IEEE802.15.4无线传感器网络性能分析及改进研究
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摘要
传感器技术、无线通信技术的进步,推动了无线传感器网络(WSN,Wireless Sensor Networks)的产生与发展。普遍接受的无线传感器网络的定义是:大规模、无线、自组织、多跳、无基础设施支持的网络,其中节点具有同构、低成本、体积较小等特点,被随意散布在工作区域采集数据,要求网络有尽可能长的生存时间。无线传感器网络在军事、环境监测、农业、工业控制等方面有很广泛的应用前景。
IEEE802.15.4标准是IEEE标准化协会为低速无线个人网(LR-WPAN,Low-Rate Wireless Personal Network)制定的通信标准,它定义了LR-WPAN的物理层和介质访问控制层。该标准具有低速率、低功耗、传输距离短、架构简单等特点,这些都很适合无线传感器网络。本文分析了大规模的应用IEEE802.15.4协议的无线传感器网络的性能,实现了小规模的基于IEEE802.15.4的无线传感器网络。为了使网络的能量消耗最小并且达到足够大的网络覆盖率,网络采用树型分簇拓扑结构并且使用信标。在文中我们分析了CSMA/CA算法和IEEE802.15.4标准的模型,性能参数是吞吐量和功耗,分析了SO和BO等标准参数对网络性能的影响。最后应用OPNET对我们的分析进行了仿真,并验证了分析的正确性。
然后应用兼容2.4GHz IEEE802.15.4标准射频芯片CC2420设计实现无线传感器网络,包括节点、路由算法的设计与实现,以及节点能耗的分析。因为协调器和设备的功耗差别很大,为了提高无线传感器网络的能量利用效率、延长网络的生存时间,我们提出了一种新的分簇算法,叫做基于能量和极大独立集的最小连通支配集算法,利用节点两跳以内的邻居信息和能量选举支配点(簇头),非支配点(普通节点)根据就近原则加入到距离最近的支配点为簇头形成的簇中。仿真结果表明,本算法和其他分簇算法相比可以更好地平衡网络的能量消耗,提高全网的能量利用率,极大地延长网络的生存时间。
The rapid development of sensor wireless communication technology promotes the appearance and evolution of Wireless Sensor Network(WSN). It is generally accepted that the definition of WSN includes large scale, self-organization, multi-hop and no infrastructure supporting. WSN node is always structure-identical, low cost and small size. The nodes are randomly distributed in the monitoring area and collect data. It is required that WSN must have a long life time.
The IEEE 802.15.4 standard is released by the IEEE 802.15 group 4, which is suitable for Low-Rate Wireless Personal Area Network(LR-WPAN). The standard defines LR-WPAN’s PHY layer and MAC layer. The standard with the features of low rate, low power, short communication range and simple structure is very fit for WSN. The performance of IEEE 802.15.4 standard in a large-scale WSN application is analyzed. To minimize the energy consumption of the entire network and to allow adequate network coverage, IEEE 802.15.4 peer-to-peer topology is selected, and configured to a beacon-enabled cluster-tree structure. The analysis consists of models for CSMA-CA mechanism and MAC operations specified by IEEE 802.15.4. The performances of device and coordinator are analyzed in terms of power consumption and throughput, and the effect of SO and BO for the network performance is analyzed. The analysis results are verified with simulations using OPNET.
Then we apply 2.4GHz IEEE802.15.4 compliant RF transceiver CC2420 design a wireless sensor network system, including the design and implementation of node and route protocol. And we analyze the energy consumption of our node. In order to balance the great difference of consumption between device and coordinator in the network, we propose a new clustering algorithm, called Energy and Maximal Independent Set Based distributed algorithm for minimum connected set(EMISB). The algorithm utilizes node’s energy status and 2-hop neighbor information to select cluster head, other nodes will join the cluster which head is the nearest one. Simulation results show that, compared to the other clustering algorithm, the new algorithm can prolong the lifetime of the network evidently while balancing energy consumption and increasing energy efficiency.
