节点位置信息驱动的物联网终端缓存管理机制的研究
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摘要
物联网通过物体、传感设备与网络的关联来实现物体自动、实时的识别、定位、追踪和监控,并触发相关事件.面对持续采集或到达的数据流,物联网的移动终端间需要进行大量的数据交互.在节点缓存空间有限的条件下,合理的节点缓存管理机制可以在提高消息投递成功率的同时减少网络开销、降低终端能耗.然而,现有缓存管理机制都是从消息队列特征或静态属性方面展开研究,忽视了节点的位置、移动方向等特征,从而导致消息在网络中无方向性的扩散;或虽考虑了节点移动特征,但集中于时间维度,且对节点间相遇规律做了诸多假设,如节点间相遇服从独立同分布等,这些都限制了算法的实际应用场景.考虑到物联网中节点移动的空间规律性,该文在研究节点移动模型的基础上提出了节点位置信息驱动的终端缓存管理机制.在消息目的位置已知的情况下,该机制根据节点在随机移动模型和车载移动模型两种场景下位置和方向的移动特征,结合节点对网络态势的感知,分别计算消息的优先级;依据该优先级,设计节点间进行数据交换时的消息调度策略及节点缓存空间不足时的消息丢弃策略;并通过对移动方式随机(如人和动物的随机移动)和移动方式受限(如城市道路中车辆移动)两种场景的仿真结果分析,评估算法的性能表现.仿真实验表明,相比于Drop Oldest(DO)等传统缓存管理策略,该文提出的缓存管理机制在不同缓存大小和不同程度网络拥塞的情况下体现出较高的性能优势,并在提升消息投递率的同时保持了较低的平均时延、网络负载率和平均跳数.
Internet of Things(IOT),which exploits the association among the objects,the sensing devices and the Internet,achieves the automatic and real-time management,i.e.,recognition,localization,tracking,monitoring,and triggers the related events.Facing the continuous data flow collected from the monitored environment or transferred from other nodes,the mobile nodes of IOT have to conduct a large amount of data interactions.With the limited buffer size of nodes,a rational buffer management mechanism is expected to improve the delivery ratio of messages,reduce the network overhead and maintain a low level of energy cost in the nodes.However,the existing research efforts on the buffer management mechanisms,which mainly focus on the aspect of message queue features or the static attributes of messages,neglect some characteristics,e.g.,the location and moving direction of nodes.Therefore,the untargeted spread of messages,whichresults in the heavy network overhead,occurs in the network.Although some research efforts have considered the mobility pattern of the node,they mainly focus on the time dimension,e.g.,the time interval between any two contact events among nodes.Moreover,many assumptions of node contacts,e.g.,the encounter time interval among nodes follows the independent and identical distribution,result in a limited practical application scenario of the buffer management algorithms.Considering the spatial regularity of node mobility,this paper proposes a location-driven buffer management mechanism based on the analysis of different mobility models.With the knowledge of the message's destination location,the mobility characteristics of the node location-direction in both random mobility model and the vehicular mobility model are applied to calculate the priority of messages.Based on the message priority,the buffer scheduling policies,when two contacted nodes need to exchange messages with each other,and the necessary dropping policies when the buffer depletion occurs,are designed.The performance of the proposed mechanism is evaluated by organizing the simulation under both random movement scenarios,e.g.,human hold mobile devices or animal carried sensors,and the limited movement scenarios,e.g.,the taxis,buses and private cars in the urban roads.The results of simulation reveal that compared with other traditional buffer management policies,e.g.,Drop-Oldest(DO),the proposed mechanism shows a promoted performance.Under different buffer sizes and different degrees of network congestion,the proposed buffer management mechanism can improve the message delivery ratio,and reduce the average delivery latency,the network overload ratio and the average hops at the same time.
