1. 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), where  Light sensors report the light readings periodically to the Base Station (BS)  LED array actors are turned on based on the light readings  Base station sends a command to cameras to turn on the camera after LED arrays are on  Cameras 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 Sensor Stack without Cross-layering support: Sensor Stack with Cross-layering support: 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 ke b, where k is the length of the bit-stream and e b 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 2e b irrespective of the amount of information being sent EbT CtS Distributed Source Coding of Correlated Data from Image Sensors Motivation: Correlation Model: X 1, X 2 : I.I.D binary sequence ; Prob [ X i =0 ] = Prob [ X i =1 ] = 1/2. Prob [ X 1 ≠ X 2 | X 1 ] = p X1X1 X2X2 BSC p ( X 2,P X 2 ) k (1-R)n Decoder P'X2P'X2 PX2PX2 X2X2 Channel X1X1 Encoder X2X2 Correlation Channel Wireless n Systematic Channel Rate R Rn X2X2 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 X 2 :  With the knowledge that X 1 is present at the decoder  Without communicating with X 1 X 1 and X 2 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%