Pods: Issues in the Design of Practical Ad-Hoc Sensor Networks Edoardo Biagioni Information and Computer Sciences University of Hawaii at Manoa

Outline The PODS wireless ad-hoc sensor network The PODS wireless ad-hoc sensor network Issues for sensor networks Issues for sensor networks  Scalability  Energy  Other issues, including collaborative event detection, position detection, mobility Closing comments Closing comments

Practical Sensor Networks Deployed in the real world Deployed in the real world Often in hostile environments Often in hostile environments Must function unattended for a long time Must function unattended for a long time Reliability: network must survive node failure(s) Reliability: network must survive node failure(s) Should be invisible or at least unobtrusive Should be invisible or at least unobtrusive Variety of tasks, including video, images, sound, IR, and event detection Variety of tasks, including video, images, sound, IR, and event detection

The PODS Wireless Sensor Network University of Hawaii University of Hawaii Information and Computer Sciences, Botany Information and Computer Sciences, Botany Study endangered plants, of which little is known Study endangered plants, of which little is known Example: Silene Hawaiiensis (at right) Example: Silene Hawaiiensis (at right)

Wireless Ad-Hoc Sensor Networks Use wireless data transmission (802.11/Wi-Fi, Bluetooth, other radio or infrared) to communicate data Use wireless data transmission (802.11/Wi-Fi, Bluetooth, other radio or infrared) to communicate data Each node generates data and also forwards data Each node generates data and also forwards data Networks self-configure to deliver data where needed, typically to one or more base stations Networks self-configure to deliver data where needed, typically to one or more base stations

PODS goals Study endangered plant species in situ Study endangered plant species in situ Do not disturb environment: camouflage equipment, limit human visits, use wireless ad- hoc networks Do not disturb environment: camouflage equipment, limit human visits, use wireless ad- hoc networks Collect high resolution images: phenology Collect high resolution images: phenology Weather sensing: low resolution, many sensors Weather sensing: low resolution, many sensors Near real-time data available on the web: Near real-time data available on the web:

High Resolution Images: Hawaiian Rainforest

PODS strategies Collect data at regular intervals: once/hour for images (daytime), every 10 minutes for weather Collect data at regular intervals: once/hour for images (daytime), every 10 minutes for weather Camouflage everything Camouflage everything Pods may “sleep” to conserve energy Pods may “sleep” to conserve energy Use all possible routes (i.e. multipath routing) to send data to the base station Use all possible routes (i.e. multipath routing) to send data to the base station Use a two-level hierarchy to decrease traffic Use a two-level hierarchy to decrease traffic Visualization turns data into information Visualization turns data into information

Wireless Sensor Network Issues Scaling Scaling Energy Consumption and Efficiency Energy Consumption and Efficiency Event Detection and Inter-Node cooperation Event Detection and Inter-Node cooperation Node Position Detection and Processing Node Position Detection and Processing Mobility: Fixed-Mobile, Self-Positioning Mobility: Fixed-Mobile, Self-Positioning

Scalability Today’s wireless ad-hoc sensor networks: at most a few hundred nodes Today’s wireless ad-hoc sensor networks: at most a few hundred nodes Tomorrow’s wireless ad-hoc sensor networks: thousands to millions of nodes Tomorrow’s wireless ad-hoc sensor networks: thousands to millions of nodes Current MANET (Mobile Ad-hoc NETwork) protocols broadcast requests to find routes, which is not scalable Current MANET (Mobile Ad-hoc NETwork) protocols broadcast requests to find routes, which is not scalable Many protocols only work with limited network diameter (maximum number of hops) Many protocols only work with limited network diameter (maximum number of hops) Data transfer does not scale [Gupta and Kumar] Data transfer does not scale [Gupta and Kumar]

Scalable Techniques Only broadcast where absolutely necessary, e.g. to establish routes to the base station(s) Only broadcast where absolutely necessary, e.g. to establish routes to the base station(s) Combine, compress, and reduce the data to be sent, e.g. by only sending when an event is detected Combine, compress, and reduce the data to be sent, e.g. by only sending when an event is detected Almost free: localized distributed computation Almost free: localized distributed computation Almost free (but not always possible): geographic routing Almost free (but not always possible): geographic routing Reduce congestion by running different networks in the same area, using multiple paths when possible [Chen] Reduce congestion by running different networks in the same area, using multiple paths when possible [Chen]

Scalable Hierarchical Network If two wireless ad-hoc networks use different frequencies If two wireless ad-hoc networks use different frequencies They can run in the same area without conflict They can run in the same area without conflict A backbone network of more powerful processors can take pictures, provide redundant communication A backbone network of more powerful processors can take pictures, provide redundant communication A network of low-power, simple processors can carry sensors, do simple in-network processing A network of low-power, simple processors can carry sensors, do simple in-network processing

