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Adaptation of TDMA Parameters Based on Network Conditions

Analytical model optimizing TDMA parameters based on network conditions for energy efficiency and capacity improvement. Explores soft clustering, dropped packets, collisions, and proof of concept to enhance multi-hop time reservation. Overcomes simulation shortcomings for scalability and accuracy, providing insights for upper layer integration. Future work includes energy consumption optimization and PHY layer enhancements. Contact for more info.

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Adaptation of TDMA Parameters Based on Network Conditions

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  1. Adaptation of TDMA Parameters Based onNetwork Conditions Bora Karaoglu Tolga Numanoglu Wendi Heinzelman Department of Electrical and Computer Engineering University of Rochester, NY, USA

  2. Motivation Capacity Each tx occupies some part of the capacity

  3. Motivation Clustering approach: Divide into a number of chunks CHs use chunks Question? How many chunks? Work summarized in: Analytical model Optimization

  4. Agenda Protocol Overview: MH-TRACE Analytical Model Dropped Packets Collisions Proof of Concept Optimization of TDMA parameters

  5. Multi-Hop Time Reservation Using Adaptive Control for Energy Efficiency • TDMA • Soft clustering • CHs responsible for channel access only • Inter cluster communication is allowed Nf = 6

  6. Protocol Overview: MH-TRACE Factors limiting performance: Dropped Packets Real-time communication Limited Local Capacity Clustering Uneven distribution of Load Node Distributions Mobility Collisions Spatial Reuse Limited capacity Divisions

  7. Agenda Protocol Overview Analytical Model Dropped Packets Collisions Proof of Concept Optimization of TDMA parameters

  8. Analytical Model • Shortcomings of Simulations • Substantial Processing Power and Time • Repetitions for statistical accuracy • Valid only for the parameters set used • Scalability of Simulation Area • Edge Effects

  9. Dropped Packets Probability of Dropping a Packet Capacity per Cluster: Number of Data Slot per Frame Nonlinear relation between Load and Pdp Detailed probability distribution of Load is needed

  10. Dropped Packets Ps:Ratio of number of nodes in spurt to all nodes Voice Activity Detector NCH:Number of CHs each node can receive access from NCM:Number of nodes in the Cluster

  11. Dropped Packets Effect of Dropped Packets on Throughput Considering Rx Throughput Each node  all one hop neighbors

  12. Collisions Number of frames (Nf) vs. co-frame CH separation (dch) Labeling structure used in cellular systems Co-frame CH separation (dch) vs. number of collisions (fcoll) Correlation between Number of Nodes that can cause collisions Number of Collisions

  13. Agenda Soft Clustering Approaches Protocol Overview Analytical Model Dropped Packets Collisions Proof of Concept Optimization of TDMA parameters

  14. Proof of Concept Number of Packets Lost per Superframe (Nf = 6)

  15. Proof of Concept Number of Packets Lost per Superframe (Nf = 8)

  16. Agenda Protocol Overview Analytical Model Dropped Packets Collisions Proof of Concept Optimization of TDMA parameters

  17. Optimization of TDMA parameters • optimization with corresponding throughput figures with respect to the maximum realizable throughput Theoretically OptimizedNf

  18. Conclusions and Future Work The model Accurate Can be used in optimization of parameters Instantaneous results for changing Transmission Power Propagation Model PHY Specs: Freq, Threshold values … Asymptotic behavior Energy consumption Average node sleep/awake durations Average energy consumption per node Node and CH comparison wrt energy consumption Optimization of Nf wrt energy consumption We are going to add effects of upper layers into the model

  19. Thanks! Questions&Comments? Contact Info: Web : www.ece.rochester.edu/~karaoglu/ E-mail : karaoglu@ece.rochester.edu

  20. PHY Layer Abstraction • BW • Each tx occupies some part of the BW • Transmissions should overcome any noise present in the space of the BW • Divide • Spatial reuse

  21. PHY Layer Abstraction • TDMA: • Divide BW along time axis • Clustering: • Distribute parts of BW spatially among clusters

  22. Protocol Overview TDMA Soft Clustering CHs responsible for channel access only Inter cluster communication is allowed

  23. Analytical Analysis Shortcomings of Simulations Substantial Processing Power and Time Repetitions for statistical accuracy Valid only for the parameters set used Scalability of Simulation Area Edge Effects

  24. Analytical Analysis Factors limiting performance: Dropped Packets Real-time communication Limited Local Capacity Clustering Uneven distribution of Load Node Distributions Mobility Collisions Spatial Reuse Limited BW Divisions

  25. Dropped Packets Probability of Dropping a Packet Capacity per Cluster: Number of Data Slot per Frame Nonlinear relation between Load and Pdp Detailed probability distribution of Load is needed

  26. Dropped Packets ps:Probability of a node to be in spurt duration pA:Probability of a node to be in the communication range of a CH pd:Probability of a node that is in the communication range of a CH to choose that CH as its channel access provider Independent of Node Density  assumed constant

  27. Dropped Packets ps:Probability of a node to be in spurt duration pA:Probability of a node to be in the communication range of a CH pd:Probability of a node that is in the communication range of a CH to choose that CH as its channel access provider pdn = ps pA pd

  28. Collisions Number of frames (Nf) vs. co-frame CH separation(dch) Labeling structure used in cellular systems

  29. Collisions co-frame CH separation (dch) vs. number of collisions (fcoll)

  30. Collisions co-frame CH separation (dch) vs. number of collisions (fcoll) • NnCH: Expected number of nodes in the cluster • Nn: Total number of nodes • NC : Number of cluster in 2*rcomm range • V : Region bounded by the circle with radius 2*rcomm around origin • fcoll : number of packets lost per SF due to collision

  31. Agenda Soft Clustering Approaches Protocol Overview Analytical Analysis Dropped Packets Collisions Proof of Concept Optimization of TDMA parameters

  32. Proof of Concept Total Number of Packets Lost per Superframe

  33. Proof of Concept RX Throughput per Superframe

  34. Agenda Soft Clustering Approaches Protocol Overview Analytical Analysis Dropped Packets Collisions Proof of Concept Optimization of TDMA parameters

  35. Optimization of TDMA parameters

  36. Other Uses of the Model Instantaneous Analysis Results for changing Transmission Power Propagation Model PHY Specs: Freq, Threshold values … Asymptotic Behavior Energy Consumption Average node sleep/awake durations Average energy consumption per node Node and CH comparison wrt energy consumption Optimization of Nf wrt energy consumption

  37. Throughput Per Node

  38. Energy Consumption per Node

  39. Thanks! Questions&Comments?

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