EasiDARM:基于分布式的物联网设备自适应注册方法
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摘要
随着物联网水平化接入协议的逐步成熟与实用化,将设备接入云平台以对设备进行实时访问逐步成为一种主流架构.由于物联网设备或其所处网络环境存在动态性,为了保证物联网云平台与设备之间的双向实时访问,设备往往需要到云平台进行周期注册.而现有注册方法存在开销大、耗时长的缺点,当大量设备或网络处于强动态场景时,云平台的注册开销将急剧加大.为此,提出了基于分布式的物联网设备自适应注册方法(EasiDARM),将复杂且耗时的周期探测过程分配给多个设备执行,并通过参数同步实现结果实时共享,极大地加快周期探测和设备自适应过程,降低物端、网端和云端开销.该方法将周期探测过程分为"快更新"和"快收敛"前后2个阶段,"快更新"阶段采用指数增长方式进行任务分配及周期探测,加快注册周期增长速度,"快收敛"阶段采用线性增长方式进行任务分配及周期探测,加快周期探测收敛速度.实验结果表明:较于传统的自适应注册方法,该方法周期探测耗时能减少46%,物端开销能降低46%,网端通信开销和云端处理开销能降低53%;同时能使云平台的突发性开销降低36%.
With the perfecting and practicability of the access protocols of the Internet of things(IoT), it is becoming a mainstream architecture to connect devices to cloud platforms for support of real-time access. Considering the dynamic nature of IoT devices and networks, we must make the devices register on the platforms periodically to ensure real-time access between the devices and the platforms. However, existing register methods cost much time and consume a lot of resources on devices, Internet and platforms; and what's more, the platforms will be overload when many devices or networks are dynamic. In this paper, we present a distributed based adaptive register method(EasiDARM) to reduce the costs of resources and time. By using multiple devices to complete the measurement of network address translation(NAT) timeout which is complex and time-consuming, and sharing the result of measurement among the devices, EasiDARM accelerates the processes of the measurement and self-adaption. The process of measurement is divided into fast update(FU) and fast converge(FC) stage, EasiDARM assigns and probes the candidate intervals with exponential growth during the FU stage to extend the register interval rapidly, and with linear growth during the FC stage to converge the measurement quickly. Through experiments show that compared with the traditional adaptive register method, EasiDARM can reduce 46% of time, 46% of consumption on devices and 53% of consumption on Internet and platforms in the process of measurement, and cut 36% of instantaneous consumption on platforms.
With the perfecting and practicability of the access protocols of the Internet of things(IoT), it is becoming a mainstream architecture to connect devices to cloud platforms for support of real-time access. Considering the dynamic nature of IoT devices and networks, we must make the devices register on the platforms periodically to ensure real-time access between the devices and the platforms. However, existing register methods cost much time and consume a lot of resources on devices, Internet and platforms; and what's more, the platforms will be overload when many devices or networks are dynamic. In this paper, we present a distributed based adaptive register method(EasiDARM) to reduce the costs of resources and time. By using multiple devices to complete the measurement of network address translation(NAT) timeout which is complex and time-consuming, and sharing the result of measurement among the devices, EasiDARM accelerates the processes of the measurement and self-adaption. The process of measurement is divided into fast update(FU) and fast converge(FC) stage, EasiDARM assigns and probes the candidate intervals with exponential growth during the FU stage to extend the register interval rapidly, and with linear growth during the FC stage to converge the measurement quickly. Through experiments show that compared with the traditional adaptive register method, EasiDARM can reduce 46% of time, 46% of consumption on devices and 53% of consumption on Internet and platforms in the process of measurement, and cut 36% of instantaneous consumption on platforms.