IEEE802.15.4标准是IEEE标准化协会为低速无线个人网(LR-WPAN,Low-Rate Wireless Personal Network)制定的通信标准,它定义了LR-WPAN的物理层和介质访问控制层。该标准具有低速率、低功耗、传输距离短、架构简单等特点,这些都很适合无线传感器网络。本文分析了大规模的应用IEEE802.15.4协议的无线传感器网络的性能,实现了小规模的基于IEEE802.15.4的无线传感器网络。为了使网络的能量消耗最小并且达到足够大的网络覆盖率,网络采用树型分簇拓扑结构并且使用信标。在文中我们分析了CSMA/CA算法和IEEE802.15.4标准的模型,性能参数是吞吐量和功耗,分析了SO和BO等标准参数对网络性能的影响。最后应用OPNET对我们的分析进行了仿真,并验证了分析的正确性。
然后应用兼容2.4GHz IEEE802.15.4标准射频芯片CC2420设计实现无线传感器网络,包括节点、路由算法的设计与实现,以及节点能耗的分析。因为协调器和设备的功耗差别很大,为了提高无线传感器网络的能量利用效率、延长网络的生存时间,我们提出了一种新的分簇算法,叫做基于能量和极大独立集的最小连通支配集算法,利用节点两跳以内的邻居信息和能量选举支配点(簇头),非支配点(普通节点)根据就近原则加入到距离最近的支配点为簇头形成的簇中。仿真结果表明,本算法和其他分簇算法相比可以更好地平衡网络的能量消耗,提高全网的能量利用率,极大地延长网络的生存时间。
The rapid development of sensor wireless communication technology promotes the appearance and evolution of Wireless Sensor Network(WSN). It is generally accepted that the definition of WSN includes large scale, self-organization, multi-hop and no infrastructure supporting. WSN node is always structure-identical, low cost and small size. The nodes are randomly distributed in the monitoring area and collect data. It is required that WSN must have a long life time.
The IEEE 802.15.4 standard is released by the IEEE 802.15 group 4, which is suitable for Low-Rate Wireless Personal Area Network(LR-WPAN). The standard defines LR-WPAN’s PHY layer and MAC layer. The standard with the features of low rate, low power, short communication range and simple structure is very fit for WSN. The performance of IEEE 802.15.4 standard in a large-scale WSN application is analyzed. To minimize the energy consumption of the entire network and to allow adequate network coverage, IEEE 802.15.4 peer-to-peer topology is selected, and configured to a beacon-enabled cluster-tree structure. The analysis consists of models for CSMA-CA mechanism and MAC operations specified by IEEE 802.15.4. The performances of device and coordinator are analyzed in terms of power consumption and throughput, and the effect of SO and BO for the network performance is analyzed. The analysis results are verified with simulations using OPNET.
Then we apply 2.4GHz IEEE802.15.4 compliant RF transceiver CC2420 design a wireless sensor network system, including the design and implementation of node and route protocol. And we analyze the energy consumption of our node. In order to balance the great difference of consumption between device and coordinator in the network, we propose a new clustering algorithm, called Energy and Maximal Independent Set Based distributed algorithm for minimum connected set(EMISB). The algorithm utilizes node’s energy status and 2-hop neighbor information to select cluster head, other nodes will join the cluster which head is the nearest one. Simulation results show that, compared to the other clustering algorithm, the new algorithm can prolong the lifetime of the network evidently while balancing energy consumption and increasing energy efficiency.
引文
[1] ZigBee Alliance Document 053474r06; ZigBee Specification,Version 1.0, Dec 2004.
[2] 802.15.4-2006 IEEE Standard for Information Technology-Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer(PHY) Specifications for Low Rate Wireless Personal Area Networks(LR-WPANS), 2006.
[3] S. J. Kristor, Pister. Tracking vehicles with a UAV-delivered sensor network. http://robotics.eecs.berkeley.edu/～pister/29Palms0103/.
