随机化数据冗余方法及其在存储系统中的应用
|
摘要
利用网络分布式存储系统存储大数据已成为数据存储技术的发展趋势。网络分布式存储系统通常由数量众多的存储节点构成，由于人为或自然灾难的不可避免性，或是存储节点本身的低可靠性，常常会发生部分存储节点损坏或是无法及时使用的情况。而这一旦发生，存储其中的重要数据就会丢失或是不可用，造成极大的损失。因此，为了保证存储数据的安全性和可靠性，将数据冗余方法引入网络分布式存储系统成为一种必然。
已有的数据冗余方法，如基于复制的数据冗余方法，基于阵列码的数据冗余方法等均存在种种不足，或者是存储冗余度过高，或者是容错能力有限，无法满足网络环境下分布式存储系统的需求。针对这一问题，本文首次以随机矩阵理论为基础，提出了一类新的数据冗余方法，称之为随机化数据冗余方法，并研究了其在两类具体的网络分布式存储环境——分布式数据容灾存储和传感器网络数据存储环境下的应用。本文的主要研究成果包括以下几个方面：
1．提出了性能优异的随机化数据冗余方法。
容错能力高、存储冗余度低、运算速度快、修复带宽低是网络环境下的分布式存储系统对数据冗余方法的需求。现有的数据冗余方法往往无法同时满足这些需求。本文以二元域上的随机矩阵为基础，提出了一类新的能满足上述需求的随机化数据冗余方法，给出了详细的文件存储、读取、以及修复算法。在本文提出的随机化数据冗余方法中：由源文件得到冗余文件、由冗余文件恢复出源文件均基于构造好的随机矩阵完成；随机矩阵满秩的高概率性质保证了冗余方法的高容错能力和低存储冗余度；同时，源文件和冗余文件之间的转换只依靠异或运算进行，降低了计算复杂度，提高了文件的处理速度；另外，随机矩阵的稀疏性也使得修复丢失的部分冗余文件数据所需的修复带宽有效降低；
2．提出了基于随机化数据冗余方法的低冗余度数据容灾方案。
数据容灾方案是网络分布式数据容灾存储系统抵御大规模存储节点损毁，保证数据生存能力的有效手段。传统的容灾方案通常以复制冗余方法为基础，以高存储空间代价换取一定的容灾能力。本文在随机化数据冗余方法的基础上，提出了一类具有低存储冗余度的数据容灾方案。与复制容灾方案相比，本文方案在提供相同容灾能力的前提下，可将系统的存储空间代价降到近似的理论最小值。本文方案的可行性和有效性在相关实验中得到了验证。
3．以随机化数据冗余方法为基础，提出了适用于无人值守传感器网络的具有低通信成本和低访问成本的分布式存储算法。
无人值守传感器网络可以看作是一类没有路由表的特殊网络分布式存储系统，其目的在于感知数据并将感知到的数据可靠地存储在整个网络中。本文以随机化数据冗余方法为基础，并与定向随机游走机制相结合，提出了适用于无人值守传感器网络的分布式存储算法。采用本文算法：可以有效地将网络中k个数据节点感知到的k个源数据包存储到网络所有的n个节点中（n> k），形成n个存储数据包。当存储过程完成之后，即使有部分节点损坏而导致存储其中的存储数据包丢失，用户也能通过从任意k+12个以上未损坏节点的存储数据包还原出原来的k个源数据包。与具有代表性的基于LT码的算法相比，本文算法将存储过程中每个源数据包在网络中的通信次数从约nlnn降到了约n；同时，本文算法也将存储完成之后，用户为获取源数据包而需要访问网络节点的个数从大于k+100降到了约k+12。本文算法的可行性和有效性在数值实验中得到了验证。
Large scale network distributed storage systems are foreseen as a way to providehighly reliable data storage with low cost. To ensure high durability and high resilienceover a long period of time, the network distributed storage system must add redundancyto the original data. Existing data redundancy methods such as replication based methodand array code based method have many deficiencies such as higher storage redundancy,limited fault tolerance and so on. These deficiencies result that they are unable to meetthe needs of distributed storage systems in the network environment.
To solve these problems, a new random data redundancy method based on randommatrix theory is proposed. The applications of proposed method in different networkstorage environments are also explored.
The main contributions of this dissertation are as follows:
1. A new random data redundancy method with high performance is proposed.
The random matrix’s probability of full rank is studied. Based on the random matrixwith high probability of full rank, the process of new random data redundancy methodis explored. The detailed data storage, recovery and repair algorithm of random dataredundancy method are given. The property of random matrix’s high probability of fullrank make the fault tolerance of proposed method is higher and the storage redundancyis lower. The operation of data’s storage, recovery and repair is only based on XORoperation, this makes the computational complexity of proposed method is lower.Furthermore, the sparsity of random matrix makes the repair bandwidth of proposedmethod is lower.
