Rajnish Kumar, Mina Sartipi, Junsuk Shin, Ramanuja Vedantham, Yujie Zhu, Faramarz Fekri, Umakishore Ramachandran, Raghupathy Sivakumar

Application

Energy-Efficient Data Gathering in Sensor and Actor Networks: A High Bit-rate Image Sensing Application

Distributed source coding for image sensors Implement the algorithm on image sensors to evaluate energy saving benefits

Cross-layer support for image sensor placement Implement the IES architecture for the heterogeneous testbed for data fusion

Energy-efficient communication from light sensors to the BS

Implement CtS communication strategy from light sensors to the BS Mutual exclusion for LED array actors

Implement mutual exclusion on LED arrays to minimize energy consumption

Heterogeneous wireless sensor and actor network consisting of mica2 motes with light sensors, LED array actors, IPAQs with image sensors (cameras), whereLight sensors report the light readings periodically to the Base Station (BS)LED array actors are turned on based on the light readingsBase station sends a command to cameras to turn on the camera after LED arrays are onCameras send the image data to the BS

Minimize the total number of transmissions for the three phases for energy-efficient communication

Goal:

Sensor Stack with Cross-layering support for efficient Image sensor placement

Motivation:

Cross-layering can help in better camera placement for the application considered Without cross-layering, there is information overlap across layers Modules make inefficient decision

– DFuse application needs routing information to decide about role migration

RoleAssignment

Application,Data Fusion

FloodRouting

HSNRouting

MACTime Sync

Service

1

23 4 5

6

7

89

1. Fusion Requirement2. Data transmission requirement3. Neighborhood4. Data transmission requirement5. Data transmission requirement6. Neighborhood, Topology7. Time synchronization accuracyrequirement8. Data transmission requirement9. Role schedule, Duty cycleinformation

Sensor Stack without Cross-layering support:

Sensor Stack with Cross-layering support:

Application

Data Fusion Layer

Data Service Layer

Medium Access Layer

InformationExchange

Service

HelperServiceLayer

Radio

Application Logic\

In-stack fusion

Next-hop selection,Logical naming, Packet

scatter/gather

Medium Access, ErrorControl, Radio Control

Attribute-Value publish/

subscribe

Locali-zation,

Synchro-nizationService

Connection

(A) Stack Lay-out (B) Functionalities

Information Exchange Service:

1. Efficient use of limited memory

2. Simple interface for information sharing

3. Extensibility

4. Asynchronous delivery

5. Complex event notification

Energy-efficient communication strategy from Light sensors to Base Station

Motivation:

Need for energy-efficient communication from light sensors to sink Traditional communication strategy conveys information between the sender and the receiver using energy (EbT) only

Energy consumption is keb, where k is the length of the bit-stream and eb is energy per bit

Can we use time as an added dimension to convey information?

Communication through Silence (CtS):

A new communication strategy that conveys information using silent periods in tandem with small amount of energy The energy consumption for CtS is always 2eb irrespective of the amount of information being sent

97 !

START

1 0 0 0 0 1 1

97

97 !

1 0 0 0 0 1 1 1 0 0 0 0 1 1

97

STOP

1 2 ….

EbT

CtS

Distributed Source Coding of Correlated Datafrom Image Sensors

Motivation:

Correlation Model:X1, X2 : I.I.D binary sequence; Prob [ Xi =0 ] = Prob [ Xi=1 ] = 1/2.

Prob [ X1 ≠ X2 | X1 ] = pX1 X2BSC

p

(X2 ,PX2 )

k

(1-R)n

Decoder P'X2

PX2

X2

Channel

X1

Encoder

X2

CorrelationChannel

Wireless

n

Systematic Channel Rate R

RnX2

Non-uniform Channels

Modeling Distributed Source Coding with Parallel Channels:

Image sensors have correlated data. Distributed source coding can exploit correlation structure with low power algorithms

Distributed Source Coding:

Goal: Compressing X2:

With the knowledge that X1 is present at the decoder

Without communicating with X1

X1 and X2 have correlated information.

Use non-uniform LDPC code for channel coding.

Mutual Exclusion for Command Delivery from Base Station to LED Array Actors

Motivation:

Illustration of Mutual Exclusion:

Need for mutual exclusion in the acting ranges of the LED arrays Mutual Exclusion in WSANs: Execute a given command exactly once (or desired number of times) for any particular location irrespective of the distribution of actors Relaxed Definition: Choose a minimal set of actors such that the overlap between acting regions is minimal

Definitions for illustration Rm: Region covered by set of actors already included as part of actor cover ri and rj: New area covered by actor i and j respectively ni and nj: New overlap area for actor i and j respectively oi and oj : Old overlap area for actor i and j respectively

Conclusions and Future Work

Conclusions:

Future Work:

Energy savings for distributed source coding: 40% Energy savings for cross-layer support: 110% Energy savings for energy-efficient communication: 88% Energy savings for Mutual exclusion for LED array actors: 55% Overall expected energy savings: 88 + 55 + 110+ 40 = 293%