[4] A. Mainwaring, J. Polastre, R. Szewczyk, etal. Wireless sensor networks for habitat monitoring. In ACM Workshop on Sensor Networks and Applications, 2002, 88-97
[5] G. Tolle, J. Polastre, R. Szewczyk, etal. A macroscope in the redwoods, Proceedings of the 3rd international conference on Embedded networked sensor systems, San Diego, California, 2005, 51-63
[6] A. Cerpa, J. Elson, D.Estrin, etal. Habitat monitoring: Application driver for wireless communications technology. In ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, San Jose, Costa Rica, 2001, 20-41
[7] K. Martinez, R. ong, J. K. Hart, etal. GLAC-SWEB: A Sensor Web for Glaciers. In Adjunct Proc. EWSN2004, Berlin, Germany, 2004, 56-62
[8] T. Gao, D. Greenspan, M. Welsh. Vital Signs Monitoring and Patient Tracking Over a Wireless Network. Proceedings of the 27th IEEE EMBS Annual International Conference, September, 2005
[9] Z. Butler, P. Corke, R. Peterson, etal. 2004. Virtual fences for controlling cows. ICRA, New Orleans, LA.
[10] S. N. Pakzad, S. Kim, G. L. Fenves, etal. Multi-purpose wireless accelerometers for civil infrastructure monitoring. 5th International Work-shop on Structural Health Monitoring (IWSHM 2005), Stanford, CA, 2005.
[11] G. Werner-Allen, J. Johnson, M. Ruiz, etal. Monitoring volcanic eruptions with a wireless sensor network. In Proc. Second European Workshop on Wireless Sensor Networks(EWSN’05), 2005, 108-120
[12] A. Koubaa, M. Alves, E. Tovar. A Comprehensive Simulation Study of Slotted CSMA/CA for IEEE 802.15.4 Wireless Sensor Networks. 2006 IEEE International Workshop on FactoryCommunication Systems. Torino, Italy, 2006, 183-192
[13] J. Mi?ic, V. B. Mi?ic. Duty Cycle Management in Sensor Networks Based on 802.15.4 Beacon Enabled MAC. Ad Hoc and Sensor Wireless Networks Journal, Old City Publishing, 2005, 1(3):207-233.
[14] J. Mi?ic, V. B. Mi?ic. Access Delay and Throughput for Uplink Transmissions in IEEE 802.15.4 PAN. Elsevier Computer Communications Journal, 2005., 28(10):1152-1166.
[15] J. Mi?ic, S. Shafi, V. B. Mi?ic. The Impact of MAC Parameters on the Performance of 802.15.4 PAN. Elsevier Ad hoc Networks Journal, 3(5):509–528, 2005.
[16] TR Park, TH Kim, JY Choi, etal, Throughput and energy consumption analysis of IEEE 802.15.4 slotted CSMA/CA. IEEE Electronics Letters, 2005, 41(18): 1017-1019.
[17] J. Zheng, M. L. Lee. A Comprehensive Performance Study of IEEE 802.15.4. IEEE Press Book, 2004.
[18] B. Bougard, F.Catthoor, D.C. Daly, etal. Energy efficiency of IEEE 802.15.4 standard in dense wireless microsensor networks: modeling and improvement perspectives, in Proceedings of Design, automation and test in Europe (DATE’05). Munich, Germany: IEEE, 2005, Vol.1: 196-201.
[19] N. Timmons, W. Scanlon. Analysis of the performance of IEEE 802.15.4 for medical sensor body area networking, in Proceedings of the 1st IEEE international conference. On Sensor and ad hoc communications and networks (SECON’04). Santa Clara, USA: IEEE, 2004, 16-24.
[20] G. Lu, B. Krishnamachari, C.S. Raghavendra. Performance evaluation of the IEEE 802.15.4 MAC for low-rate low-power wireless networks, in Proceedings of the 23rd IEEE international Performance computing and communications conference (IPCCC’04). Phoenix, USA: IEEE, 2004, 701-706.