2. A new disaster recovery scheme based on proposed random data redundancymethod for disaster recovery systems is proposed.
Disaster recovery scheme is adopted by disaster recovery systems to against thedamage of large-scale storage nodes. Traditional disaster recovery schemes are usuallybased on data replication tecnology. In this dissertation, based on random dataredundancy method, a new disaster recovery scheme with low storage space cost isproposed. Compared with traditional replication based scheme, the proposed scheme can provide the lowest consumption of storage space when the disaster recoveryparameter is given. The feasibility and effectiveness of the proposed scheme has beenverified in the actual disaster recovery storage platform.
3. Distributed data storage algorithms with low communication cost and low dataquery cost for unattended wireless sensor networks are proposed based on random dataredundancy method.
Unattended wireless sensor network (UWSN) is a special distributed storage systemwith no routing table, which is used to sense and store data. In this dissertation, reliabledistributed data storage algorithms for UWSN based on random data redundancy anddirectional random walk rule are proposed. Using the proposed algorithms, k sourcedata packets generated by k data node is stored distributedly into the n node in thenetwork (n> k) and every node eventually stores a stored data packet. After the storageprocess is completed, even if there is loss of part of the stored data packets, the user canalso recover all the data packets from any k+12survived stored data packets.Compared with the representative LT code-based algorithm, the proposed algorithmsreduce the communication time of every data packet in storage process from about nlnnto about n. At the same time, the proposed algorithms also reduce the query time ofstored data packets form about k+100to about k+12. The feasibility and effectivenessof the proposed algorithms have been verified by numerical experiments.
已有的数据冗余方法，如基于复制的数据冗余方法，基于阵列码的数据冗余方法等均存在种种不足，或者是存储冗余度过高，或者是容错能力有限，无法满足网络环境下分布式存储系统的需求。针对这一问题，本文首次以随机矩阵理论为基础，提出了一类新的数据冗余方法，称之为随机化数据冗余方法，并研究了其在两类具体的网络分布式存储环境——分布式数据容灾存储和传感器网络数据存储环境下的应用。本文的主要研究成果包括以下几个方面：
1．提出了性能优异的随机化数据冗余方法。
容错能力高、存储冗余度低、运算速度快、修复带宽低是网络环境下的分布式存储系统对数据冗余方法的需求。现有的数据冗余方法往往无法同时满足这些需求。本文以二元域上的随机矩阵为基础，提出了一类新的能满足上述需求的随机化数据冗余方法，给出了详细的文件存储、读取、以及修复算法。在本文提出的随机化数据冗余方法中：由源文件得到冗余文件、由冗余文件恢复出源文件均基于构造好的随机矩阵完成；随机矩阵满秩的高概率性质保证了冗余方法的高容错能力和低存储冗余度；同时，源文件和冗余文件之间的转换只依靠异或运算进行，降低了计算复杂度，提高了文件的处理速度；另外，随机矩阵的稀疏性也使得修复丢失的部分冗余文件数据所需的修复带宽有效降低；
2．提出了基于随机化数据冗余方法的低冗余度数据容灾方案。
数据容灾方案是网络分布式数据容灾存储系统抵御大规模存储节点损毁，保证数据生存能力的有效手段。传统的容灾方案通常以复制冗余方法为基础，以高存储空间代价换取一定的容灾能力。本文在随机化数据冗余方法的基础上，提出了一类具有低存储冗余度的数据容灾方案。与复制容灾方案相比，本文方案在提供相同容灾能力的前提下，可将系统的存储空间代价降到近似的理论最小值。本文方案的可行性和有效性在相关实验中得到了验证。
3．以随机化数据冗余方法为基础，提出了适用于无人值守传感器网络的具有低通信成本和低访问成本的分布式存储算法。
无人值守传感器网络可以看作是一类没有路由表的特殊网络分布式存储系统，其目的在于感知数据并将感知到的数据可靠地存储在整个网络中。本文以随机化数据冗余方法为基础，并与定向随机游走机制相结合，提出了适用于无人值守传感器网络的分布式存储算法。采用本文算法：可以有效地将网络中k个数据节点感知到的k个源数据包存储到网络所有的n个节点中（n> k），形成n个存储数据包。当存储过程完成之后，即使有部分节点损坏而导致存储其中的存储数据包丢失，用户也能通过从任意k+12个以上未损坏节点的存储数据包还原出原来的k个源数据包。与具有代表性的基于LT码的算法相比，本文算法将存储过程中每个源数据包在网络中的通信次数从约nlnn降到了约n；同时，本文算法也将存储完成之后，用户为获取源数据包而需要访问网络节点的个数从大于k+100降到了约k+12。本文算法的可行性和有效性在数值实验中得到了验证。
Large scale network distributed storage systems are foreseen as a way to providehighly reliable data storage with low cost. To ensure high durability and high resilienceover a long period of time, the network distributed storage system must add redundancyto the original data. Existing data redundancy methods such as replication based methodand array code based method have many deficiencies such as higher storage redundancy,limited fault tolerance and so on. These deficiencies result that they are unable to meetthe needs of distributed storage systems in the network environment.
