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研究生: 沙庫瑪
Prasan Kumar
論文名稱:
Modeling and Performance Analysis of IEEE 802.15.4 MAC for Wireless Sensor Networks
指導教授: 許健平
Jang-Ping Sheu
口試委員:
學位類別: 博士
Doctor
系所名稱: 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
畢業學年度: 97
語文別: 英文
論文頁數: 158
中文關鍵詞: 無線感測網路的模組化IEEE 802.15.4
外文關鍵詞: Wireless sensor networks, IEEE 802.15.4
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  • 無線感測網路(WSN)被想像來廣泛用於各種應用,範圍從環境監測、存貨追蹤、健康監控、家庭自動化到人體內部或周圍的網路連線。近年來,許多的發展都聚焦在新的感測節點之硬體、整合感測和無線電電路及合適的網路通訊協定,以滿足低成本和低功耗的需求。儘管上述在感測器硬體和發展適當的感測器網路通訊協定有所進展,但缺乏合適的無線感測網路標準和相關的商品,已減緩了此項技術的成熟進程。隨著針對低傳輸率、低功耗之無線個人區域網絡(WPANs)的IEEE 802.15.4無線媒體存取控制層(MAC)和實體層(PHY)之標準被釋出後,這種情況可望獲得改善,且是因受到已開始行銷基於此標準所生產產品之公司的嚴重關注。
    對於無線感測網路在資料傳輸能力和網絡壽命方面的效能分析,是關鍵性的研究議題,目標朝向設計出感測網路最佳的部署策略。相對於其他類型的無線網路,節點在無線感測網路中,是以隨意的形式被稠密地部署和組織起來。由於傳輸範圍有限,任兩個節點間無法直接相互通訊,而須依靠其它感測節點,在它們之間幫忙轉送資料。因此,資料封包在來源與目的地間必須經過多次的轉送。此外,感測節點的體積通常很小,且有電力來源上的限制。所以在無線感測網路中,能量消耗的分析是一個重要的效能測量之標的。因IEEE 802.15.4的標準,對於使用低傳輸率、低功耗和短通訊範圍的設備,定義了媒體存取控制的通訊協定。所以,其媒體存取控制的模型建立及效能分析,對於無線感測網路是值得研究的。
    在這篇論文中,我們討論在無線感測網路中,免競爭和競爭基礎的頻道存取機制。考慮在無線感測網路中,不同的MAC機制和對於能量消耗的數學模型之問題,進行分析。對於無線感測網路,我們提出一種混合式頻道存取機制,其中考慮頻道存取程序和結合IEEE 802.11二進制指數後退的機制。以因成功的頻道評估後發生碰撞的碰撞節點(backlogged nodes),利用線性擴展反饋模型和離散時間馬可夫鏈模型,分析無線感測網路中系統模型的成功和失敗機率。此外,在無線感測網路的星狀拓撲中,基於混合式頻道存取機制之能量消耗模式亦被開發。
    此外,對IEEE 802.15.4的信標可用(beacon-enabled)時槽式CSMA-CA機制之分析模型,亦被設計於無線感測網路的星狀拓撲中使用具回應之傳輸。現行IEEE 802.15.4 CSMA-CA機制被加以擴展,包括隨封包碰撞的機率之節點重送限制。而在流量未飽和的條件下,一個IEEE 802.15.4無線感測網路中對於上傳流量的三維馬可夫鏈模型,則被開發用以分析節點的電量消耗和吞吐量。廣泛的效能分析被創造來分析系統模型的電量消耗和吞吐量,及研究不同網路和流量參數如封包到達率、封包大小、節點數目和資料傳輸率的影響。對於無線感測網路,二進制指數競爭視窗(window)在節點的電量消耗之影響是被驗證過。我們的分析模型和廣泛的模擬與驗證比較後,顯示我們所提出的分析架構是完全正確的,且對於電量消耗和流量分析能提供精確的效能預測。


    Wireless sensor network (WSN) is envisioned for a wide range of applications ranging
    from environmental surveillance, inventory tracking, health monitoring, home au-
    tomation to networking in or around a human body. Much of the development in
    recent years has focused on new sensor node hardware, integration of sensing and
    radio circuitry as well as design of suitable networking protocols to meet the require-
    ments of low cost and low power operation. Despite above advances in both sensor
    hardware and development of suitable sensor networking protocols, lack of a suitable
    WSN standard and associated commercial product has slowed the maturation pro-
    cess of this technology. The situation is expected to change with the release of the
    IEEE 802.15.4 Wireless MAC and PHY speci¯cations for low-rate, low-power wireless
    personal area networks (WPANs) due to signi¯cant interest from companies that are
    already beginning to ship products based on this standard.
