# SNU INC Lab SNU INC Lab STEM: Topology Management for Energy Efficient Sensor Networks Curt Schurgers et. al. IEEE Aerospace Conference '02 Presented by.

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SNU INC Lab SNU INC Lab STEM: Topology Management for Energy Efficient Sensor Networks Curt Schurgers et. al. IEEE Aerospace Conference '02 Presented by Sangha Park

SNU INC Lab SNU INC Lab 2014-05-302 Content Introduction Sparse Topology Management Theoretical Analysis Performance Evaluation Combining STEM and GAF Conclusion

SNU INC Lab SNU INC Lab 2014-05-303 1. Introduction Sensor networks It is important to point that a node in the network has essentially two different tasks: Sensing its environment and processing the information. Forwarding traffic as an intermediate relay in the multi- hop path Significant energy savings are only obtainable by putting the node in sleep mode, essentially disconnecting it from the network and changing the topology

SNU INC Lab SNU INC Lab 2014-05-304 1. Introduction Topology Management The goal of topology management is to coordinated the sleep transitions of all nodes, while ensuring adequate network connectivity, such data can be forwarded efficiently to the data sink. Transfer state : Assume the network has data to forward. Monitoring state: No data needs to be forwarded to the data sink. Sensor networks often the vast majority of time in the monitoring state.

SNU INC Lab SNU INC Lab 2014-05-305 2. SPARSE TOPOLOGY MANAGEMENT Basic concept The sensor network is in the monitoring state the vast majority of its lifetime. STEM (Sparse Topology and Energy Management) Dual Frequency Wakeup plane : f1 Data plane : f2

SNU INC Lab SNU INC Lab 2014-05-306 3. THEORETICAL ANALYSIS Setup Latency(Ts) The statistics of Ts ( For T > T R x) P(Ts = B 1+2 ) = (T R x – B 1 ) / T P(Ts = kB 1+2 ) = B 1+2 / T (k = 2…K) P(Ts = (K+1)B 1+2 ) = (T - KB 1+2 - T R x + B 1 + B 1+2 )/ T The average setup latency per hop

SNU INC Lab SNU INC Lab 2014-05-307 3. THEORETICAL ANALYSIS Energy Savings. ignoring t data. the general relationship between setup latency and the relative energy gain

SNU INC Lab SNU INC Lab 2014-05-308 4. PERFORMANCE EVALUATION Simulation Setting R = 20m, L = 79.27m, N = 100 L beacon = L response = 144bits, B 1+2 = 150ms, T R x = 225ms Send 20 information packets of 1040bits to the data sink with an inter-packet spacing of 16 seconds t* = 320 seconds

SNU INC Lab SNU INC Lab 2014-05-309 4. PERFORMANCE EVALUATION Average Setup Latency The average setup latency per hop as a function of the wakeup period T. Eq(6) Average setup latency

SNU INC Lab SNU INC Lab 2014-05-3010 4. PERFORMANCE EVALUATION Relative Energy Savings Without STEM With STEM Gain = 1 - Relative energy savings versus The total observation interval t

SNU INC Lab SNU INC Lab 2014-05-3011 4. PERFORMANCE EVALUATION Setup Latency Tradeoff. Simulated energy – setup latency tradeoff

SNU INC Lab SNU INC Lab 2014-05-3012 5. COMBINING STEM AND GAF GAF Behavior Average numbers of node in a grid is M M = M / Θ Θ is the fraction of used grid Interaction of STEM and GAF. Theoretical energy – setup delay tradeoff

SNU INC Lab SNU INC Lab 2014-05-3013 6. CONCLUSION STEM ( topology management technique ) trades off power savings versus path setup latency in sensor networks. STEM integrates directly with other topology management schemes such GAF, and results in energy savings.

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