Hierarchical Network

Energy Efficiency A low-power x86 system PC fed by a large lead- acid battery might run for two weeks A low-power x86 system PC fed by a large lead- acid battery might run for two weeks Can use Solar Panels, but expensive and hard to camouflage Can use Solar Panels, but expensive and hard to camouflage Energy might be the dominant cost and weight in a large sensor network: processor $10-$100, g, radio similar, batteries $100 (and processors are getting smaller and cheaper faster than batteries) Energy might be the dominant cost and weight in a large sensor network: processor $10-$100, g, radio similar, batteries $100 (and processors are getting smaller and cheaper faster than batteries)

Addressing Energy Efficiency Don’t use x86: Don’t use x86: ARM can be twice as efficient, PIC can be 1000 times more efficient ARM can be twice as efficient, PIC can be 1000 times more efficient Use sleep mode whenever possible – protocols must accomodate this Use sleep mode whenever possible – protocols must accomodate this Use directional antennas to gain greater range without additional power (power to go a distance d can increase as fast as d 4 ) Use directional antennas to gain greater range without additional power (power to go a distance d can increase as fast as d 4 )

Event Detection Detection done by a single-node, e.g. a change in weather value or a bird song: relatively simple Detection done by a single-node, e.g. a change in weather value or a bird song: relatively simple Distributed event detection requires knowing your neighbors and relative positions Distributed event detection requires knowing your neighbors and relative positions Event detection is a way of compressing data Event detection is a way of compressing data A posteriori event detection: reprogramming the network (after deployment) to try and detect events not known before deployment A posteriori event detection: reprogramming the network (after deployment) to try and detect events not known before deployment

Position Detection GPS is still expensive ($) and energy intensive (minutes to a first fix, with relatively large energy draw) GPS is still expensive ($) and energy intensive (minutes to a first fix, with relatively large energy draw) Equip a few nodes with GPS, let the others detect their position from radio range or signal strength: [Savarese, Robinson, Bulusu] Equip a few nodes with GPS, let the others detect their position from radio range or signal strength: [Savarese, Robinson, Bulusu] For manual deployments: record position when deploying, configure node to remember position For manual deployments: record position when deploying, configure node to remember position

Mobility: Fixed-Mobile Network Most of the network is fixed but a few units may move: e.g. researcher in the field, Berkeley UAV (unmanned aerial vehicle) data collection Most of the network is fixed but a few units may move: e.g. researcher in the field, Berkeley UAV (unmanned aerial vehicle) data collection MANET protocol would be wasteful: too much routing overhead MANET protocol would be wasteful: too much routing overhead On-demand routing is useful On-demand routing is useful Optimize for the many fixed nodes, not the few mobile nodes Optimize for the many fixed nodes, not the few mobile nodes

Mobile Sensor Nodes Air-dropped sensor networks: aircraft can return for multiple passes until the desired area is covered Air-dropped sensor networks: aircraft can return for multiple passes until the desired area is covered Mobile sensor nodes: how should they place themselves to both cover the area and communicate Mobile sensor nodes: how should they place themselves to both cover the area and communicate

References [Chen]: Multipath On-Demand Routing in Sensor Network Topologies [Chen]: Multipath On-Demand Routing in Sensor Network Topologies [Gupta and Kumar]: The Capacity of Wireless Networks [Gupta and Kumar]: The Capacity of Wireless Networks [Savarese]: Savarese, Rabaey, Beutel, Locationing in distributed ad-hoc wireless sensor networks [Savarese]: Savarese, Rabaey, Beutel, Locationing in distributed ad-hoc wireless sensor networks [Robinson]: Robinson and Marshall, An iterative approach to locating simple devices in an ad-hoc network [Robinson]: Robinson and Marshall, An iterative approach to locating simple devices in an ad-hoc network [Bulusu]: Bulusu, Heidemann, Estrin, Adaptive Beacon Placement [Bulusu]: Bulusu, Heidemann, Estrin, Adaptive Beacon Placement

Summary Main issues: scalability, energy efficiency Main issues: scalability, energy efficiency These issues affect the entire network design, including hardware design, protocol design, and what data that can be collected These issues affect the entire network design, including hardware design, protocol design, and what data that can be collected Other issues: event detection and node collaboration, determination of position, and mobility Other issues: event detection and node collaboration, determination of position, and mobility Pressing real-world problems really help! Pressing real-world problems really help!

Acknowledgements and URLs DARPA DARPA Kim Bridges and Brian Chee, University of Hawaii Kim Bridges and Brian Chee, University of Hawaii Students at the University of Hawaii: Shu Chen, Fengxian Fan, Michael Lurvey, Dan Morton, and many more Students at the University of Hawaii: Shu Chen, Fengxian Fan, Michael Lurvey, Dan Morton, and many more