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EDRP: Enhanced Dynamic Relay Point Protocol for Data Dissemination in Multi-hop Wireless IoT Networks

Jothi Prasanna Shanmuga Sundaram, Magzhan Gabidolla, Luis Fujarte, Shawn Duong, Jianlin Guo, Toshiaki Koike-Akino, Pu, Wang, Kieran Parsons, Philip V. Orlik, Takenori Sumi, Yukimasa Nagai, Miguel A. Carreira-Perpinan, Alberto E. Cerpa

TL;DR

EDRP is designed, which integrates two novel components: a Link-Quality Aware CSMA (LQ-CSMA) and a Machine Learning-based Block Size Selection (ML-BSS) algorithm for rateless codes, which demonstrates an average goodput improvement than the competing protocols.

Abstract

Emerging IoT applications are transitioning from battery-powered to grid-powered nodes. DRP, a contention-based data dissemination protocol, was developed for these applications. Traditional contention-based protocols resolve collisions through control packet exchanges, significantly reducing goodput. DRP mitigates this issue by employing a distributed delay timer mechanism that assigns transmission-start delays based on the average link quality between a sender and its children, prioritizing highly connected nodes for early transmission. However, our in-field experiments reveal that DRP is unable to accommodate real-world link quality fluctuations, leading to overlapping transmissions from multiple senders. This overlap triggers CSMA's random back-off delays, ultimately degrading the goodput performance. To address these shortcomings, we first conduct a theoretical analysis that characterizes the design requirements induced by real-world link quality fluctuations and DRP's passive acknowledgments. Guided by this analysis, we design EDRP, which integrates two novel components: (i) Link-Quality Aware CSMA (LQ-CSMA) and (ii) a Machine Learning-based Block Size Selection (ML-BSS) algorithm for rateless codes. LQ-CSMA dynamically restricts the back-off delay range based on real-time link quality estimates, ensuring that nodes with stronger connectivity experience shorter delays. ML-BSS algorithm predicts future link quality conditions and optimally adjusts the block size for rateless coding, reducing overhead and enhancing goodput. In-field evaluations of EDRP demonstrate an average goodput improvement of 39.43\% than the competing protocols.

EDRP: Enhanced Dynamic Relay Point Protocol for Data Dissemination in Multi-hop Wireless IoT Networks

TL;DR

EDRP is designed, which integrates two novel components: a Link-Quality Aware CSMA (LQ-CSMA) and a Machine Learning-based Block Size Selection (ML-BSS) algorithm for rateless codes, which demonstrates an average goodput improvement than the competing protocols.

Abstract

Emerging IoT applications are transitioning from battery-powered to grid-powered nodes. DRP, a contention-based data dissemination protocol, was developed for these applications. Traditional contention-based protocols resolve collisions through control packet exchanges, significantly reducing goodput. DRP mitigates this issue by employing a distributed delay timer mechanism that assigns transmission-start delays based on the average link quality between a sender and its children, prioritizing highly connected nodes for early transmission. However, our in-field experiments reveal that DRP is unable to accommodate real-world link quality fluctuations, leading to overlapping transmissions from multiple senders. This overlap triggers CSMA's random back-off delays, ultimately degrading the goodput performance. To address these shortcomings, we first conduct a theoretical analysis that characterizes the design requirements induced by real-world link quality fluctuations and DRP's passive acknowledgments. Guided by this analysis, we design EDRP, which integrates two novel components: (i) Link-Quality Aware CSMA (LQ-CSMA) and (ii) a Machine Learning-based Block Size Selection (ML-BSS) algorithm for rateless codes. LQ-CSMA dynamically restricts the back-off delay range based on real-time link quality estimates, ensuring that nodes with stronger connectivity experience shorter delays. ML-BSS algorithm predicts future link quality conditions and optimally adjusts the block size for rateless coding, reducing overhead and enhancing goodput. In-field evaluations of EDRP demonstrate an average goodput improvement of 39.43\% than the competing protocols.
Paper Structure (13 sections, 15 equations, 10 figures, 2 tables, 1 algorithm)

This paper contains 13 sections, 15 equations, 10 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Work
  3. Real-world performance analysis of DRP
  4. Insights into the performance of DRP
  5. Theoretical Analysis of Design Requirements
  6. Analysis of Inter-Sender Delay and Collision Probability
  7. Theoretical Analysis of Rateless Block Size Selection
  8. EDRP: Enhanced Dynamic Relay Point Protocol
  9. LQ-CSMA: Link-Quality-aware CSMA
  10. ML-based block size selection algorithm for rateless coding
  11. Real-world evaluations of EDRP
  12. Conclusion
  13. Discussion and Future Work

Figures (10)

  • Figure 1: Hardware setup
  • Figure 2: Topology setup
  • Figure 3: Goodput of DRP
  • Figure 4: Transmission events showing successful and collided transmissions of multiple senders in the same neighborhood
  • Figure 5: Technical analysis on the effect of inter sender delay on the collisions during disseminations.
  • ...and 5 more figures