一种基于数据聚合的传感器网络可调模型
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摘要
该文主要面向上行汇聚流量为主的传感器网络应用场景,针对现有优化方案在灵活性和计算开销等方面的问题进行了分析,包括优化目标单一、节能方法对于多重寿命标准难以适应、计算复杂度与求解近似比难以取舍、环境突变或管理需求的调整无法快速响应等等,对当前流行的传感器硬件进行了数据收发的功耗测试后,根据其射频耗能特性,以提高网络可靠性的最小化"最大链路利用率"和单纯功耗优化的最小化"网络连通支配集"为优化目标,引入加权绿色因子,建立了功耗和性能可以调节的模型RES-WSN(Reliability and Energy Steerable WSN).该模型的求解复杂度较低,当网络有数百个节点时,问题依然可以较快求解,为传感器网络提供了一种在能量消耗和可靠性及多重寿命准则间柔性调节的方案.根据该文方案求得的路由关系和数据流传输的分配结果,以"Multiple Instances"的思路和拓展选项的方式在RPL路由协议的基础上给出了部署方案.通过实验验证,该文模型对网络的可靠性的调控比例最高为52.08%,对能量消耗的调控比例最高为60.51%,特别是在仅考虑节能优化且允许部分节点死亡的情况下,网络存活时间相比只考虑可靠性的情况延长了42.54%,与近期相关研究"MinST"模型相比延长了9.23%～15.38%.
Because sensor nodes are usually powered by battery and limited in electricity,how to extend the life of nodes and the entire network is an important issue for network deployers and academics.The energy saving research of WSN is involved in all layers of the network,such as dynamic voltage scaling in hardware layer,efficient coding in link layer,reliable opportunity routing in network layer,wavelet data compression in application layer,and some also require cross layer collaboration.Focusing on the scenario of uplink traffic aggregation in the WSN,the problems of flexibility and computing overhead in existed optimization schemes are analyzed.They are,but not limited to,the singularity of purpose,the diversity of network lifetime standards and the adaptability of energy saving approaches,the tradeoff between computational complexity and accuracy,and the delayed response to the changes of environment or requirement.In this paper,the power consumption is measured of data transmit-receive on popular sensor hardware.Then,agreen factor is defined in order to propose a reliability &energy adjustable model called RES-WSN according to the RF energy characteristics.The RES-WSN model considers two mainly optimization objects,minimizing the MLU(maximum link utilization)and minimizing the connected dominating set.The former controls reliability and the latter contributes to energysaving.The model can quickly solve the problem with medium scale network over hundreds of nodes by relative low computation complexity.To the computation results of connection topology and traffic assignment,a new deployment scheme is established in the fashion of multi-instance ideas and the expansion of DIO options based on the RPL protocol but leads to small degrees of extension.The expansion requirements for the RPL protocol are mainly based on two aspects.First,the implementation of traffic allocation,and then the acquisition and maintenance of a small number of father nodes that may occur.In view of the above requirements,this paper adopts"multi-instance"method,which accords with the guiding principle of RPL protocol.The experimental results prove that scale of the reliability in the RES-WSN can be expanded to52.08%,the energy consumption 60.51%.Especially,under extreme energy saving cases,the network lifetime is 42.54%longer than the reliability optimization cases and 9.23%-15.38%longer than the model called MinST from a similar study.Further more,three typical scenarios were selected for real node experiments,that is,power consumption,green factor impact and system lifetime.The true experiments use 31 real nodes,one is Sink and the other 30 is common nodes.Every node hardware is the mini-system of TI(Texas Instruments)CC2530.The code of hibernation control is revised and information acquisition part is adding for the suitability.The system energy consumption of the maximum case was only 52.5% of the high reliability,which was similar to the simulation results.When the green factor is minimum and some nodes are allowed to die,the network lifetime of RES-WSN is 15.38%longer than MinST,which is more significant than the simulation experiment(9.23%).