[21] Y. C. Tseng, S.Y. Ni, E.Y.Shih. Adaptive approaches to relieving broadcast storms in a wireless multihop mobile ad hoc network, IEEE Trans. on Computers, 2003, 545-557.
[22]陈敏. OPNET网络仿真.北京:清华大学出版社, 2003, 2-5.
[23] J. M. Kahn, R. H. Katz, K. S. Piste. Next Century Challenges: Mobile Networking for“Smart Dust”. Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking. Seattle: IEEE,1999, 271-278.
[24] http://www.tinyos.net/scoop/special/hardware/
[25] http://www.tinyos.net/
[26] David Gay, Philip Levis, David Culler, etal. nesC1.1 language reference manual, 2003. http://nesc.sourceforge.net/papers/nesC-ref.pdf
[27]李学海. EM78单片机实用教程.北京:电子工业出版社, 2003, 15-16.
[28] CC2420 data sheet, http://www.chipcon.com/files/CC2420 Data Sheet_1_ 2.pdf
[29] Chipcon AS SmartRF CC2420 Preliminary Datasheet (rev1.2), 2004-06-09
[30]董传坤,向渝,汪文勇.无线传感器网络节点能量预测模型研究. CERNET的发展与研究.中国,天津, 2009, 293-298.
[31] W. Heinzelman, A. Chandrakasan, H. Balakrishnan. An application specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Communication, 2002, 1(4): 660–670.
[32] O. Younis, S. Fahmy. Distributed clustering in ad-hocsensor networks: A hybrid energy-efficient approach. In: Proc 13th Joint Conf on IEEE Computer and Communications Societies (INFOCOM), March 2004.
[33] Zhou W, Chen H M, Zhang X F. An energy efficient strong head clustering algorithm for wireless sensor networks. Wireless Communications, Networking and Mobile Computing, 2007. 2007. 2584-2587
[34] Zhu X, Shen L, Yum T. Hausdorff clustering and minimum energy routing for wireless sensor networks. Vehicular Technology, IEEE Transactions on, 2009, 58(2) : 990-997
[35] A. Khan, A. B. Abdullah, A. Rahman. Data Delivery Optimization by Efficient Cluster Head Selection of Wireless Sensor Network. 2009 5th International Colloquium on Signal Processing &its Applications(CSPA). Kuala Lumpur : IEEE, 2009.186-190
[36] S. Bandyopadhyay, E.J. Coyle. An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. INFOCOM 2003. San Francisco: IEEE, 2003. Volume(3), 1713-1723.
[37] K. Dasgupta, K. Kalpakis, P. Namjoshi. An Efficient Clustering-based Heuristic for Data Gathering and Aggregation in Sensor Networks. Wireless Communications and Networking (WCNC 2003). New Orleans: IEEE, 2003. vol(3), 1948-1953.
[38]林恺,赵海,尹震宇,罗玎玎。一种基于能量预测的无线传感器网络分簇算法.电子学报,2008,36(4): 824-828.
[39]龚海刚,刘明,陈力军,谢立. DEED:一种无线传感器网络中高效节能的数据通信协议.电子学报,2005,33(8): 1391-1396.
[40]唐勇,周明天.基于极大独立集的最小连通支配集的分布式算法.电子学报,2007,35(5): 868-874.
[41] Laouiti A ,Qayyum A ,Viennot L . Multipoint relaying: an efficient technique for flooding in mobile wireless networks. Proceedings of the 35th Annual Hawaii Int’l Conf on System Sciences.Hawaii: IEEE Press, 2002. 298 - 307.
[42] Wu J. An enhanced approach to determine a small forwardnode set based on multipoint relay. Proceedings of the 58th IEEE Vehicular Technology Conference. Florida: IEEE Press, 2003. 2774 - 2777.
[2] 802.15.4-2006 IEEE Standard for Information Technology-Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer(PHY) Specifications for Low Rate Wireless Personal Area Networks(LR-WPANS), 2006.
