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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%