引文
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[16]Alibaba. Alibaba smart living platform [OL] [2017-05-23]. http://open.aliplus.com/
[17]Ajitomi D, Kawazoe H, Minami K, et al. A cost-effective method to keep availability of many cloud-connected devices[C] //Proc of the 8th IEEE Int Conf on Cloud Computing. Piscataway, NJ: IEEE, 2015: 1- 8
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[19]LORD MicroStrain. SensorCloud platform[OL]. [2017-05-23]. http://www.sensorcloud.com/
[20]Everyware. Everyware platform[OL]. [2017-05-23]. http://everyware.com/
[21]Evrythng. EVRYTHNG IoT smart products platform[OL]. [2017-05-23]. https://evrythng.com/
[22]Shi Hailong, Li Dong, Qiu Jiefan, et al. A task execution framework for cloud-assisted sensor networks[J]. Journal of Computer Science and Technology, 2014, 29(2): 216- 226
[23]Nimbits. Nimbits Internet of things platform[OL]. [2017-05-23]. http://www.nimbits.com/
[24]Wen Binmin. A research and application of MQTT protocol base on adaptive heartbeat mechanism[D]. Guangzhou: South China University of Technology, 2015 (in Chinese)(温彬民. 一种基于自适应心跳机制的MQTT通信协议的研究与应用[D]. 广州: 华南理工大学, 2015)
[25]Guha S, Francis P. Characterization and measurement of TCP traversal through NATs and firewalls[C] //Proc of the 5th ACM SIGCOMM Conf on Internet Measurement. New York: ACM, 2005: 199- 211
[26]Acunto L, Pouwelse J, Sips H. A measurement of NAT & firewall characteristics in peer to peer systems[C] //Proc of the 15th Advanced School for Computing and Imaging Conf. Delft, Netherlands: Advanced School for Computing and Imaging (ASCI), 2009
[27]H?t?nen S, Nyrhinen A, Eggert L, et al. An experimental study of home gateway characteristics[C] //Proc of the 10th ACM SIGCOMM Conf on Internet Measurement. New York: ACM, 2010: 260- 266
[28]Bernstein D, Cohn J. Adapting to NAT timeout values in P2P overlay networks[C] //Proc of the 24th IEEE Int Symp on Parallel and Distributed Processing, Workshops and PhD Forum (IPDPSW). Piscataway, NJ: IEEE, 2010
[29]Rahman M S, Uddin Y S, Rahman M S, et al. Using adaptive heartbeat rate on long-lived TCP connections[C] //Proc of the 2nd Int Conf on Networking Systems and Security(NSysS). Piscataway, NJ: IEEE, 2016
[30]Wang Zhaoguang, Qian Zhiyun, Xu Qiang, et al. An untold story of middleboxes in cellular networks[C] //Proc of the 11th ACM SIGCOMM Conf. New York: ACM, 2011: 374- 385
[2]Cui Li, Huang Xi, Li Dong, et al. Ecosystem of Internet of things technology[J]. High-Technology & Industrialization, 2014, 10(7): 80- 85 (in Chinese)(崔莉, 黄希, 李栋, 等. 物联网技术生态系统[J]. 高科技与产业化, 2014, 10(7): 80- 85)
[3]Shelby Z, Hartke K, Bormann C. The constrained application protocol (CoAP)[EB/OL]. [2017-05-23]. https://tools.ietf.org/html/rfc7252
[4]OASIS. Message queuing telemetry transport[OL]. [2017-05-23]. http://docs.oasis-open.org/mqtt/
[5]Open Mobile Alliance. Light weight machine to machine (LWM2M)[OL]. [2017-05-23]. http://openmobilealliance.org/iot/lightweight-m2m-lwm2m
[6]Tolle G. Embedded binary HTTP (EBHTTP)[OL]. [2017-05-23]. http://tools.ietf.org/id/draft-tolle-core-ebhttp-00.txt
[7]LogMeIn. IoT platform for connected devices Xively by LogMeIn[OL]. [2017-05-23]. https://www.xively.com/
[8]IBM. IBM watson Internet of things (IoT)[OL]. [2017-05-23]. https://www.ibm.com/internet-of-things/
[9]China Mobile Communications Corporation. OneNET Internet of things platform[OL]. [2017-05-23]. http://open.iot.10086.cn/