Because sensor nodes are usually powered by battery and limited in electricity,how to extend the life of nodes and the entire network is an important issue for network deployers and academics.The energy saving research of WSN is involved in all layers of the network,such as dynamic voltage scaling in hardware layer,efficient coding in link layer,reliable opportunity routing in network layer,wavelet data compression in application layer,and some also require cross layer collaboration.Focusing on the scenario of uplink traffic aggregation in the WSN,the problems of flexibility and computing overhead in existed optimization schemes are analyzed.They are,but not limited to,the singularity of purpose,the diversity of network lifetime standards and the adaptability of energy saving approaches,the tradeoff between computational complexity and accuracy,and the delayed response to the changes of environment or requirement.In this paper,the power consumption is measured of data transmit-receive on popular sensor hardware.Then,agreen factor is defined in order to propose a reliability &energy adjustable model called RES-WSN according to the RF energy characteristics.The RES-WSN model considers two mainly optimization objects,minimizing the MLU(maximum link utilization)and minimizing the connected dominating set.The former controls reliability and the latter contributes to energysaving.The model can quickly solve the problem with medium scale network over hundreds of nodes by relative low computation complexity.To the computation results of connection topology and traffic assignment,a new deployment scheme is established in the fashion of multi-instance ideas and the expansion of DIO options based on the RPL protocol but leads to small degrees of extension.The expansion requirements for the RPL protocol are mainly based on two aspects.First,the implementation of traffic allocation,and then the acquisition and maintenance of a small number of father nodes that may occur.In view of the above requirements,this paper adopts"multi-instance"method,which accords with the guiding principle of RPL protocol.The experimental results prove that scale of the reliability in the RES-WSN can be expanded to52.08%,the energy consumption 60.51%.Especially,under extreme energy saving cases,the network lifetime is 42.54%longer than the reliability optimization cases and 9.23%-15.38%longer than the model called MinST from a similar study.Further more,three typical scenarios were selected for real node experiments,that is,power consumption,green factor impact and system lifetime.The true experiments use 31 real nodes,one is Sink and the other 30 is common nodes.Every node hardware is the mini-system of TI(Texas Instruments)CC2530.The code of hibernation control is revised and information acquisition part is adding for the suitability.The system energy consumption of the maximum case was only 52.5% of the high reliability,which was similar to the simulation results.When the green factor is minimum and some nodes are allowed to die,the network lifetime of RES-WSN is 15.38%longer than MinST,which is more significant than the simulation experiment(9.23%).
引文
[1]Winter T,Thubert P,Hui J,et al.RPL:IPv6routing protocol for low-power and lossy networks.RFC 6550,2012
[2]Khalil I M,Khreishah A,Ahmed F,Shuaib K.Dependable wireless sensor networks for reliable and secure humanitarian relief applications.Ad Hoc Networks,2014,13:94-106