To solve these problems, a new random data redundancy method based on randommatrix theory is proposed. The applications of proposed method in different networkstorage environments are also explored.
The main contributions of this dissertation are as follows:
1. A new random data redundancy method with high performance is proposed.
The random matrix’s probability of full rank is studied. Based on the random matrixwith high probability of full rank, the process of new random data redundancy methodis explored. The detailed data storage, recovery and repair algorithm of random dataredundancy method are given. The property of random matrix’s high probability of fullrank make the fault tolerance of proposed method is higher and the storage redundancyis lower. The operation of data’s storage, recovery and repair is only based on XORoperation, this makes the computational complexity of proposed method is lower.Furthermore, the sparsity of random matrix makes the repair bandwidth of proposedmethod is lower.
2. A new disaster recovery scheme based on proposed random data redundancymethod for disaster recovery systems is proposed.
Disaster recovery scheme is adopted by disaster recovery systems to against thedamage of large-scale storage nodes. Traditional disaster recovery schemes are usuallybased on data replication tecnology. In this dissertation, based on random dataredundancy method, a new disaster recovery scheme with low storage space cost isproposed. Compared with traditional replication based scheme, the proposed scheme can provide the lowest consumption of storage space when the disaster recoveryparameter is given. The feasibility and effectiveness of the proposed scheme has beenverified in the actual disaster recovery storage platform.
3. Distributed data storage algorithms with low communication cost and low dataquery cost for unattended wireless sensor networks are proposed based on random dataredundancy method.
Unattended wireless sensor network (UWSN) is a special distributed storage systemwith no routing table, which is used to sense and store data. In this dissertation, reliabledistributed data storage algorithms for UWSN based on random data redundancy anddirectional random walk rule are proposed. Using the proposed algorithms, k sourcedata packets generated by k data node is stored distributedly into the n node in thenetwork (n> k) and every node eventually stores a stored data packet. After the storageprocess is completed, even if there is loss of part of the stored data packets, the user canalso recover all the data packets from any k+12survived stored data packets.Compared with the representative LT code-based algorithm, the proposed algorithmsreduce the communication time of every data packet in storage process from about nlnnto about n. At the same time, the proposed algorithms also reduce the query time ofstored data packets form about k+100to about k+12. The feasibility and effectivenessof the proposed algorithms have been verified by numerical experiments.
引文
[1]施建.华为:大数据与大未来[N].21世纪经济报道,2012年12月29日
[2] J. Gantz, D. Reinsel. The digital universe decade–are you ready?[R]. Framingham, MA:International Data Corporation, July16,2010
[3] J. Gantz. The diverse and exploding digital universe: An updated forecast of worldwideinformation growth through2011[R]. Framingham, MA: International Data Corporation, July20,2008
[4]罗英伟,汪小林,尹冬生,等.信息存储与管理[M].北京:人民邮电出版社,2010,48-58
[5] J. Hennessy, D. Patterson.计算机系统结构——量化研究方法(第四版)[M].北京:电子工业出版社,2010,248-297
[6]岳明.工信部明确云计算攻关重点：分布式存储与虚拟化技术[EB/OL].http://www.c114.net/news/16/a714741.html,2012年9月6日
[7]王意洁,孙伟东,周松,等.云计算环境下的分布式存储关键技术[J].软件学报,2012,23(4):962-986
[8]罗象宏,舒继武.存储系统中的纠删码研究综述[J].计算机研究与发展,2012,49(1):1-11
[9] S. Ghemawat, H. Gobioff, S. Leung. The Google file system[C]. In Proceedings of the9th ACMSymposium on Operating Systems Principles, New York,2003,29-43
[10]刘鹏云.计算（第二版）[M].北京:电子工业出版社,2011,1-7
[11] S. Rhea, C. Wells, P. Eaton, et al. Maintenance-free global data storage[J]. IEEE InternetComputing,2001,5(5):40-49
[12] R. Bhagwan, K. Tati, Y. Cheng, et al. Total Recall: system support for automated availabilitymanagement[C], In Proceedings of USENIX Symposium on Networked Systems Design andImplementation, New York,2004,337-350.
