Energy-efficient Capture of Stochastic Events by Global- and Local-periodic Network Coverage

Energy-efficient Capture of Stochastic Events by Global- and Local-periodic Network Coverage

David K. Y. YauDavid K. Y. Yau

SensorNet: Plume Detection by In-situ Sensor Network

MotivationsMotivations

Unattended operation of many low-cost and small form factor sensors Dense static network Uncontrolled (random) placement Significant overlap in sensing regions

Possibility to duty-cycle sensors to save energy Eliminate redundant coverage Load balance between sensors for maximum network

lifetime

Unattended operation of many low-cost and small form factor sensors Dense static network Uncontrolled (random) placement Significant overlap in sensing regions

Possibility to duty-cycle sensors to save energy Eliminate redundant coverage Load balance between sensors for maximum network

lifetime

Motivations (cont’d)Motivations (cont’d)

Exploitation of real-world event properties and dynamics Events may stay and hence can be captured with delay

by (q,p)-periodic sensor When events stay, “quality of monitoring” may be

much higher than q/p high energy saving potential If p small enough, arbitrarily high fraction of events can be

captured no matter how small q/p (q,p) schedule can be optimized for maximum

event/information capture given event dynamics

Exploitation of real-world event properties and dynamics Events may stay and hence can be captured with delay

by (q,p)-periodic sensor When events stay, “quality of monitoring” may be

much higher than q/p high energy saving potential If p small enough, arbitrarily high fraction of events can be

captured no matter how small q/p (q,p) schedule can be optimized for maximum

event/information capture given event dynamics

BasicsBasics

Stochastic event arrivals/departures at each PoI Distribution of event staying times X Distribution of event absent times Y X and Y for same event may be dependent; but different events are

i.i.d.

Capture of events by sensor of range r (binary perfect-disk model) Anisotropic sensing is possible without affecting main conclusions

Many sensors placed according to Poisson Point Process of intensity ; may communicate within given wireless range

Stochastic event arrivals/departures at each PoI Distribution of event staying times X Distribution of event absent times Y X and Y for same event may be dependent; but different events are

i.i.d.

Capture of events by sensor of range r (binary perfect-disk model) Anisotropic sensing is possible without affecting main conclusions

Many sensors placed according to Poisson Point Process of intensity ; may communicate within given wireless range

Basics (cont’d)Basics (cont’d)

Sensors can be turned on/off (as a whole) Energy model: energy rate of k1 when on, k2 when off;

constant energy c to switch between on/off In principle, sensing/communication/computation can

be independently controlled Performance metrics (Step utility function)

Probability of instantaneous event capture Pin (over all events that could be captured only)

Probability of event capture (with or without delay) Pc Other types of events (utility functions) can be analyzed

Sensors can be turned on/off (as a whole) Energy model: energy rate of k1 when on, k2 when off;

constant energy c to switch between on/off In principle, sensing/communication/computation can

be independently controlled Performance metrics (Step utility function)

Probability of instantaneous event capture Pin (over all events that could be captured only)

Probability of event capture (with or without delay) Pc Other types of events (utility functions) can be analyzed

Energy Efficiency TechniquesEnergy Efficiency Techniques

(q,p)-periodic sensor schedule to exploit event dynamics (mainly, staying times)

Coordinated sleep between sensors to eliminate redundant coverage Sensor x is redundant if its sensing region is completely

covered by those of its active neighbors (conservative condition)

Sensors exchange their location, active schedule, remaining energy, etc (Hello protocol)

Safe to turn off x without affecting performance Different neighbors can go to sleep at different times;

permission to sleep renegotiated for energy balance

(q,p)-periodic sensor schedule to exploit event dynamics (mainly, staying times)

Coordinated sleep between sensors to eliminate redundant coverage Sensor x is redundant if its sensing region is completely

covered by those of its active neighbors (conservative condition)

Sensors exchange their location, active schedule, remaining energy, etc (Hello protocol)

Safe to turn off x without affecting performance Different neighbors can go to sleep at different times;

permission to sleep renegotiated for energy balance

Coordinated Sleep ProtocolCoordinated Sleep Protocol

Sensor roles Regular, supporting, redundant

Regular sensors identify their support sets regularly; a sensor ranks support set by Minimum residual energy (energy balance) Overlap of active time between itself and

support members (maximally productive sleep; in particular, a > 2 c / (k1 - k2))

Sensor roles Regular, supporting, redundant

Regular sensors identify their support sets regularly; a sensor ranks support set by Minimum residual energy (energy balance) Overlap of active time between itself and

support members (maximally productive sleep; in particular, a > 2 c / (k1 - k2))

