized control, platform heterogeneity, batteries can be recharged. Mobility presents both challenges and unique opportunities. SAP implementation = Aruba AP-70 + Moteiv Tmote Invent Network symbiosis: we are deploying SAP on the back of existing WiFi APs to reduce the time and cost of system deployment. Each AP will continue to fulfill its normal role while MetroSense taps its spare resources. SkiScape Sensing BikeNet Sensing Dual focus: quantifying the cyclist experience and facilitating in situ and post facto information sharing between cyclists Dual focus: monitor ski resort trail conditions and collect and store skier speed and location statistics Opportunistic Operations – Illustrated opportunistic tasking opportunistic collection opportunistic sensing limited peering comms & ground-truth sensing
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Transcript of MetroSense Project: People-Centric Sensing at Scale Shane B. Eisenman †, Nicholas D. Lane ‡,...

Page 1: MetroSense Project: People-Centric Sensing at Scale Shane B. Eisenman †, Nicholas D. Lane ‡, Emiliano Miluzzo ‡, Ronald A. Peterson ‡, Gahng-Seop Ahn †

MetroSense Project: People-Centric Sensing at ScaleShane B. Eisenman†, Nicholas D. Lane‡, Emiliano Miluzzo‡, Ronald A. Peterson‡, Gahng-Seop Ahn† and Andrew T. Campbell‡

†Electrical Engineering, Columbia University ‡Computer Science, Dartmouth College

With support from ISTS, Intel and Nokia. Shane Eisenman is supported by the Army Research Office (ARO) under Award W911NF-04-1-0311More information on the MetroSense Project, including publications, technical reports, and source code from http://metrosense.cs.dartmouth.edu/.

Mobile People-centric ApplicationsMotivation Campus Area Sensor Network

MetroSense Architecture Opportunistic Delegation Model

TX range

sensing range

direct delegation

indirect delegation

Data mule

sensing “space” of interest

• Goal is to leverage mobility when direct sensing from SAP is not possible. Scenario: application requires sensed modality ß from “space” during [t1, t2]

• SAP delegates sensing responsibility ß for a given time to a mobile sensor (MS) in its radio range. The MS senses the target, if possible, and carries the result back to the SAP, if possible.

• Direct vs. Indirect delegation

• If MSs available to a SAP are not fit to be direct delegates, a SAP may authorize a MS to delegate to another MS on the SAPs behalf (indirect delegation).

• Examples: indirect tasking, virtual sensing range extension, indirect collection = “data muling”

• Design challenges• Limited “rendezvous” time • Sensor selection challenging

MetroSense is a three-tiered physical architecture: Server Tier, Sensor Access Point (SAP) Tier and Sensor TierMetroSense comprises three main software component sets: Common Components, Core Components and Resource Components

ServerTier

SAPTier

SensorTier

Mobility gives rise to opportunistic sensor networking: opportunistic tasking, opportunistic sensing, and opportunistic collection.

Looking forward 10-20 years we envision Internet scale sensing where the majority of the traffic on the network is sensor data and the majority of applications used every day by the general populace integrates sensing and actuation in some form. Sensing will be people-centric. We believe the gap between the state of the art and our future vision can be bridged through the development of a new wireless sensor edge for the Internet. To be truly impactful on the daily lives of lay people, new applications must by about people and the way they interact with their surroundings.

A focus on people-centric sensing shifts design challenges: no centralized control, platform heterogeneity, batteries can be recharged. Mobility presents both challenges and unique opportunities.

SAP implementation = Aruba AP-70 + Moteiv Tmote Invent

Network symbiosis: we are deploying SAP on the back of existing WiFi APs to reduce the time and cost of system deployment. Each AP will continue to fulfill its normal role while MetroSense taps its spare resources.

SkiScape Sensing

BikeNet Sensing

Dual focus: quantifying the cyclist experience and facilitating in situ and post facto information sharing between cyclists

Dual focus: monitor ski resort trail conditions and collect and store skier speed and location statistics

Opportunistic Operations – Illustrated

opportunistictasking

opportunisticcollection

opportunisticsensing

limitedpeering

comms & ground-truthsensing