[10]Yeelink. Yeelink Internet of things platform[OL]. [2017-05-23]. http://www.yeelink.net/
[11]China Academy of Information and Communications Technology. Internet of things white paper(2016)[OL]. 2016 [2017-05-23]. http://www.caict.ac.cn/kxyj/qwfb/bps/201612/t20161228_2185496.htm (in Chinese)(中国信息通信研究院. 物联网白皮书(2016年)[OL]. 2016 [2017-05-23]. http://www.caict.ac.cn/kxyj/qwfb/bps/201612/t20161228_ 2185496.htm)
[12]Gartner. Gartner says the Internet of things installed base will grow to 26 billion units by 2020[OL]. [2017-05-23]. http://www.gartner.com/newsroom/id/2636073
[13]Chen Haiming, Shi Hailong, Li Meng, et al. Service middleware for Internet of things: Challenges and approaches[J]. Chinese Journal of Computers, 2017, 40(8): 1725- 1749 (in Chinese)(陈海明, 石海龙, 李勐, 等. 物联网服务中间件: 挑战与研究进展[J]. 计算机学报, 2017, 40(8): 1725- 1749)
[14]Baidu. Baidu Internet of things platform[OL]. [2017-05-23]. https://cloud.baidu.com/solution/iot/index.html/
[15]Lewei50. Lewei50 Internet of things platform[OL]. [2017-05-23]. http://www.lewei50.com/
[16]Alibaba. Alibaba smart living platform [OL] [2017-05-23]. http://open.aliplus.com/
[17]Ajitomi D, Kawazoe H, Minami K, et al. A cost-effective method to keep availability of many cloud-connected devices[C] //Proc of the 8th IEEE Int Conf on Cloud Computing. Piscataway, NJ: IEEE, 2015: 1- 8
[18]Mathworks. IoT analytics-ThingSpeak Internet of things[OL]. [2017-05-23]. https://thingspeak.com/
[19]LORD MicroStrain. SensorCloud platform[OL]. [2017-05-23]. http://www.sensorcloud.com/
[20]Everyware. Everyware platform[OL]. [2017-05-23]. http://everyware.com/
[21]Evrythng. EVRYTHNG IoT smart products platform[OL]. [2017-05-23]. https://evrythng.com/
[22]Shi Hailong, Li Dong, Qiu Jiefan, et al. A task execution framework for cloud-assisted sensor networks[J]. Journal of Computer Science and Technology, 2014, 29(2): 216- 226
[23]Nimbits. Nimbits Internet of things platform[OL]. [2017-05-23]. http://www.nimbits.com/
[24]Wen Binmin. A research and application of MQTT protocol base on adaptive heartbeat mechanism[D]. Guangzhou: South China University of Technology, 2015 (in Chinese)(温彬民. 一种基于自适应心跳机制的MQTT通信协议的研究与应用[D]. 广州: 华南理工大学, 2015)
[25]Guha S, Francis P. Characterization and measurement of TCP traversal through NATs and firewalls[C] //Proc of the 5th ACM SIGCOMM Conf on Internet Measurement. New York: ACM, 2005: 199- 211
[26]Acunto L, Pouwelse J, Sips H. A measurement of NAT & firewall characteristics in peer to peer systems[C] //Proc of the 15th Advanced School for Computing and Imaging Conf. Delft, Netherlands: Advanced School for Computing and Imaging (ASCI), 2009
[27]H?t?nen S, Nyrhinen A, Eggert L, et al. An experimental study of home gateway characteristics[C] //Proc of the 10th ACM SIGCOMM Conf on Internet Measurement. New York: ACM, 2010: 260- 266
[28]Bernstein D, Cohn J. Adapting to NAT timeout values in P2P overlay networks[C] //Proc of the 24th IEEE Int Symp on Parallel and Distributed Processing, Workshops and PhD Forum (IPDPSW). Piscataway, NJ: IEEE, 2010
[29]Rahman M S, Uddin Y S, Rahman M S, et al. Using adaptive heartbeat rate on long-lived TCP connections[C] //Proc of the 2nd Int Conf on Networking Systems and Security(NSysS). Piscataway, NJ: IEEE, 2016
[30]Wang Zhaoguang, Qian Zhiyun, Xu Qiang, et al. An untold story of middleboxes in cellular networks[C] //Proc of the 11th ACM SIGCOMM Conf. New York: ACM, 2011: 374- 385