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A Time Synchronization Protocol for TDMA Based Wireless Sensor Networks
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์ ๊ธฐ๊ณตํ๋ถ, 2013. 8. ์ด์ ์ฐ.There has been much interest in wireless sensor networks recently, due to their diverse range of possible applications. Although there have been much research in MAC layer protocols for wireless sensor networks, these works are mainly focussed on the power savings and efficiencies of the protocols. For sensor networks which are in-situ and do not require much flexibility, such as a battery management system, energy is not always the most important factor, but rather reliability and scalability (where sensing periods are known). As such, a traditional TDMA protocol can be considered as a good option.
Time synchronization in wireless sensor networks have also been considered by many academics, but work related to time synchronization in TDMA networks have been much less popular. In this thesis, a time synchronization protocol for TDMA based wireless sensor networks is proposed, Propagating Chain Time Synchronization.
Propagating Chain Time Synchronization is a novel protocol for synchronizing TDMA based networks. The scheme achieves improved synchronization errors compared to traditional beacon synchronization methods, through skew correction estimated from chained two-way message exchanges, which employ piggybacking and overhearing.1 Introduction 1
1.1 Wireless Sensor Networks 1
1.1.1 Challenges in Designing Wireless Sensor Networks 2
1.2 Thesis Motivation 7
1.2.1 Wireless Sensor Networks in Battery Management Systems 7
2 Time Synchronization 10
2.1 Overview 10
2.2 Models of Clock Synchronization 11
2.2.1 Typical Synchronization Errors 13
2.3 Related Work 14
2.3.1 Sender-Receiver Synchronization 14
2.3.2 Receiver-Receiver Synchronization 16
2.3.3 Receiver-Only Synchronization 17
2.3.4 Clock Skew Estimation and Correction 18
2.3.5 Clock Synchronization in TDMA Based Networks 19
3 Propagating Chain Time Synchronization for TDMA Based Wireless Sensor Networks 21
3.1 Overview 21
3.2 System Model 21
3.2.1 Basic Assumptions 22
3.2.2 Topology 22
3.2.3 Chained Synchronization 23
3.2.4 Overhearing and Piggybacking 24
3.2.5 Propagating Skew Correction 28
4 Theoretical Error Analysis 31
4.1 System Models 31
4.2 Node Clock Modelling 32
4.3 TSF 34
4.4 Chained Synchronization 36
4.5 Two-Way Message Exchange Synchronization Error 38
5 Simulation 42
5.1 Simulation Parameters 42
5.2 Simulation Results 46
6 Conclusion 52
Bibliography 54Maste
Modelling Clock Synchronization in the Chess gMAC WSN Protocol
We present a detailled timed automata model of the clock synchronization
algorithm that is currently being used in a wireless sensor network (WSN) that
has been developed by the Dutch company Chess. Using the Uppaal model checker,
we establish that in certain cases a static, fully synchronized network may
eventually become unsynchronized if the current algorithm is used, even in a
setting with infinitesimal clock drifts
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
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