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Cluster-based Network Time Synchronization for Resilience with Energy Efficiency

Nitin Shivaraman, Patrick Schuster, Saravanan Ramanathan, Arvind Easwaran, Sebastian Steinhorst

TL;DR

This paper tackles the challenge of fault-resilient time synchronization in resource-constrained IoT networks. It introduces C-sync, a clustering-based decentralized protocol that uses Local Centers as time sources and Byzantine-consensus within clusters to isolate faults, while significantly reducing communication and energy overhead compared to centralized or non-resilient schemes. The approach combines a five-state clustering process with a two-state consensus phase, achieving bounded synchronization error and scalable fault tolerance on Contiki-enabled hardware, with linear per-node complexity. Experimental results on a real testbed show that C-sync delivers comparable accuracy to GTSP but with markedly lower energy consumption across different network topologies, underscoring its practical value for resilient, energy-efficient IoT deployments.

Abstract

Time synchronization of devices in Internet-of-Things (IoT) networks is one of the challenging problems and a pre-requisite for the design of low-latency applications. Although many existing solutions have tried to address this problem, almost all solutions assume all the devices (nodes) in the network are faultless. Furthermore, these solutions exchange a large number of messages to achieve synchronization, leading to significant communication and energy overhead. To address these shortcomings, we propose C-sync, a clustering-based decentralized time synchronization protocol that provides resilience against several types of faults with energy-efficient communication. C-sync achieves scalability by introducing multiple reference nodes in the network that restrict the maximum number of hops any node can have to its time source. The protocol is designed with a modular structure on the Contiki platform to allow application transitions. We evaluate C-sync on a real testbed that comprises over 40 Tmote Sky hardware nodes distributed across different levels in a building and show through experiments the fault resilience, energy efficiency, and scalability of the protocol. C-sync detects and isolates faults to a cluster and recovers quickly. The evaluation makes a qualitative comparison with state-of-the-art protocols and a quantitative comparison with a class of decentralized protocols (derived from GTSP) that provide synchronization with no/limited fault-tolerance. Results also show a reduction of 56.12% and 75.75% in power consumption in the worst-case and best-case scenarios, respectively, compared to GTSP, while achieving similar accuracy.

Cluster-based Network Time Synchronization for Resilience with Energy Efficiency

TL;DR

This paper tackles the challenge of fault-resilient time synchronization in resource-constrained IoT networks. It introduces C-sync, a clustering-based decentralized protocol that uses Local Centers as time sources and Byzantine-consensus within clusters to isolate faults, while significantly reducing communication and energy overhead compared to centralized or non-resilient schemes. The approach combines a five-state clustering process with a two-state consensus phase, achieving bounded synchronization error and scalable fault tolerance on Contiki-enabled hardware, with linear per-node complexity. Experimental results on a real testbed show that C-sync delivers comparable accuracy to GTSP but with markedly lower energy consumption across different network topologies, underscoring its practical value for resilient, energy-efficient IoT deployments.

Abstract

Time synchronization of devices in Internet-of-Things (IoT) networks is one of the challenging problems and a pre-requisite for the design of low-latency applications. Although many existing solutions have tried to address this problem, almost all solutions assume all the devices (nodes) in the network are faultless. Furthermore, these solutions exchange a large number of messages to achieve synchronization, leading to significant communication and energy overhead. To address these shortcomings, we propose C-sync, a clustering-based decentralized time synchronization protocol that provides resilience against several types of faults with energy-efficient communication. C-sync achieves scalability by introducing multiple reference nodes in the network that restrict the maximum number of hops any node can have to its time source. The protocol is designed with a modular structure on the Contiki platform to allow application transitions. We evaluate C-sync on a real testbed that comprises over 40 Tmote Sky hardware nodes distributed across different levels in a building and show through experiments the fault resilience, energy efficiency, and scalability of the protocol. C-sync detects and isolates faults to a cluster and recovers quickly. The evaluation makes a qualitative comparison with state-of-the-art protocols and a quantitative comparison with a class of decentralized protocols (derived from GTSP) that provide synchronization with no/limited fault-tolerance. Results also show a reduction of 56.12% and 75.75% in power consumption in the worst-case and best-case scenarios, respectively, compared to GTSP, while achieving similar accuracy.
Paper Structure (29 sections, 2 theorems, 7 equations, 8 figures, 1 table, 2 algorithms)

This paper contains 29 sections, 2 theorems, 7 equations, 8 figures, 1 table, 2 algorithms.

Key Result

Lemma 1

The maximum synchronization error between any node to its nearest LC is a parametric value.

Figures (8)

  • Figure 1: Time Synchronization in C-sync using a clustered architecture for power efficiency and fault resilience.
  • Figure 2: The two phases of the C-sync protocol represented as a state machine.
  • Figure 3: Software architecture of Contiki OS integrated with C-sync.
  • Figure 4: Compensation of unstable high-frequency DCO using the stable low-frequency crystal oscillator.
  • Figure 5: The synchronization error of different nodes within a cluster having a faulty CH. The error remains within one logical time slot without any impact on network synchronization.
  • ...and 3 more figures

Theorems & Definitions (4)

  • Lemma 1
  • proof
  • Theorem 1
  • proof