[13] A. Haeberlen, A. Mislove, P. Druschel. Glacier: highly durable, decentralized storage despitemassive correlated failures[C]. In Proceedings of USENIX Symposium on Networked SystemsDesign and Implementation, New York,2005,143-158
[14] D. A. Patterson, G. Gibson, R. H. Katz. A case for redundant arrays of inexpensive disks[C]. InProceedings of ACM International Conference on Management of Data, New York,1988,109-116
[15]敖青云.存储技术原理分析[M].北京:电子工业出版社,2011,22-36
[16] K. Shvachko, H. Kuang, S. Radia, et al. The Hadoop distributed file system[C]. In Proceedingsof the26th IEEE Symposium on Massive Storage Systems and Technologies, Washington, DC,2010,1-10
[17] G. DeCandia, D. Hastorun, M. Jampani, et al. Dynamo: Amazon’s highly available key-valuestore[C]. In Proceedings of the21st ACM SIGOPS Symposium on Operating SystemsPrinciples, New York,2007,205-220
[18] Z. Zhang, A. Deshpande, X. Ma, et al. Does erasure coding have a role to play in my datacenter?[R]. Redmond, WA: Microsoft Corporation, July13,2010
[19] M. Blaum, J. Brady, J. Bruck, et al. EVENODD: An efficient scheme for tolerating double diskfailures in RAID architectures[J]. IEEE Transactions on Computers,1995,45(2):192-202
[20] C. Huang, L. Xu. STAR: An efficient coding scheme for correcting triple storage nodefailures[J]. IEEE Transactions on Computers,2008,57(7):889-901
[21] M. Li, J. Su, W. Zheng. Grid Codes: Strip-based erasure codes with high fault tolerance forstorage systems[J]. ACM Transactions on Storage,2009,4(4):15:1-15:22
[22] L. Xu, J. Bruck. X-code: MDS array codes with optimal encoding[J]. IEEE Transactions onInformation Theory,1999,45(1):272-276
[23] P. Corbett, B. English, A. Goel, et al. Row-diagonal redundant for double disk failurecorrection[C]. In Proceedings of the3rd USENIX Conference on File and Storage Technologies,Berkeley, CA,2004,2-15
[24] J. Plank, A. Buchsbaum, T. Bradley, et al. Minimum density RAID-6codes[J]. ACMTransactions on Storage,2011,6(4):16-37
[25]万武南,吴震,陈运,等.一种基于3容错阵列码的RAID数据布局[J].计算机学报,2007,30(10):1721-1730
[26] L. Xu, V. Bohossian, J. Bruck, et al. Low density MDS codes and factors of complete graphs[J].IEEE Transaction on Information Theory,1999,45(6):1817-1826
[27] N. K. Lee, S. B. Yang, K. W. Lee. Efficient parity placement schemes for tolerating up to twodisks failures in disk arrays[J]. Journal of Systems Architecture,2000,46(15):1383-1402
[28] J. Plank. The RAID-6liberation codes[C]. In Proceedings of the6th USENIX Conference onFile and Storage Technologies, Berkeley, CA,2008,97-110
[29] J. Plank. The RAID-6Liber8tion code[J]. International Journal of High PerformanceComputing Applications,2009,23(3):242-251
[30] G. Feng, R. H. Deng, F. Bao, et al. New efficient MDS array codes for RAID Part I:Reed-Solomon-like codes for tolerating three disk failures[J]. IEEE Transaction on Computers,2005,54(9):1071-1080
[31] Y. Cassuto, J. Bruck. Cyclic lowest density MDS array codes[J]. IEEE Transaction onInformation Theory,2009,55(4):1721-1729
[32] M. Li, J. Shu. On cyclic lowest density MDS array codes constructed using starters[C]. InProceedings of2010IEEE International Symp on Information Theory. Piscataway,2010,1315-1319
[33] J. Hafner. WEAVER codes: highly fault tolerant erasure codes for storage systems[C]. InProceedings of the4th conference on USENIX Conference on File and Storage Technologies,San Francisco,2005,6-16
[34] J. L. Hafner. HoVer erasure codes for disk arrays[C]. In Proceedings of2006InternationalConference on Dependable Systems and Networks, Piscataway,2010,217-226
[35] G. Feng, R. H. Deng, F. Bao, et al. New efficient MDS array codes for RAID Part II: Rabin-likecodes for tolerating multiple (≥4) failures[J]. IEEE Transaction on Computers,2005,54(12):1473-1483
[36] A. Thusoo, D. Borthakur, R. Murthy, et al. Data warehousing and analytics infrastructure atFacebook[C]. In Proceedings of SIGMOD2010, New York,2010,1013-1020
[37] S. Reed, G. Solomon. Polynomial codes over certain finite fields[J]. Journal of the Society forIndustrial and Applied Mathematics,1960,8(2):300-304
[38] M. Rabin. Efficient dispersal of information for security loading balancing and fault tolerance[J]. Journal of the Association for Computing Machinery,1989,36(2):335-348