[3] S. J. Kristor, Pister. Tracking vehicles with a UAV-delivered sensor network. http://robotics.eecs.berkeley.edu/～pister/29Palms0103/.
[4] A. Mainwaring, J. Polastre, R. Szewczyk, etal. Wireless sensor networks for habitat monitoring. In ACM Workshop on Sensor Networks and Applications, 2002, 88-97
[5] G. Tolle, J. Polastre, R. Szewczyk, etal. A macroscope in the redwoods, Proceedings of the 3rd international conference on Embedded networked sensor systems, San Diego, California, 2005, 51-63
[6] A. Cerpa, J. Elson, D.Estrin, etal. Habitat monitoring: Application driver for wireless communications technology. In ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, San Jose, Costa Rica, 2001, 20-41
[7] K. Martinez, R. ong, J. K. Hart, etal. GLAC-SWEB: A Sensor Web for Glaciers. In Adjunct Proc. EWSN2004, Berlin, Germany, 2004, 56-62
[8] T. Gao, D. Greenspan, M. Welsh. Vital Signs Monitoring and Patient Tracking Over a Wireless Network. Proceedings of the 27th IEEE EMBS Annual International Conference, September, 2005
[9] Z. Butler, P. Corke, R. Peterson, etal. 2004. Virtual fences for controlling cows. ICRA, New Orleans, LA.
[10] S. N. Pakzad, S. Kim, G. L. Fenves, etal. Multi-purpose wireless accelerometers for civil infrastructure monitoring. 5th International Work-shop on Structural Health Monitoring (IWSHM 2005), Stanford, CA, 2005.
[11] G. Werner-Allen, J. Johnson, M. Ruiz, etal. Monitoring volcanic eruptions with a wireless sensor network. In Proc. Second European Workshop on Wireless Sensor Networks(EWSN’05), 2005, 108-120
[12] A. Koubaa, M. Alves, E. Tovar. A Comprehensive Simulation Study of Slotted CSMA/CA for IEEE 802.15.4 Wireless Sensor Networks. 2006 IEEE International Workshop on FactoryCommunication Systems. Torino, Italy, 2006, 183-192
[13] J. Mi?ic, V. B. Mi?ic. Duty Cycle Management in Sensor Networks Based on 802.15.4 Beacon Enabled MAC. Ad Hoc and Sensor Wireless Networks Journal, Old City Publishing, 2005, 1(3):207-233.
[14] J. Mi?ic, V. B. Mi?ic. Access Delay and Throughput for Uplink Transmissions in IEEE 802.15.4 PAN. Elsevier Computer Communications Journal, 2005., 28(10):1152-1166.
[15] J. Mi?ic, S. Shafi, V. B. Mi?ic. The Impact of MAC Parameters on the Performance of 802.15.4 PAN. Elsevier Ad hoc Networks Journal, 3(5):509–528, 2005.
[16] TR Park, TH Kim, JY Choi, etal, Throughput and energy consumption analysis of IEEE 802.15.4 slotted CSMA/CA. IEEE Electronics Letters, 2005, 41(18): 1017-1019.
[17] J. Zheng, M. L. Lee. A Comprehensive Performance Study of IEEE 802.15.4. IEEE Press Book, 2004.
[18] B. Bougard, F.Catthoor, D.C. Daly, etal. Energy efficiency of IEEE 802.15.4 standard in dense wireless microsensor networks: modeling and improvement perspectives, in Proceedings of Design, automation and test in Europe (DATE’05). Munich, Germany: IEEE, 2005, Vol.1: 196-201.
[19] N. Timmons, W. Scanlon. Analysis of the performance of IEEE 802.15.4 for medical sensor body area networking, in Proceedings of the 1st IEEE international conference. On Sensor and ad hoc communications and networks (SECON’04). Santa Clara, USA: IEEE, 2004, 16-24.