Internet of Things(IOT),which exploits the association among the objects,the sensing devices and the Internet,achieves the automatic and real-time management,i.e.,recognition,localization,tracking,monitoring,and triggers the related events.Facing the continuous data flow collected from the monitored environment or transferred from other nodes,the mobile nodes of IOT have to conduct a large amount of data interactions.With the limited buffer size of nodes,a rational buffer management mechanism is expected to improve the delivery ratio of messages,reduce the network overhead and maintain a low level of energy cost in the nodes.However,the existing research efforts on the buffer management mechanisms,which mainly focus on the aspect of message queue features or the static attributes of messages,neglect some characteristics,e.g.,the location and moving direction of nodes.Therefore,the untargeted spread of messages,whichresults in the heavy network overhead,occurs in the network.Although some research efforts have considered the mobility pattern of the node,they mainly focus on the time dimension,e.g.,the time interval between any two contact events among nodes.Moreover,many assumptions of node contacts,e.g.,the encounter time interval among nodes follows the independent and identical distribution,result in a limited practical application scenario of the buffer management algorithms.Considering the spatial regularity of node mobility,this paper proposes a location-driven buffer management mechanism based on the analysis of different mobility models.With the knowledge of the message's destination location,the mobility characteristics of the node location-direction in both random mobility model and the vehicular mobility model are applied to calculate the priority of messages.Based on the message priority,the buffer scheduling policies,when two contacted nodes need to exchange messages with each other,and the necessary dropping policies when the buffer depletion occurs,are designed.The performance of the proposed mechanism is evaluated by organizing the simulation under both random movement scenarios,e.g.,human hold mobile devices or animal carried sensors,and the limited movement scenarios,e.g.,the taxis,buses and private cars in the urban roads.The results of simulation reveal that compared with other traditional buffer management policies,e.g.,Drop-Oldest(DO),the proposed mechanism shows a promoted performance.Under different buffer sizes and different degrees of network congestion,the proposed buffer management mechanism can improve the message delivery ratio,and reduce the average delivery latency,the network overload ratio and the average hops at the same time.
引文
[1]Want R,Schilit B N,Jenson S.Enabling the Internet of Things.Computer,2015,48(1):28-35
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[3]Vahdat A,Becker D.Epidemic routing for partially-connected Ad Hoc networks.Duke University,North Carolina,USA:Technical Report CS-2000-06,2000
[4]Spyropoulos T,Psounis K,Raghavendra C S.Spray and wait:An efficient routing scheme for intermittently connected mobile networks//Proceedings of the ACM SIGCOMMWorkshop on Delay-Tolerant Networking.Philadelphia,Pennsylvania,USA,2005:252-259
[5]Lindgren A,Doria A,Schelen O.Probabilistic routing in intermittently connected networks.ACM SIGMOBILE Mobile Computing&Communications Review,2003,7(3):19-20
[6]Zhang X,Neglia G,Kurose J,et al.Performance modeling of epidemic routing//Proceedings of the International Conference on Research in Networking.Berlin,Germany,2006:827-839
[7]Falaki H,Mahajan R,Kandula S,et al.Diversity in smartphone usage//Proceedings of the International Conference on Mobile Systems,Applications,and Services.New York,USA,2010:179-194
[8]Jin L,Chen Y,Wang T,et al.Understanding user behavior in online social networks:A survey.IEEE Communications Magazine,2013,51(9):144-150
[9]Camp T,Boleng J,Davies V.A survey of mobility models for ad hoc network research.Wireless Communications&Mobile Computing,2002,2(5):483-502
[10]Zhang X,Kurose J,Levine B N,et al.Study of a bus-based disruption-tolerant network-mobility modeling and impact on routing//Proceedings of the International Conference on Mobile Computing and Networking.Montréal,Québec,Canada,2007:195-206