[39] Y. Chen, J. Edler, A. Goldberg, et al. A prototype implementation of archival intermemory[C].In Proceedings of the4th ACM conference on Digital libraries, New York,1999,28-37
[40] J. Plank. A tutorial on Reed-Solomon coding for fault-tolerance in RAID-like systems[J].Software-Practice and Experience,1997,27(9):995-1012
[41] J. Plank, Y. Ding. Note: Correction to the1997tutorial on Reed-Solomon coding[J].Software-Practice and Experience,2005,35(2):189-194
[42] R. M. Roth, A. Lempel. On MDS codes via Cauchy Matrices[J]. IEEE Transaction onInformation Theory,1989,35(6),1314-1319
[43] J. Blomer, M. Kalfane, M. Karpinski, et al. An XOR-based erasure-resilient coding scheme[R].Berkeley, California: International Computer Science Institute, August20,1995
[44] J. Plank, L. Xu. Optimizing Cauchy Reed-Solomon codes for fault-tolerant network storageapplications[C]. In Proceedings of IEEE International Symposium on Network Computing andApplications, Cambridge,2006,173-180
[45] J. Plank, C. Schuman, B. Robison. Heuristics for optimizing matrix-based erasure codes forfault-tolerant storage systems[C]. In Proceedings of IEEE/IFIP International Conference onDependable Systems and Networks, Boston,2012,1-12
[46] B. Calder, J. Wang, A. Ogus et al. Windows Azure storage: A highly available cloud storageservice with strong consistency[C]. In Proceedings of the23rd ACM Symposium on OperatingSystems Principles, New York,2011,143-157
[47] R. Gallager. Low-density parity-check codes[J]. IEEE Transaction on Information Theory,1962,8(1):21-28
[48] M. Luby, M. Mitzenmacher, A. Shokrollahi et al. Efficient erasure correcting codes[J]. IEEETransaction on Information Theory,2001,47(2):569-584
[49]王意洁,卢锡城.基于TORNADO码的复制算法[J].国防科技大学学报,2004,26(3):39-42
[50] B. Gaidioz, B. Koblitz, N. Santos. Exploring high performance distributed file storage usingLDPC codes[J]. Parallel Computing,2007,33(2):264-274
[51] J. Plank, M. Thomason. On the practical use of LDPC codes for distributed storageapplications[C]. In Proceedings of Dependable Systems and Networks, Florenct,2004,115-214
[52] J. Plank, A. Buchsbaum, R. Collins, et al. Small parity-check erasure codes-exploration andobservations[C]. In Proceedings of Dependable Systems and Networks, Yokohama,2005,326-335
[53] M. Luby. LT codes[C]. In Proceedings of IEEE Symposium on Foundations of ComputerScience, New York,2002,271-280
[54] J. Cooley, J. Mineweaser, L. Servi, et al. Software-based erasure codes for scalable distributedstorage[C]. In Proceedings of Mass Storage Systems and Technologies, New York,2003,157-164
[55] H. Xia, A. Chien, RobuSTore: Robust performance for distributed storage systems[C]. InProceedings of Supercomputing2007, New York,2007,1-11,2007
[56] A. Dimakis, P. Godfrey, J. Wainwright, et al. Network coding for distributed storage systems
[C]. In Proceedings of the26th IEEE International Conference on Computer Communications,Anchorage, Alaska,2007,2000-2008
[57]徐俊明.图论及其应用(第二版)[M].合肥:北京中国科学技术大学出版社,2005,125-128
[58]叶中行.信息论基础(第二版)[M].北京:高等教育出版社,2007,192-202
[59] A. Dimakis, P. Godfrey, Y. Wu, et al. Network coding for distributed storage systems[J]. IEEETransactions on Information Theory,2010,56(9):4539-4551
[60] A. Dimakis, K. Ramchandran, Y. Wu, et al. A survey on network codes for distributed storage[J].Proceedings of the IEEE,2011,99(3):476-489
[61]常乾,许胤龙,项利萍,等.基于EVENODD码的单盘故障快速恢复算法[J].计算机应用与软件,2011,28(6):15-18
[62] L. Xiang, Y. Xu, J. C. S. Lui, et al. Optimal recovery of single disk failure in RDP code storagesystems[J]. ACM SIGMETRICS Performance Evaluation Review,2010,38(1):119–130
[63] O. Khan, R. Burn, J. Plank, et al. Rethinking erasure codes for cloud file systems: minimizingI/O for recovery and degraded reads[C]. In Proceedings of the10th USENIX Conference onFile and Storage Technologies, New York,2012,2-15
[64] Z. Wang, A. G. Dimakis, J. Bruck. Rebuilding for Array Codes in Distributed StorageSystems[C]. In Proceedings of Workshop on the Application of Communication Theory toEmerging Memory Technologies, New York,2010,1-7
[65] W. J. Bolosky, J. R. Douceur, D. Ely, et al. Feasibility of a serverless distributed file systemdeployed on an existing set of desktop PCs[J]. ACM SIGMETRICS Performance EvaluationRevies,2000,28(1):34-43