[3]Werner-Allen G,Johnson J,Ruiz M,et al.Monitoring volcanic eruptions with a wireless sensor network//Proceedings of the Second European Workshop on Wireless Sensor.Istanbul,Turkey,2005:108-120
[4]Dietrich I,Dressler F.On the lifetime of wireless sensor networks.ACM Transactions on Sensor Networks,2009,5(1):1-39
[5]Shao Xing,Wang Cui-Xiang,Rao Yuan.Research on cross layer network coding aware energy efficient routing for wireless sensor network.Acta Electronica Sinica,2015,43(12):2484-2490(in Chinese)(邵星,王翠香,饶元.基于跨层网络编码感知的无线传感器网络节能路由算法研究.电子学报,2015,43(12):2484-2490)
[6]Liu Tao,Li Tian-Rui,Tan Wen-Rong,Yin Feng.Distributed data sinking mechanism based on joint optimization in wireless sensor networks.Journal on Communications,2015,36(7):18-30(in Chinese)(刘韬,李天瑞,谈文蓉,殷锋.基于分布式与联合优化的无线传感器网络数据汇聚机制.通信学报,2015,36(7):18-30)
[7]Shah M,Grabocka J,Schilling N,et al.Learning DTW-shapelets for time-series classification//Proceedings of the IKDD Conference on Data Science.Pune,India,2016:1-8
[8]Ferjani A A,Liouane N,Kacem I.Task allocation for wireless sensor network using logic gate-based evolutionary algorithm//Proceedings of the CoDIT’16.Saint Julian’s,Malta,2016:654-658
[9]Sun Li-Juan,Wei Jing,Guo Jian,et al.Node scheduling algorithm for heterogeneous wireless sensor networks.Acta Electronica Sinica,2014,42(10):1907-1912(in Chinese)(孙力娟,魏静,郭剑等.面向异构无线传感器网络的节点调度算法.电子学报,2014,42(10):1907-1912)
[10]Wei Z,Keong N G W.Prolonging lifespan of sensor networks using redundant nodes.Ad Hoc and Sensor Wireless Networks,2013,19(1):1-19
[11]Latif K,Javaid N,Saqib M N,et al.Energy consumption model for density controlled divide-and-rule cheme forenergy efficient routing in wireless sensor networks.International Journal of Ad Hoc and Ubiquitous Computing,2016,21(2):130-139
[12]Nuruzzaman M T,Ferng H W.A low energy consumption routing protocol for mobile sensor networks with a pathconstrained mobile sink//Proceedings of the 2016 IEEEInternational Conference on Communications.Kuala Lumpur,Malaysia,2016:1-6
[13]Zhao M,Yang Y.Bounded relay hop mobile data gathering in wireless sensor networks.IEEE Transactions on Computers,2010,61(2):373-382
[14]Restuccia F,Das S K.Optimizing the lifetime of sensor networks with uncontrollable mobile sinks and QoS constraints.ACM Transactions on Sensor Networks,2016,12(1):1-31
[15]Habibi J,Aghdam A G,Ghrayeb A.A framework for evaluating the best achievable performance by distributed lifetime-efficient routing schemes in wireless sensor networks.IEEE Transactions on Wireless Communications,2015,14(6):3231-3246
[16]Berber S,Fang S.Systems and methods for power efficient data communications in wireless sensor networks.Auckland,NZ2012/000030,2012
[17]Zhu Y,Xu J,Li E,Xu L.Energy-efficient reliable data gathering scheme based on Enhanced Reed-Solomon code for wireless sensor networks//Proceedings of the International Conference on Smart Computing.Hong Kong,China,2014:275-280
[18]Francois F,Wang N,Moessner K,Georgoulas S.Optimizing link sleeping reconfigurations in ISP networks with off-peak time failure protection.IEEE Transactions on Network and Service Management,2013,10(2):176-188
[19]Liu J,Xu H,Zhou A.Beamforming design for energy efficiency maximization in miso channels.The Institute of Electronics,Information and Communication Engineers,2016,E99.B(5):1189-1195