[11]Lindgren A,Phanse K S.Evaluation of queuing policies and forwarding strategies for routing in intermittently connected networks//Proceedings of the International Conference on Communication System Software and Middleware.New Delhi,India,2006:1-10
[12]Burgess J,Gallagher B,Jensen D,et al.MaxProp:routing for vehicle-based disruption-tolerant networks//Proceedings of the IEEE International Conference on Computer Communications.Barcelona,Spain,2007:1-11
[13]Liu Y,Wang J,Zhang S,et al.A buffer management scheme based on message transmission status in delay tolerant networks//Proceedings of the Global Telecommunications Conference.Kathmandu,Nepal,2011:1-5
[14]Wei K,Guo S,Zeng D,et al.A multi-attribute decision making approach to congestion control in delay tolerant networks//Proceedings of the IEEE International Conference on Communications.Sydney,Australia,2014:2742-2747
[15]Balasubramanian A,Levine B,Venkataramani A.DTNrouting as a resource allocation problem//Proceedings of the Conference on Applications,Technologies,Architectures,and Protocols for Computer Communications.New York,USA,2007:373-384
[16]Krifa A,Spyropoulos T,Spyropoulos T.Message drop and scheduling in DTNs:Theory and practice.IEEE Transactions on Mobile Computing,2012,11(9):1470-1483
[17]Shin K,Kim S.Enhanced buffer management policy that utilises message properties for delay-tolerant networks.IETCommunications,2011,5(6):753-759
[18]Chitti S H,Prasad N R,Ovsthus K,et al.A novel buffer management for delayed delivery traffic in future networks//Proceedings of the International Conference on Wireless Communications,Vehicular Technology,Information Theory and Aerospace&Electronics Systems.Aalborg,Denmark,2014:1-5
[19]Kaveevivitchai S,Ochiai H,Esaki H.Message deletion and mobility patterns for efficient message delivery in DTNs//Proceedings of the IEEE International Conference on Pervasive Computing and Communication Workshops.Mannheim,Germany,2010:760-763
[20]Broch J.A performance comparison of multi-hop wireless ad hoc network routing protocols//Proceedings of the ACM/IEEE International Conference on Mobile Computing and Networking.New York,USA,1998:85-97
[21]Bettstetter C.Mobility modeling in wireless networks:Categorization,smooth movement,and border effects.ACMSIGMOBILE Mobile Computing&Communications Review,2001,5(3):55-66
[22]Le T,Kalantarian H,Gerla M.A buffer management strategy based on power-law distributed contacts in delay tolerant networks//Proceedings of the International Conference on Computer Communication and Networks.Waikoloa,USA,2016:1-8
[23]Luo P,Huang H,Shu W,et al.Performance evaluation of vehicular DTN routing under realistic mobility models//Proceedings of the Wireless Communications and Networking Conference.Las Vegas,USA,2008:2206-2211
[24]Zhang L,Yu B,Pan J.GeoMob:A mobility-aware geocast scheme in metropolitans via taxicabs and buses//Proceedings of the IEEE Conference on Computer Communications.Toronto,Canada,2014:1279-1787
[25]Keranen A,Ott J,et al.The ONE simulator for DTN protocol evaluation//Proceedings of the International Conference on Simulation TOOLS and Techniques.Brussels,Belgium,2009:55
(1)UMass Diverse Outdoor Mobile Environment(DOME).http://prisms.cs.umass.deu/dome 2017,7,19
(2)MIT Media Lab:Reality Mining.http://reality.media.mit.edu 2017,7,19
(3)The Cabspotting Project.http://canspotting.org.2017,7,19
[2]Ngu A H H,Gutierrez M,Metsis V,et al.IoT Middleware:A survey on issues and enabling technologies.IEEE Internet of Things Journal,2017,4(1):1-20
[3]Vahdat A,Becker D.Epidemic routing for partially-connected Ad Hoc networks.Duke University,North Carolina,USA:Technical Report CS-2000-06,2000
[4]Spyropoulos T,Psounis K,Raghavendra C S.Spray and wait:An efficient routing scheme for intermittently connected mobile networks//Proceedings of the ACM SIGCOMMWorkshop on Delay-Tolerant Networking.Philadelphia,Pennsylvania,USA,2005:252-259
[5]Lindgren A,Doria A,Schelen O.Probabilistic routing in intermittently connected networks.ACM SIGMOBILE Mobile Computing&Communications Review,2003,7(3):19-20