[66] J. M. Busca, F. Picconi, P. Sens. Pastis: A highly-scalable multi-user peet-to-peer file system[C].In Proceedings of the11th European Conference on Parallel, Lisbon, Portugal,2005,1173-1182
[67] F. Dabek, M. F. Kaashoek, D. Karger, et al. Wide-area cooperative storage with CFS[C]. InProceedings of ACM Symposium on Operating Systems Principles, Canada,2001,205-215
[68] I. Stoica, R. Morris, D. Karger, et al. Chord: A scalable peer-to-peer lookup service for internetapplications[J]. IEEE ACM Transactions on Networking,2003,11(1):17-31
[69] Z. Zhang, Q. Lian, S. Lin, et al. Bitvault: a highly reliable distributed data retention platform[J].ACM SIGOPS Operating Systems Review,2007,41(2):27-36
[70] C. Cooper. On the rank of random matrices[J]. Random Structures and Algorithms,2000,16(2):209-232
[71] C. Cooper. On the distribution of rank of a random matrix over a finite field[J]. RandomStructures and Algorithms,2000,17(3-4):197-212
[72]冯克勤.纠错码的代数理论[M].北京:清华大学出版社,2005,14-22
[73]万哲先.代数和编码[M].北京:高等教育出版社,2007,201-234
[74] S. Lin, D. J. Costello.差错控制编码[M].北京:机械工业出版社,2007,44-62
[75] R. Bhagwan, D. Moore, S. Savage et al. Replication strategies for highly available peer-to-peerstorage[R]. San Diego: University of California at San Diego, September10,2002
[76] B. Chun, F. Dabek, A. Haeberlen, et al. Efficient replica maintenance for distributed storagesystems[C]. In Proceedings of USENIX Symposium on Networked Systems Design andImplementation, New York,2006,1-14
[77] J. Tian and Y. Dai. Understanding the dynamic of peer-to-peer systems[C]. In Proceedings ofInternational Workshop on Peer-to-Peer Systems, New York,2007,11-17
[78] R. Bhagwan, D. Moore, S. Savage, et al Replication strategies for highly available peer-to-peerstorage[J]. Lecture Notes in Computer Science,2003,2584:153-158
[79] S. Nath, H. Yu, P. B. Gibbons, et al. Subtleties in tolerating correlated failures in wide-areastorage systems[C]. In Proceedings of USENIX Symposium on Networked Systems Design andImplementation, New York,2006,225-238
[80] T. S. J. Schwarz, E. L. Miller. Using algebraic signatures to check remotely administeredstorage[C]. In Proceedings of IEEE International Conference on Distributed ComputingSystems, New York,2006,71-82
[81] N. Oualha, M. Onen, Y. Roudier. A security protocol for self-organizing data storage[C]. InProceedings of International Information Security Conference, Milano, Italy,2008,675-679
[82] A. Datta, K. Aberer. Internet-scale storage systems under churn-a study of the steady-state usingmarkov models[C]. In Proceedings of IEEE International Conference on Peer-to-PeerComputing, Cambriage, UK,2006,133-144
[83] A. Duminuco, E. Biersack, T. En-Najjary. Proactive replication in distributed storage systemsusing machine availability estimation[C]. In Proceedings of ACM Conference on EmergingNetworking Experiments and Technologies, New York,2007,60-66
[84] B. Schroeder, G. Gibson. Disk failures in the real world: What does an MTTF of1000000meanto you?[C]. In Proceedings of the5th USENIX Conference on File and Storage Technologies,Berkeley, CA,2007,1-16
[85] E. Pinheiro, W. D. Weber, L. A. Barroso. Failure trends in a large disk drive population[C]. InProceedings of the5th USENIX Conference on File and Storage Technologies, Berkeley, CA,2007,17-28
[86]姚文斌,伍淳华.中国灾备标准和产业发展现状[J].中兴通讯技术,2010,16(5):1-4
[87]杨义先,姚文斌,陈钊.信息系统灾备技术综论[J].北京邮电大学学报,2010,33(2):1-6
[88]徐恒.中国容灾市场势头强劲—软件与服务唱主角[N].中国电子报,2009-03-27
[89] W. Zheng, B. Fang. Structure-independent disaster recovery: concept, architecture andimplementations[J]. Science in China, Series F: Information Sciences,2009,52(2):813-823
[90]田敬,代亚非. P2P持久存储研究[J].软件学报,2007,18(6):1379-1399
[91] G.Somasundaram, A. Shrivastava.信息存储与管理——数字信息的存储、管理和保护[M].北京:人民邮电出版社,2010,168-185
[92]王改性,师若鸣,扈彩艳,等.数据存储备份与灾难恢复[M].北京:电子工业出版社,2009,233-258
[93]高建秀,吴振新,孙硕.云存储在数字资源长期保存中的应用探讨[J].现代图书情报技术,2010,6(2):1-6
[94]金文新.高校图书馆存储系统的构建及其数据安全和备份方案研究[J].情报资料工作,2009,1(10):40-43
[95]陈臣.面向分散式存储的数字图书馆云存储方案研究[J].新世纪图书馆,2012,13(12):65-68
[96]万武南.分布式安全存储系统纠删码技术的研究[D].北京:中国科学院研究生院,2006,97-105
[97]陈峥.一类新的阵列纠删码理论及应用研究[D].北京:中国科学院研究生院,2009,43-56
[98]张永成.一种高性能数据容灾系统的关键技术研究[D].北京:中国科学院研究生院,2009,97-105
[99]方佳嘉.感官信息秘密分享技术及其应用研究[D].北京:中国科学院研究生院,2012,109-118
[100]王晓京,方佳嘉,蔡红亮,王一丁,等.视图的秘密分享及其代数编码方法[J].计算机应用,2012,32(3):669-678