[20]Yazdanpanah M,Assi C,Shayan Y.Optimal joint routing and scheduling in wireless mesh networks with smart antennas//Proceeding of the 11th IEEE International Symposium on“a World of Wireless Mobile and Multimedia Networks”(WOWMOM).Montreal,Canada,2010:1-7
[21]Shafigh A S,Lorenzo B,Glisic S,et al.A framework for dynamic network architecture and topology optimization.Transactions on Networking,2016,24(2):717-730
[22]Tian Y,Boangoat J,Ekici E,et al.Real-time task mapping and scheduling for collaborative in-network processing in DVS-enabled wireless sensor networks//Proceedings of the20th International Conference on Parallel and Distributed Processing.Rhodes Island,Greece,2006:25
[23]Liu Dan,Zhou Qian,Zhang Zhi,Liu Baoling.Cluster-based energy-efficient transmission using a new hybrid compressed sensing in WSN//Proceedings of the INFOCOM WKSHPS.San Francisco,USA,2016:372-376
[24]Liu Anfeng,Jin Xin,Cui Guohua,Chen Zhigang.Deployment guidelines for achieving maximum lifetime and avoiding energy holes in sensor network.Information Sciences,2013,230(1):197-226
[25]Halder S,DasBit S.Design of a probability density function targeting energy-efficient node deployment in wireless sensor networks.IEEE Transactions on Network and Service Management,2014,11(2):204-219
[26]Yan J,Zhou M,Ding Z.Recent advances in energy-efficient routing protocols for wireless sensor networks:A review.IEEE Access,2016,10(4):5673-5686
[27]Jabbar S,Minhas A A,Rashid T,Rho S.Heuristic approach for stagnation free energy aware routing in wireless sensor networks.Ad Hoc&Sensor Wireless Networks,2016,31(2):21-45
[28]Zhou Z,Du C,Shu L,Hancke G.An energy-balanced heuristic for mobile sink scheduling in hybrid WSNs.IEEETransactions on Industrial Informatics,2016,12(1):28-40
[29]Imon S K A,Khan A,Francesco M D,Das S K.Energyefficient randomized switching for maximizing lifetime in treebased wireless sensor networks.IEEE/ACM Transactions on Networking,2015,23(5):1401-1415
[30]Laouid A,Dahmani A,Bounceur A,et al.A distributed multi-path routing algorithm to balance energy consumption in wireless sensor networks.Ad Hoc Networks,2017,64:53-64
[31]Hu Xiaoqing,Hu Yu Hen,Xu Bugong.Energy-balanced scheduling for target tracking in wireless sensor networks.ACM Transactions on Sensor Networks,2014,11(1):1-29
[32]Alhalafi A,Sboui L,Naous R,Shihada B.gTBS:A green task-based sensing for energy efficient wireless sensor networks//Proceedings of the INFOCOM WKSHPS.San Francisco,USA,2016:136-143
[33]Liu A F,Jin X,Cui G H,Chen Z G.Deployment guidelines for achieving maximum lifetime and avoiding energy holes in sensor network.Information Sciences,2013,230(1):197-226
[34]Liu An-Feng,Ren Ju,Xu Juan,et al.Analysis and avoidance of energy hole problem in heterogeneous wireless sensor networks.Journal of Software,2012,23(9):2438-2448(in Chinese)(刘安丰,任炬,徐娟等.异构传感器网络能量空洞分析与避免研究.软件学报,2012,23(9):2438-2448)
[35]Halde S,Bit S D.Enhancement of wireless sensor network lifetime by deploying heterogeneous nodes.Journal of Network and Computer Applications,2014,38(1):106-124
[36]Fan Gao-Juan,Wang Ru-Chuan,Huang Hai-Ping,Sun Li-Juan.Tolerable coverage area based node scheduling algorithm in wireless sensor networks.Acta Electronica Sinica,2011,39(1):89-94(in Chinese)(凡高娟,王汝传,黄海平,孙力娟.基于容忍覆盖区域的无线传感器网络节点调度算法.电子学报,2011,39(1):89-94)
[37]Layout R F,Kit C C D.A true system-on-chip solution for2.4-GHz IEEE 802.15.4and ZigBee applications.USA:Texas Instruments,DATASHEET:SWRU191B,2010