    Performance analysis of wireless sensor networks in terms of data transmission
    capacity and lifetime of the networks are critical research issues towards the design of
    optimal deployment strategies of the sensor networks. In contrast to other types of
    wireless networks, nodes in wireless sensor networks are densely deployed and organize
    themselves in an ad hoc fashion. Due to limited transmission ranges, any two nodes
    cannot reach each other directly and rely on other sensor nodes to relay data between
    them. Hence, the data packets between the source and destination are routed through
    multi-hops. Besides, sensor nodes are normally small in size and have constrained
    energy sources. Hence energy consumption analysis is an important performance
    measure in wireless sensor networks. Since, IEEE 802.15.4 standard de¯nes medium access control protocol for the devices using low data rate, low power and short-range
    transmissions, modeling and performance analysis of its MAC for the wireless sensor
    network is worth to study.
    In this thesis, the contention free and contention based channel access mechanism
    in wireless sensor networks is discussed. Considering di®erent MAC mechanisms in
    wireless sensor networks, mathematical models for the energy consumption issues are
    analyzed. A hybrid channel access mechanism is proposed for the wireless sensor net-
    work that considers the channel access procedure of IEEE 802.15.4 and combines the
    binary exponential backo® mechanism of IEEE 802.11. Taking the backlogged nodes
    due to collision after successful channel assessment, extended linear feedback model
    and discrete time Markov chain model are designed to analyze the successful and
    failure probabilities of the system model of the wireless sensor network. Besides, en-
    ergy consumption model for the star topology of wireless sensor network is developed
    based on the hybrid channel access mechanism.
    Besides, analytical models for the beacon-enabled slotted CSMA-CA mechanism
    of IEEE 802.15.4 is designed for the star topology of wireless sensor network taking
    acknowledged transmissions. The current mechanism of IEEE 802.15.4 CSMA-CA
    is extended to include the retransmission limit of the nodes with packet collision
    probability. A three-dimensional Markov chain model for the uplink tra±c of IEEE
    802.15.4 wireless sensor network is developed to analyze the energy consumption and
    throughput of the nodes under unsaturated tra±c conditions. Extensive performance
    analysis are made to analyze energy consumption and throughput of the system mod-
    els and to study the impact of di®erent network and tra±c parameters such as the
    packet arrival rate, packet size, node numbers and data rates. The e®ect of binary
    exponential contention window on energy consumption of the nodes is veri¯ed for the
    wireless sensor networks. The comparison with comprehensive simulations and vali-
    dations of our analytical models shows that the proposed analytical frameworks are
    totally correct and provides accurate performance predictions for energy consumption
    and throughput analysis.