[6]Zhang X,Neglia G,Kurose J,et al.Performance modeling of epidemic routing//Proceedings of the International Conference on Research in Networking.Berlin,Germany,2006:827-839
[7]Falaki H,Mahajan R,Kandula S,et al.Diversity in smartphone usage//Proceedings of the International Conference on Mobile Systems,Applications,and Services.New York,USA,2010:179-194
[8]Jin L,Chen Y,Wang T,et al.Understanding user behavior in online social networks:A survey.IEEE Communications Magazine,2013,51(9):144-150
[9]Camp T,Boleng J,Davies V.A survey of mobility models for ad hoc network research.Wireless Communications&Mobile Computing,2002,2(5):483-502
[10]Zhang X,Kurose J,Levine B N,et al.Study of a bus-based disruption-tolerant network-mobility modeling and impact on routing//Proceedings of the International Conference on Mobile Computing and Networking.Montréal,Québec,Canada,2007:195-206
[11]Lindgren A,Phanse K S.Evaluation of queuing policies and forwarding strategies for routing in intermittently connected networks//Proceedings of the International Conference on Communication System Software and Middleware.New Delhi,India,2006:1-10
[12]Burgess J,Gallagher B,Jensen D,et al.MaxProp:routing for vehicle-based disruption-tolerant networks//Proceedings of the IEEE International Conference on Computer Communications.Barcelona,Spain,2007:1-11
[13]Liu Y,Wang J,Zhang S,et al.A buffer management scheme based on message transmission status in delay tolerant networks//Proceedings of the Global Telecommunications Conference.Kathmandu,Nepal,2011:1-5
[14]Wei K,Guo S,Zeng D,et al.A multi-attribute decision making approach to congestion control in delay tolerant networks//Proceedings of the IEEE International Conference on Communications.Sydney,Australia,2014:2742-2747
[15]Balasubramanian A,Levine B,Venkataramani A.DTNrouting as a resource allocation problem//Proceedings of the Conference on Applications,Technologies,Architectures,and Protocols for Computer Communications.New York,USA,2007:373-384
[16]Krifa A,Spyropoulos T,Spyropoulos T.Message drop and scheduling in DTNs:Theory and practice.IEEE Transactions on Mobile Computing,2012,11(9):1470-1483
[17]Shin K,Kim S.Enhanced buffer management policy that utilises message properties for delay-tolerant networks.IETCommunications,2011,5(6):753-759
[18]Chitti S H,Prasad N R,Ovsthus K,et al.A novel buffer management for delayed delivery traffic in future networks//Proceedings of the International Conference on Wireless Communications,Vehicular Technology,Information Theory and Aerospace&Electronics Systems.Aalborg,Denmark,2014:1-5
[19]Kaveevivitchai S,Ochiai H,Esaki H.Message deletion and mobility patterns for efficient message delivery in DTNs//Proceedings of the IEEE International Conference on Pervasive Computing and Communication Workshops.Mannheim,Germany,2010:760-763
[20]Broch J.A performance comparison of multi-hop wireless ad hoc network routing protocols//Proceedings of the ACM/IEEE International Conference on Mobile Computing and Networking.New York,USA,1998:85-97
[21]Bettstetter C.Mobility modeling in wireless networks:Categorization,smooth movement,and border effects.ACMSIGMOBILE Mobile Computing&Communications Review,2001,5(3):55-66
[22]Le T,Kalantarian H,Gerla M.A buffer management strategy based on power-law distributed contacts in delay tolerant networks//Proceedings of the International Conference on Computer Communication and Networks.Waikoloa,USA,2016:1-8
[23]Luo P,Huang H,Shu W,et al.Performance evaluation of vehicular DTN routing under realistic mobility models//Proceedings of the Wireless Communications and Networking Conference.Las Vegas,USA,2008:2206-2211
[24]Zhang L,Yu B,Pan J.GeoMob:A mobility-aware geocast scheme in metropolitans via taxicabs and buses//Proceedings of the IEEE Conference on Computer Communications.Toronto,Canada,2014:1279-1787
[25]Keranen A,Ott J,et al.The ONE simulator for DTN protocol evaluation//Proceedings of the International Conference on Simulation TOOLS and Techniques.Brussels,Belgium,2009:55
(1)UMass Diverse Outdoor Mobile Environment(DOME).http://prisms.cs.umass.deu/dome 2017,7,19
(2)MIT Media Lab:Reality Mining.http://reality.media.mit.edu 2017,7,19
(3)The Cabspotting Project.http://canspotting.org.2017,7,19