[101]蔚赵春,周永庚,关佶红.无线传感器网络中数据存储与访问研究进展[J].电子学报,2008,36(10):2001-2010
[102]梁小满,马行坡.无线传感器网络数据存储技术研究进展[J].计算机应用研究,2009,26(2):439-443
[103]张希伟,戴海鹏,徐力杰,等.无线传感器网络中移动协助的数据收集策略研究[J].软件学报,2012,23(12):1-17
[104]任伟,任毅,张慧,等.无人值守无线传感器网络中一种安全高效的数据存活策略[J].计算机研究与发展,2009,46(12):2093-2100
[105] Z. Kong, S. A. Aly, E. Soljanin. Decentralized coding algorithms for distributed storage inwireless sensor networks[J]. IEEE Journal on Selected Areas in Communications,2010,28(2):261-267
[106]李挺,冯勇.无线传感器网络的安全路由研究[J].计算机应用研究,2012,29(12):4412-4419
[107] D. Vitali, A. Spognardi, A. Villani, et al. Replication schemes in unattended wireless sensornetworks[C]. In Proceedings of the4th IFIP International Conference on New Technologies,Mobility and Security, Paris,2011,1-5
[108] T. K. Madsen, A. Grauballe, M. G. Jensen, et al. Reliable cooperative information storage inwireless sensor networks[C]. In Proceedings of IEEE International Conference onTelecommunications, Petersburg,2008,1-6
[109] S. A. Aly, Z. Kong, E. Soljanin. Raptor codes based distributed storage algorithms for wirelesssensor networks[C]. In Proceedings of IEEE International Symposium on Information Theory,Toronto,2008,2051-2055
[110] S. Jafarizadeh, Jamalipour. Distributed data storage in large-scale sensor networks based on LTcodes[EB/OL]. http://arxiv.org/ftp/arxiv/papers/1201/1201.4479.pdf, December31,2012
[111] S. A. Aly, Z. Kong, E. Soljanin. Fountain codes based distributed storage alogorithms forlarge-scale wireless sensor networks[C]. In Proceedings of the7th IEEE InternationalConference on Information in Sensor Networks, Louis,2008,171-182
[112] C. Cooper, A. Frieze. The cover time of random geometric graphs[J]. Random Structures andAlgorithms,2011,38(3):324-349
[113] L. Tzevelekas, K. Oikonomou, I. Stavrakakis. Random walk with jumps in large-scale randomgeometric graphs[J]. Computer Communications,2010,33(13):1505-1514
[114] C. Avin, B. Krishnamachari. The power of choice in random walks: An empirical study[J].Computer Networks,2008,52(1):44-60
[115] C. Avin, B. Krishnamachari. The power of choice in random walks: An empirical study[C]. InProceedings of the9th ACM International Symposium on Modeling Analysis and Simulation ofWireless and Mobile Systems, New York,2006,219-228
[116] A. Shokrollahi. Raptor Codes[J]. IEEE Transactions on Information Theory,2006,52(6):2551-2567
[117] Z. Zhu, S. Liu, J. Zhang, et al. Performance analysis of LT codes with different degreedistribution[C]. In Proceedings of the5th International Workshop on Chaos-fractals Theoriesand Applications, Dalian, Liaoning, China,2012,142-146
[118] N. Alon, C. Avin, M. Koucky, et al. Many random walks are faster than one[C]. In Proceedingsof the20th Annual ACM Symposium on Parallel Algorithms and Architectures, New York,2008,119-128
[119] N. Alon, C. Avin, M. Koucky, et al. Many random walks are faster than one[J]. Combinatorics,Probability and Computing,2011,20(4):481-502
[120] C. Cooper, A. Frieze, T. Radzik. Multiple random walks in random regular graphs[J]. SIAMJournal on Discrete Mathematics,2009,23(4):1738-1761
[2] J. Gantz, D. Reinsel. The digital universe decade–are you ready?[R]. Framingham, MA:International Data Corporation, July16,2010
[3] J. Gantz. The diverse and exploding digital universe: An updated forecast of worldwideinformation growth through2011[R]. Framingham, MA: International Data Corporation, July20,2008
[4]罗英伟,汪小林,尹冬生,等.信息存储与管理[M].北京:人民邮电出版社,2010,48-58
[5] J. Hennessy, D. Patterson.计算机系统结构——量化研究方法(第四版)[M].北京:电子工业出版社,2010,248-297
[6]岳明.工信部明确云计算攻关重点：分布式存储与虚拟化技术[EB/OL].http://www.c114.net/news/16/a714741.html,2012年9月6日
[7]王意洁,孙伟东,周松,等.云计算环境下的分布式存储关键技术[J].软件学报,2012,23(4):962-986
[8]罗象宏,舒继武.存储系统中的纠删码研究综述[J].计算机研究与发展,2012,49(1):1-11
[9] S. Ghemawat, H. Gobioff, S. Leung. The Google file system[C]. In Proceedings of the9th ACMSymposium on Operating Systems Principles, New York,2003,29-43
[10]刘鹏云.计算（第二版）[M].北京:电子工业出版社,2011,1-7
[11] S. Rhea, C. Wells, P. Eaton, et al. Maintenance-free global data storage[J]. IEEE InternetComputing,2001,5(5):40-49
[12] R. Bhagwan, K. Tati, Y. Cheng, et al. Total Recall: system support for automated availabilitymanagement[C], In Proceedings of USENIX Symposium on Networked Systems Design andImplementation, New York,2004,337-350.