Example Support SetExample Support Set

J

B

C

A

IH

G

D

EF

A’s support sets:

C, D, H, I

D, F, H, I

Hello message

Negotiation of Permission to SleepNegotiation of Permission to Sleep

J

B

C

A

IH

G

D

E

F

Request to sleep (RTS)

Clear to sleep (CTS)

Confirm (CNF)Supporting

Redundant

If two neighbors both want to go to sleep, they defer sending CTSby random delay (probabilistically longer if less remaining energy)

Syncrhonous and Asynchronous Periodic Network

Syncrhonous and Asynchronous Periodic Network

Synchronous periodic network All sensors start their (q,p) schedule at the same time (global-periodic) Network of sensors behave as one big periodic sensor Maximum coordinated sleep opportunities Leverage lightweight time synchronization protocols

Asynchronous periodic network Each sensor starts (q,p) schedule at an independent random point in

time (local-periodic) Spread-out on periods for better event capture Reduced coordinated sleep opportunities (less temporal redundancy) Zero coordination for periodic operation

Synchronous periodic network All sensors start their (q,p) schedule at the same time (global-periodic) Network of sensors behave as one big periodic sensor Maximum coordinated sleep opportunities Leverage lightweight time synchronization protocols

Asynchronous periodic network Each sensor starts (q,p) schedule at an independent random point in

time (local-periodic) Spread-out on periods for better event capture Reduced coordinated sleep opportunities (less temporal redundancy) Zero coordination for periodic operation

Coordinated Sleep OpportunitiesCoordinated Sleep Opportunities

Spatial redundancy Deployment density

Temporal redundancy Overlapping q active time for synchronous

periodic scheduling Opportunistic overlapping time for

asynchronous periodic scheduling Higher q higher overlap probability

Spatial redundancy Deployment density

Temporal redundancy Overlapping q active time for synchronous

periodic scheduling Opportunistic overlapping time for

asynchronous periodic scheduling Higher q higher overlap probability

Design PointsDesign Points

Periodic scheduling can be used together and orthogonally with coordinated sleep

Four design points Synchronous network with/without coordinated

sleep Asynchronous network with/without

coordinated sleep

Periodic scheduling can be used together and orthogonally with coordinated sleep

Four design points Synchronous network with/without coordinated

sleep Asynchronous network with/without

coordinated sleep

Energy-aware Optimization of Synchronous Network

Energy-aware Optimization of Synchronous Network

Required Pin specified by user

Pc of single sensor given by [CoNext 2008]

Required Pin specified by user

Pc of single sensor given by [CoNext 2008]

Pc as function of pPc as function of p

For Step utility,Pc monotonically decreasing in p(full information captured instantaneously no need to remain on)

Information Capture under Limited Energy

Information Capture under Limited Energy

When energy also considered, extremely fine q/p wastes energy to turn on/off the sensor frequently optimal event capture per unit of energy occurs at intermediate p

Energy model: k1 q + k2 (p - q) + 2c

Standard techniques apply for single dimension optimization of continuous function

Analysis of Capture DelayAnalysis of Capture Delay

Capture Delay for Exponential Staying times

Capture Delay for Exponential Staying times

Illustration of Capture DelayIllustration of Capture Delay

Event Capture of Asynchronous Network

Event Capture of Asynchronous Network

Events not captured by one sensor may be captured by another sensor All sensors within distance r of event are

“within range” Consideration for all in-range sensors needed By Poisson Point Process, probability of k such

sensors given by

Events not captured by one sensor may be captured by another sensor All sensors within distance r of event are

“within range” Consideration for all in-range sensors needed By Poisson Point Process, probability of k such

sensors given by

Non-capture Probability by One SensorNon-capture Probability by One Sensor

For Pin, simply 1 - q/p

For Pc, given by

Hence, we have …

For Pin, simply 1 - q/p

For Pc, given by

Hence, we have …

Probability of Instantaneous Capture (Asynchronous Network)

Probability of Instantaneous Capture (Asynchronous Network)

Probability of Capture(Asynchronous Network)

Probability of Capture(Asynchronous Network)

Optimization of Asynchronous NetworkOptimization of Asynchronous Network

User-specified Pin q/p (Theorem 3)

Pin increases linearly with q/p for synchronous network, but

Increase is exponential for asynchronous network

Optimization of p given q/p (Theorem 4)

User-specified Pin q/p (Theorem 3)

Pin increases linearly with q/p for synchronous network, but

Increase is exponential for asynchronous network

Optimization of p given q/p (Theorem 4)

Pin as Function of q/p (Asynchronous Network)

Pin as Function of q/p (Asynchronous Network)