[38]Shan Mengfan,Chen Guihai,Luo Dijun.Building maximum lifetime shortest path data aggregation trees in wireless sensor networks.ACM Transactions on Sensor Networks,2014,11(1):1-24
[39]Applegate D,Cohen E.Making intra-domain routing robust to changing and uncertain traffic demands:Understanding fundamental tradeoffs//Proceedings of the ACM SIGCOMM.Karlsruhe,Germany,2003:313-324
[40]Madan R,Cui S,Lall S,Goldsmith A.Cross-layer design for lifetime maximization in interference-limited wireless sensor networks//Proceedings of the 24th IEEE Conference on Computer Communications(INFOCOM).Miami,USA,2005:1964-1975
[41]Hellman K,Colagrosso M.Investigating a wireless sensor network optimal lifetime solution for linear topologies.Journal of Interconnection Networks,2006,7(1):91-99
[42]Candes E J,Tao T.Decoding by linear programming.IEEETransactions on Information Theory,2005,51(12):4203-4215
[43]Bandeira A S,Dobriban E,Mixon D G,Sawin W F.Certifying the restricted isometry property is hard.IEEE Transactions on Information Theory,2013,59(2):3448-3450
[44]Candès E J,Wakin M B,Boyd S P.Enhancing sparsity by reweighted l1 minimization.Journal of Fourier Analysis&Applications,2007,14(5):877-905
[45]Xiao Rong,Chen Wen-Long,Sun Bo.Light weight and tree-based forwarding model in IPv6IoT subnet.Journal of Software,2014,25(8):1729-1742(in Chinese)(肖融,陈文龙,孙波.面向IPv6物联子网的轻量级树型转发模型.软件学报,2014,25(8):1729-1742)
[46]Chen Wenlong,Zheng Zhe,Xiao Rong,et al.HRVN:Ahighly reliable forwarding model based on virtual nodes in node-intensive WSNs.International Journal of Distributed Sensor Networks,2015,11(3):1-12
[2]Khalil I M,Khreishah A,Ahmed F,Shuaib K.Dependable wireless sensor networks for reliable and secure humanitarian relief applications.Ad Hoc Networks,2014,13:94-106
[3]Werner-Allen G,Johnson J,Ruiz M,et al.Monitoring volcanic eruptions with a wireless sensor network//Proceedings of the Second European Workshop on Wireless Sensor.Istanbul,Turkey,2005:108-120
[4]Dietrich I,Dressler F.On the lifetime of wireless sensor networks.ACM Transactions on Sensor Networks,2009,5(1):1-39
[5]Shao Xing,Wang Cui-Xiang,Rao Yuan.Research on cross layer network coding aware energy efficient routing for wireless sensor network.Acta Electronica Sinica,2015,43(12):2484-2490(in Chinese)(邵星,王翠香,饶元.基于跨层网络编码感知的无线传感器网络节能路由算法研究.电子学报,2015,43(12):2484-2490)
[6]Liu Tao,Li Tian-Rui,Tan Wen-Rong,Yin Feng.Distributed data sinking mechanism based on joint optimization in wireless sensor networks.Journal on Communications,2015,36(7):18-30(in Chinese)(刘韬,李天瑞,谈文蓉,殷锋.基于分布式与联合优化的无线传感器网络数据汇聚机制.通信学报,2015,36(7):18-30)
[7]Shah M,Grabocka J,Schilling N,et al.Learning DTW-shapelets for time-series classification//Proceedings of the IKDD Conference on Data Science.Pune,India,2016:1-8
[8]Ferjani A A,Liouane N,Kacem I.Task allocation for wireless sensor network using logic gate-based evolutionary algorithm//Proceedings of the CoDIT’16.Saint Julian’s,Malta,2016:654-658
[9]Sun Li-Juan,Wei Jing,Guo Jian,et al.Node scheduling algorithm for heterogeneous wireless sensor networks.Acta Electronica Sinica,2014,42(10):1907-1912(in Chinese)(孙力娟,魏静,郭剑等.面向异构无线传感器网络的节点调度算法.电子学报,2014,42(10):1907-1912)
[10]Wei Z,Keong N G W.Prolonging lifespan of sensor networks using redundant nodes.Ad Hoc and Sensor Wireless Networks,2013,19(1):1-19
