STETS: A novel energy-efficient time synchronization scheme based on embedded networking devices

Qiu, Tie; Lin, Chi; Guo, Weidong; Zhang, Yushuang

doi:10.1016/j.micpro.2015.07.006

Cited by 33 publications

(13 citation statements)

References 34 publications

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“…The flooding provides an easy way to achieve a synchronized network, regardless of the messaging scheme utilized to exchange the time information. The Tiny-Sync and Mini-Sync [ 98 ], the Lightweight Time Synchronization (LTS) [ 97 ], and the Timing-sync Protocol for Sensor Networks (TPSN) [ 82 ] use two-way message exchanges; the Spanning Tree-based Energy-efficient Time Synchronization (STETS) [ 99 ], its improved version R-Sync [ 37 ] and self-recovering version Self-Recoverable Time Synchronization (SRTS) [ 100 ] use receiver-only scheme; and the Flooding Time Synchronization Protocol (FTSP) [ 56 ], which is the de-facto synchronization protocol in WSN literature, uses one-way message dissemination.…”

Section: Time Synchronization Messagingmentioning

confidence: 99%

“…One way to implement this idea is to use the receiver-only messaging scheme, where the high-end nodes perform two-way time information exchanges, while the low-end nodes overhear these packets. The Group-wise Pair selection Algorithm (GMA) is a multi-hop scheme presented by Noh et al [ 104 ] and STETS [ 99 ] enable such deployments, but suffer from isolated nodes and sensitivity to group leaders problems. A solution to the first problem is provided in R-Sync [ 37 ], and a solution to the second is provided in SRTS [ 100 ].…”

Section: Time Synchronization Messagingmentioning

confidence: 99%

See 1 more Smart Citation

Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols

Yi̇ği̇tler

Badihi

Jäntti

2020

Sensors

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Internet of Things (IoT) is expected to change the everyday life of its users by enabling data exchanges among pervasive things through the Internet. Such a broad aim, however, puts prohibitive constraints on applications demanding time-synchronized operation for the chronological ordering of information or synchronous execution of some tasks, since in general the networks are formed by entities of widely varying resources. On one hand, the existing contemporary solutions for time synchronization, such as Network Time Protocol, do not easily tailor to resource-constrained devices, and on the other, the available solutions for constrained systems do not extend well to heterogeneous deployments. In this article, the time synchronization problems for IoT deployments for applications requiring a coherent notion of time are studied. Detailed derivations of the clock model and various clock relation models are provided. The clock synchronization methods are also presented for different models, and their expected performance are derived and illustrated. A survey of time synchronization protocols is provided to aid the IoT practitioners to select appropriate components for a deployment. The clock discipline algorithms are presented in a tutorial format, while the time synchronization methods are summarized as a survey. Therefore, this paper is a holistic overview of the available time synchronization methods for IoT deployments.

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Section: Time Synchronization Messagingmentioning

confidence: 99%

Section: Time Synchronization Messagingmentioning

confidence: 99%

Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols

Yi̇ği̇tler

Badihi

Jäntti

2020

Sensors

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“…Variable max child weight index is the index of max child weight in array child[]. At first, the sink node needs to clear array child[] (Line 1), then it sends a P T REELECT SIN K packet to all the child nodes for Algorithm 5 Network for the child nodes 1: clear array child[] 2: send P T REELECT SIN K to the child nodes 3: start a timer 4: if a node receives P T REELECT SIN K then 5: ava sink num ← 0 and clears optional sink[]; 6: broadcast P T SIN K SEARCH 7: calculate the weights of sink nodes; 8: send the biggest weight is to the sink node 9: end if 10: the sink node selects the maximum weight from child[] 11: send P T REJOIN REQU EST to child[max child weight index] 12: if a child node receives P T REJOIN REQU EST then 13: is net node ← f alse 14: execute algorithm 2 15: if is net node = true then 16: add the old sink node to its child node table 17: send P T REJOIN OK to the old sink node 18: else 19: is net node ← true 20: sent P T REJOIN F AILED to the old sink node 21: end if 22: end if 23: if sink node receives P T REJOIN OK then 24: delete child[max child weight index] 25: is net node ← true 26: return 27: else if sink node receives P T REJOIN F AILED then 28: i ← 0, max child weight ← 0 go to Line 12; 47: end if reelecting sink node (Line 2). At the same time, it starts a timer (Line 3).…”

Section: End If 21: End Ifmentioning

confidence: 99%

“…The memory, energy and ability of computing are limited by network nodes [8], [9]. In order to maximize lifetime, many researchers [10] apply themselves to control network topology [11], build better data transmission route and balance energy consumption of nodes [12], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Tree-Based Self-Organizing Protocol for Internet of Things

et al. 2016

Self Cite

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There are a lot of researches on self-organizing network at present. However, due to the characteristics of topological change of the Internet of Things, node resource constraints and random distribution and so on. Most of the existing self-organizing network are not applicable. This paper is aimed at the characteristics of the Internet of Things, and draws lessons from small world model, energy multi-path routing and hybrid routing algorithm. On the basis of GEAR protocol, a model of high efficient self-organizing network for large scale aware node is proposed: A multi-path hybrid routing model based on small world model, referred as SMH (Small World Multi-Path Hybrid Routing) model. In this paper, the model is implemented and an improved protocol based on GEAR is obtained, which is SMH-GEAR protocol. And SMH-GEAR protocol and GEAR protocol are compared and analyzed with simulation by using NS-2 network simulation platform. The result of the experiment shows SMH-GEAR protocol is better than GEAR protocol in terms of overall performance.

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“…Over the past decades, we have witnessed the development of automotive electronics [1] and IoTs [2]. Nowadays, modern vehicles have already equipped with dozens or even hundreds of sensors onboard, like oxygen sensor, speedometer, temperature sensor and etc [3].…”

Section: Introductionmentioning

confidence: 99%

Cost-efficient traffic-aware data collection protocol in VANET

Zhang

2017

Ad Hoc Networks

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Data from running vehicles are invaluable to numerous ITS and urban computing applications. This paper studies the issue of collecting data from multiple vehicles to a roadside base station via vehicle-to-vehicle and vehicle-toinfrastructure communications. Existing data collection approaches in VANET have mainly focused on the network problems, such as packet loss, network clustering or data aggregation, but the impact of real-time traffic condition is barely considered. In this paper, we investigate the data collection problem in VANETs under rapid evolving traffic conditions. Our approach can adaptively choose to carry or forward the data packet, based on current traffic information. The objective is to minimize the network communication overhead while satisfying the data collection time constraint. We formulate the data collection problem as a scheduling optimization problem and prove it is NP-complete. An optimal dynamic programming solution and a genetic algorithm based heuristic solution are developed to solve the problem under different application scenarios. Extensive evaluations validate that our proposed solution outperforms some existing ones in terms of effectiveness and efficiency.

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STETS: A novel energy-efficient time synchronization scheme based on embedded networking devices

Cited by 33 publications

References 34 publications

Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols

Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols

An Efficient Tree-Based Self-Organizing Protocol for Internet of Things

Cost-efficient traffic-aware data collection protocol in VANET

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