[20] G. Lu, B. Krishnamachari, C.S. Raghavendra. Performance evaluation of the IEEE 802.15.4 MAC for low-rate low-power wireless networks, in Proceedings of the 23rd IEEE international Performance computing and communications conference (IPCCC’04). Phoenix, USA: IEEE, 2004, 701-706.
[21] Y. C. Tseng, S.Y. Ni, E.Y.Shih. Adaptive approaches to relieving broadcast storms in a wireless multihop mobile ad hoc network, IEEE Trans. on Computers, 2003, 545-557.
[22]陈敏. OPNET网络仿真.北京:清华大学出版社, 2003, 2-5.
[23] J. M. Kahn, R. H. Katz, K. S. Piste. Next Century Challenges: Mobile Networking for“Smart Dust”. Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking. Seattle: IEEE,1999, 271-278.
[24] http://www.tinyos.net/scoop/special/hardware/
[25] http://www.tinyos.net/
[26] David Gay, Philip Levis, David Culler, etal. nesC1.1 language reference manual, 2003. http://nesc.sourceforge.net/papers/nesC-ref.pdf
[27]李学海. EM78单片机实用教程.北京:电子工业出版社, 2003, 15-16.
[28] CC2420 data sheet, http://www.chipcon.com/files/CC2420 Data Sheet_1_ 2.pdf
[29] Chipcon AS SmartRF CC2420 Preliminary Datasheet (rev1.2), 2004-06-09
[30]董传坤,向渝,汪文勇.无线传感器网络节点能量预测模型研究. CERNET的发展与研究.中国,天津, 2009, 293-298.
[31] W. Heinzelman, A. Chandrakasan, H. Balakrishnan. An application specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Communication, 2002, 1(4): 660–670.
[32] O. Younis, S. Fahmy. Distributed clustering in ad-hocsensor networks: A hybrid energy-efficient approach. In: Proc 13th Joint Conf on IEEE Computer and Communications Societies (INFOCOM), March 2004.
[33] Zhou W, Chen H M, Zhang X F. An energy efficient strong head clustering algorithm for wireless sensor networks. Wireless Communications, Networking and Mobile Computing, 2007. 2007. 2584-2587
[34] Zhu X, Shen L, Yum T. Hausdorff clustering and minimum energy routing for wireless sensor networks. Vehicular Technology, IEEE Transactions on, 2009, 58(2) : 990-997
[35] A. Khan, A. B. Abdullah, A. Rahman. Data Delivery Optimization by Efficient Cluster Head Selection of Wireless Sensor Network. 2009 5th International Colloquium on Signal Processing &its Applications(CSPA). Kuala Lumpur : IEEE, 2009.186-190
[36] S. Bandyopadhyay, E.J. Coyle. An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. INFOCOM 2003. San Francisco: IEEE, 2003. Volume(3), 1713-1723.
[37] K. Dasgupta, K. Kalpakis, P. Namjoshi. An Efficient Clustering-based Heuristic for Data Gathering and Aggregation in Sensor Networks. Wireless Communications and Networking (WCNC 2003). New Orleans: IEEE, 2003. vol(3), 1948-1953.
[38]林恺,赵海,尹震宇,罗玎玎。一种基于能量预测的无线传感器网络分簇算法.电子学报,2008,36(4): 824-828.
[39]龚海刚,刘明,陈力军,谢立. DEED:一种无线传感器网络中高效节能的数据通信协议.电子学报,2005,33(8): 1391-1396.
[40]唐勇,周明天.基于极大独立集的最小连通支配集的分布式算法.电子学报,2007,35(5): 868-874.
[41] Laouiti A ,Qayyum A ,Viennot L . Multipoint relaying: an efficient technique for flooding in mobile wireless networks. Proceedings of the 35th Annual Hawaii Int’l Conf on System Sciences.Hawaii: IEEE Press, 2002. 298 - 307.
[42] Wu J. An enhanced approach to determine a small forwardnode set based on multipoint relay. Proceedings of the 58th IEEE Vehicular Technology Conference. Florida: IEEE Press, 2003. 2774 - 2777.
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