[11]Latif K,Javaid N,Saqib M N,et al.Energy consumption model for density controlled divide-and-rule cheme forenergy efficient routing in wireless sensor networks.International Journal of Ad Hoc and Ubiquitous Computing,2016,21(2):130-139
[12]Nuruzzaman M T,Ferng H W.A low energy consumption routing protocol for mobile sensor networks with a pathconstrained mobile sink//Proceedings of the 2016 IEEEInternational Conference on Communications.Kuala Lumpur,Malaysia,2016:1-6
[13]Zhao M,Yang Y.Bounded relay hop mobile data gathering in wireless sensor networks.IEEE Transactions on Computers,2010,61(2):373-382
[14]Restuccia F,Das S K.Optimizing the lifetime of sensor networks with uncontrollable mobile sinks and QoS constraints.ACM Transactions on Sensor Networks,2016,12(1):1-31
[15]Habibi J,Aghdam A G,Ghrayeb A.A framework for evaluating the best achievable performance by distributed lifetime-efficient routing schemes in wireless sensor networks.IEEE Transactions on Wireless Communications,2015,14(6):3231-3246
[16]Berber S,Fang S.Systems and methods for power efficient data communications in wireless sensor networks.Auckland,NZ2012/000030,2012
[17]Zhu Y,Xu J,Li E,Xu L.Energy-efficient reliable data gathering scheme based on Enhanced Reed-Solomon code for wireless sensor networks//Proceedings of the International Conference on Smart Computing.Hong Kong,China,2014:275-280
[18]Francois F,Wang N,Moessner K,Georgoulas S.Optimizing link sleeping reconfigurations in ISP networks with off-peak time failure protection.IEEE Transactions on Network and Service Management,2013,10(2):176-188
[19]Liu J,Xu H,Zhou A.Beamforming design for energy efficiency maximization in miso channels.The Institute of Electronics,Information and Communication Engineers,2016,E99.B(5):1189-1195
[20]Yazdanpanah M,Assi C,Shayan Y.Optimal joint routing and scheduling in wireless mesh networks with smart antennas//Proceeding of the 11th IEEE International Symposium on“a World of Wireless Mobile and Multimedia Networks”(WOWMOM).Montreal,Canada,2010:1-7
[21]Shafigh A S,Lorenzo B,Glisic S,et al.A framework for dynamic network architecture and topology optimization.Transactions on Networking,2016,24(2):717-730
[22]Tian Y,Boangoat J,Ekici E,et al.Real-time task mapping and scheduling for collaborative in-network processing in DVS-enabled wireless sensor networks//Proceedings of the20th International Conference on Parallel and Distributed Processing.Rhodes Island,Greece,2006:25
[23]Liu Dan,Zhou Qian,Zhang Zhi,Liu Baoling.Cluster-based energy-efficient transmission using a new hybrid compressed sensing in WSN//Proceedings of the INFOCOM WKSHPS.San Francisco,USA,2016:372-376
[24]Liu Anfeng,Jin Xin,Cui Guohua,Chen Zhigang.Deployment guidelines for achieving maximum lifetime and avoiding energy holes in sensor network.Information Sciences,2013,230(1):197-226
[25]Halder S,DasBit S.Design of a probability density function targeting energy-efficient node deployment in wireless sensor networks.IEEE Transactions on Network and Service Management,2014,11(2):204-219
[26]Yan J,Zhou M,Ding Z.Recent advances in energy-efficient routing protocols for wireless sensor networks:A review.IEEE Access,2016,10(4):5673-5686
[27]Jabbar S,Minhas A A,Rashid T,Rho S.Heuristic approach for stagnation free energy aware routing in wireless sensor networks.Ad Hoc&Sensor Wireless Networks,2016,31(2):21-45