    Abstract ii Acknowledgements v List of Tables viii List of Figures ix 1 Introduction 1 1.1 Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1 Home Automation . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.2 Indoor Parking Monitoring . . . . . . . . . . . . . . . . . . . . 5 1.2.3 Warehouse Monitoring . . . . . . . . . . . . . . . . . . . . . . 6 1.3 Motivations and Goals . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.5 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Preliminary 12 vii 2.1 Wireless Medium Access Control Protocols . . . . . . . . . . . . . . . 12 2.1.1 Contention Free MAC . . . . . . . . . . . . . . . . . . . . . . 14 2.1.1.1 Random Access . . . . . . . . . . . . . . . . . . . . . 17 2.1.1.2 Scheduled-based Access . . . . . . . . . . . . . . . . 18 2.1.2 Contention based MAC . . . . . . . . . . . . . . . . . . . . . . 20 2.1.2.1 Reservation based . . . . . . . . . . . . . . . . . . . 22 2.1.2.2 Scheduling based . . . . . . . . . . . . . . . . . . . . 22 2.2 MAC Protocols for WSNs . . . . . . . . . . . . . . . . . . . . . . . . 24 2.3 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3 Channel Access Mechanisms in Wireless Networks 34 3.1 Wireless Access Protocols . . . . . . . . . . . . . . . . . . . . . . . . 34 3.1.1 IEEE 802.11 Speci¯cations . . . . . . . . . . . . . . . . . . . . 37 3.1.2 IEEE 802.15.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.1.3 IEEE 802.15.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.1.4 IEEE 802.15.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.1.5 IEEE 802.15.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.1.5.1 Components of IEEE 802.15.4 . . . . . . . . . . . . . 46 3.1.5.2 Network Topology . . . . . . . . . . . . . . . . . . . 47 3.1.5.3 Data transfer model . . . . . . . . . . . . . . . . . . 48 3.1.5.4 Superframe Structure . . . . . . . . . . . . . . . . . 51 3.2 Comparisons of Channel Access Mechanisms . . . . . . . . . . . . . . 52 3.2.1 IEEE 802.11 MAC Mechanism . . . . . . . . . . . . . . . . . . 53 3.2.2 IEEE 802.15.4 MAC Mechanism . . . . . . . . . . . . . . . . . 57 viii 4 Performance Analysis of MAC with Hybrid Channel Access Mech- anism 62 4.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.1.1 Hybrid CSMA-CA Mechanism . . . . . . . . . . . . . . . . . . 65 4.2 Analytical Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.2.1 Extended Linear Feedback Model . . . . . . . . . . . . . . . . 67 4.2.2 Discrete-Time Markov Chain Model . . . . . . . . . . . . . . . 69 4.3 Energy Consumption Analysis . . . . . . . . . . . . . . . . . . . . . . 74 4.3.1 Packet Retransmission Model . . . . . . . . . . . . . . . . . . 75 4.3.2 Energy Consumption Model . . . . . . . . . . . . . . . . . . . 77 4.4 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.4.1 Simulation Setups . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.4.2 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . 82 4.4.3 E®ective Energy Consumption Analysis . . . . . . . . . . . . . 90 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5 Performance Analysis of MAC with Packet Retransmission Limits 95 5.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.1.1 Retransmission based CSMA-CA Mechanism . . . . . . . . . . 97 5.2 Analytical Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.2.1 The Markov Chain Model . . . . . . . . . . . . . . . . . . . . 100 5.2.2 Packet Collision Probability . . . . . . . . . . . . . . . . . . . 103 5.2.3 Channel Assess Probability . . . . . . . . . . . . . . . . . . . 104 5.2.4 Packet Transmission Probability . . . . . . . . . . . . . . . . . 107 ix 5.2.5 Conditional Channel Access Probability . . . . . . . . . . . . 108 5.2.6 Steady State Probabilities . . . . . . . . . . . . . . . . . . . . 110 5.3 Throughput and Energy Consumption Analysis . . . . . . . . . . . . 112 5.3.1 Throughput Analysis Model . . . . . . . . . . . . . . . . . . . 112 5.3.2 Energy Consumption Model . . . . . . . . . . . . . . . . . . . 114 5.4 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 115 5.4.1 Simulation Setups . . . . . . . . . . . . . . . . . . . . . . . . . 115 5.4.2 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . 116 5.4.2.1 E®ect of NRT . . . . . . . . . . . . . . . . . . . . . . 118 5.4.3 Throughput and Energy Analysis . . . . . . . . . . . . . . . . 118 5.4.3.1 High Data Rate . . . . . . . . . . . . . . . . . . . . . 120 5.4.3.2 Low Data Rate . . . . . . . . . . . . . . . . . . . . . 122 5.4.3.3 E®ect of Node Numbers . . . . . . . . . . . . . . . . 123 5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 6 Conclusions and Future Work 125 6.1 Major Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Bibliography 130 x

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