Optimization of QE as Function of p (Asynchronous)

Optimization of QE as Function of p (Asynchronous)

Network SimulationsNetwork Simulations

Synchronous network With coordinated sleep (S-CSP) Without coordinated sleep (S-nc)

Asynchronous network With coordinated sleep (A-CSP) Without coordinated sleep (A-nc)

Role-alternating, Coverage-preserving protocol (RACP) [Hsin & Liu, IPSN 2004]

Synchronous network With coordinated sleep (S-CSP) Without coordinated sleep (S-nc)

Asynchronous network With coordinated sleep (A-CSP) Without coordinated sleep (A-nc)

Role-alternating, Coverage-preserving protocol (RACP) [Hsin & Liu, IPSN 2004]

A-nc vs. RACPA-nc vs. RACP

=4, required Pin = 0.99+ q/p=0.4

A-nc has 75% longer network lifetime, w/ little loss in Pin

A-nc requires no zero synchronization between sensors

A-nc achieves perfect load balancing (trivially)

A-CSP vs. RACPA-CSP vs. RACPA-CSP starts to die at about same time as A-nc, but …

Death is much more gradual

A-CSP has less good load balancing as RACP, because shifted on periods reduce chance for coordinated sleep

S-CSP vs. RACP (Probability of Instantaneous Capture)

S-CSP vs. RACP (Probability of Instantaneous Capture)

Pin = 0.4 q/p = 0.4

S-CSP achieves required Pin

S-CSP lasts twice as long as RACP tradeoff between performance and energy efficiency

S-CSP vs. RACP(Probability of Capture)

S-CSP vs. RACP(Probability of Capture)

S-CSP closes perfomance gap significantly in terms of event capture (0.8 vs. 0.4), because …

S-CSP is designed to take advantage of event staying time to work less hard and capture events at a delay

S-CSP vs. A-CSP(Probability of Capture)S-CSP vs. A-CSP

(Probability of Capture)S-CSP starts to die later because aligned on periods provide maximum sleep opportunities, but …

A-CSP achieves better event capture almost all the time, in spite of its degraded performance earlier

S-CSP vs. S-ncS-CSP vs. S-nc

Coordinated sleep prolongs network lifetime by about 1/3

Coordinated sleep achieves pretty good load balancing (complete network death happens rather quickly, cf. asynchronous network)

Summary of ResultsSummary of Results

Synchronous network provides performance/energy tradeoff by exploiting event staying time to capture events at a delay If user is willing to relax requirement on Pin (so we can use

smaller q/p) Performance gap closes significantly in terms of Pc

At low/moderate density, asynchronous network provides similar tradeoff, but tradeoff becomes more attractive Pin increases exponentially w/ q/p (cf. linear increase for

synchronous network)

Synchronous network provides performance/energy tradeoff by exploiting event staying time to capture events at a delay If user is willing to relax requirement on Pin (so we can use

smaller q/p) Performance gap closes significantly in terms of Pc

At low/moderate density, asynchronous network provides similar tradeoff, but tradeoff becomes more attractive Pin increases exponentially w/ q/p (cf. linear increase for

synchronous network)

Summary of Results (cont’d)Summary of Results (cont’d)

For high-density asynchronous network, tradeoff becomes mostly not necessary Loss of Pin is very small Gain in network lifetime is quite large

Asynchronous network provides better performance than synchronous network, but …

Asynchronous network provides less chance for coordinated sleep (load balancing also less effective)

For high-density asynchronous network, tradeoff becomes mostly not necessary Loss of Pin is very small Gain in network lifetime is quite large

Asynchronous network provides better performance than synchronous network, but …

Asynchronous network provides less chance for coordinated sleep (load balancing also less effective)

Related WorkRelated Work

Offline computation of subsets of k-cover sensors [Slijepcevic & Potkonjak 01] Not adaptive to dynamic networks

Online coordinated sleep protocols [Hsin & Liu 0; Yan, He & Stankovic 03; Tan & Georganas 02] Don’t consider event dynamics and optimization of periodic

networks

Network optimization for dynamic events [Bisnik, Abouzeid & Isler 06; Yau et al. 08] Sparse mobile sensor networks; no on-line sensor coordination

Offline computation of subsets of k-cover sensors [Slijepcevic & Potkonjak 01] Not adaptive to dynamic networks

Online coordinated sleep protocols [Hsin & Liu 0; Yan, He & Stankovic 03; Tan & Georganas 02] Don’t consider event dynamics and optimization of periodic

networks

Network optimization for dynamic events [Bisnik, Abouzeid & Isler 06; Yau et al. 08] Sparse mobile sensor networks; no on-line sensor coordination