[28]Zhou Z,Du C,Shu L,Hancke G.An energy-balanced heuristic for mobile sink scheduling in hybrid WSNs.IEEETransactions on Industrial Informatics,2016,12(1):28-40
[29]Imon S K A,Khan A,Francesco M D,Das S K.Energyefficient randomized switching for maximizing lifetime in treebased wireless sensor networks.IEEE/ACM Transactions on Networking,2015,23(5):1401-1415
[30]Laouid A,Dahmani A,Bounceur A,et al.A distributed multi-path routing algorithm to balance energy consumption in wireless sensor networks.Ad Hoc Networks,2017,64:53-64
[31]Hu Xiaoqing,Hu Yu Hen,Xu Bugong.Energy-balanced scheduling for target tracking in wireless sensor networks.ACM Transactions on Sensor Networks,2014,11(1):1-29
[32]Alhalafi A,Sboui L,Naous R,Shihada B.gTBS:A green task-based sensing for energy efficient wireless sensor networks//Proceedings of the INFOCOM WKSHPS.San Francisco,USA,2016:136-143
[33]Liu A F,Jin X,Cui G H,Chen Z G.Deployment guidelines for achieving maximum lifetime and avoiding energy holes in sensor network.Information Sciences,2013,230(1):197-226
[34]Liu An-Feng,Ren Ju,Xu Juan,et al.Analysis and avoidance of energy hole problem in heterogeneous wireless sensor networks.Journal of Software,2012,23(9):2438-2448(in Chinese)(刘安丰,任炬,徐娟等.异构传感器网络能量空洞分析与避免研究.软件学报,2012,23(9):2438-2448)
[35]Halde S,Bit S D.Enhancement of wireless sensor network lifetime by deploying heterogeneous nodes.Journal of Network and Computer Applications,2014,38(1):106-124
[36]Fan Gao-Juan,Wang Ru-Chuan,Huang Hai-Ping,Sun Li-Juan.Tolerable coverage area based node scheduling algorithm in wireless sensor networks.Acta Electronica Sinica,2011,39(1):89-94(in Chinese)(凡高娟,王汝传,黄海平,孙力娟.基于容忍覆盖区域的无线传感器网络节点调度算法.电子学报,2011,39(1):89-94)
[37]Layout R F,Kit C C D.A true system-on-chip solution for2.4-GHz IEEE 802.15.4and ZigBee applications.USA:Texas Instruments,DATASHEET:SWRU191B,2010
[38]Shan Mengfan,Chen Guihai,Luo Dijun.Building maximum lifetime shortest path data aggregation trees in wireless sensor networks.ACM Transactions on Sensor Networks,2014,11(1):1-24
[39]Applegate D,Cohen E.Making intra-domain routing robust to changing and uncertain traffic demands:Understanding fundamental tradeoffs//Proceedings of the ACM SIGCOMM.Karlsruhe,Germany,2003:313-324
[40]Madan R,Cui S,Lall S,Goldsmith A.Cross-layer design for lifetime maximization in interference-limited wireless sensor networks//Proceedings of the 24th IEEE Conference on Computer Communications(INFOCOM).Miami,USA,2005:1964-1975
[41]Hellman K,Colagrosso M.Investigating a wireless sensor network optimal lifetime solution for linear topologies.Journal of Interconnection Networks,2006,7(1):91-99
[42]Candes E J,Tao T.Decoding by linear programming.IEEETransactions on Information Theory,2005,51(12):4203-4215
[43]Bandeira A S,Dobriban E,Mixon D G,Sawin W F.Certifying the restricted isometry property is hard.IEEE Transactions on Information Theory,2013,59(2):3448-3450
[44]Candès E J,Wakin M B,Boyd S P.Enhancing sparsity by reweighted l1 minimization.Journal of Fourier Analysis&Applications,2007,14(5):877-905
[45]Xiao Rong,Chen Wen-Long,Sun Bo.Light weight and tree-based forwarding model in IPv6IoT subnet.Journal of Software,2014,25(8):1729-1742(in Chinese)(肖融,陈文龙,孙波.面向IPv6物联子网的轻量级树型转发模型.软件学报,2014,25(8):1729-1742)
[46]Chen Wenlong,Zheng Zhe,Xiao Rong,et al.HRVN:Ahighly reliable forwarding model based on virtual nodes in node-intensive WSNs.International Journal of Distributed Sensor Networks,2015,11(3):1-12