[13] A. Haeberlen, A. Mislove, P. Druschel. Glacier: highly durable, decentralized storage despitemassive correlated failures[C]. In Proceedings of USENIX Symposium on Networked SystemsDesign and Implementation, New York,2005,143-158
[14] D. A. Patterson, G. Gibson, R. H. Katz. A case for redundant arrays of inexpensive disks[C]. InProceedings of ACM International Conference on Management of Data, New York,1988,109-116
[15]敖青云.存储技术原理分析[M].北京:电子工业出版社,2011,22-36
[16] K. Shvachko, H. Kuang, S. Radia, et al. The Hadoop distributed file system[C]. In Proceedingsof the26th IEEE Symposium on Massive Storage Systems and Technologies, Washington, DC,2010,1-10
[17] G. DeCandia, D. Hastorun, M. Jampani, et al. Dynamo: Amazon’s highly available key-valuestore[C]. In Proceedings of the21st ACM SIGOPS Symposium on Operating SystemsPrinciples, New York,2007,205-220
[18] Z. Zhang, A. Deshpande, X. Ma, et al. Does erasure coding have a role to play in my datacenter?[R]. Redmond, WA: Microsoft Corporation, July13,2010
[19] M. Blaum, J. Brady, J. Bruck, et al. EVENODD: An efficient scheme for tolerating double diskfailures in RAID architectures[J]. IEEE Transactions on Computers,1995,45(2):192-202
[20] C. Huang, L. Xu. STAR: An efficient coding scheme for correcting triple storage nodefailures[J]. IEEE Transactions on Computers,2008,57(7):889-901
[21] M. Li, J. Su, W. Zheng. Grid Codes: Strip-based erasure codes with high fault tolerance forstorage systems[J]. ACM Transactions on Storage,2009,4(4):15:1-15:22
[22] L. Xu, J. Bruck. X-code: MDS array codes with optimal encoding[J]. IEEE Transactions onInformation Theory,1999,45(1):272-276
[23] P. Corbett, B. English, A. Goel, et al. Row-diagonal redundant for double disk failurecorrection[C]. In Proceedings of the3rd USENIX Conference on File and Storage Technologies,Berkeley, CA,2004,2-15
[24] J. Plank, A. Buchsbaum, T. Bradley, et al. Minimum density RAID-6codes[J]. ACMTransactions on Storage,2011,6(4):16-37
[25]万武南,吴震,陈运,等.一种基于3容错阵列码的RAID数据布局[J].计算机学报,2007,30(10):1721-1730
[26] L. Xu, V. Bohossian, J. Bruck, et al. Low density MDS codes and factors of complete graphs[J].IEEE Transaction on Information Theory,1999,45(6):1817-1826
[27] N. K. Lee, S. B. Yang, K. W. Lee. Efficient parity placement schemes for tolerating up to twodisks failures in disk arrays[J]. Journal of Systems Architecture,2000,46(15):1383-1402
[28] J. Plank. The RAID-6liberation codes[C]. In Proceedings of the6th USENIX Conference onFile and Storage Technologies, Berkeley, CA,2008,97-110
[29] J. Plank. The RAID-6Liber8tion code[J]. International Journal of High PerformanceComputing Applications,2009,23(3):242-251
[30] G. Feng, R. H. Deng, F. Bao, et al. New efficient MDS array codes for RAID Part I:Reed-Solomon-like codes for tolerating three disk failures[J]. IEEE Transaction on Computers,2005,54(9):1071-1080
[31] Y. Cassuto, J. Bruck. Cyclic lowest density MDS array codes[J]. IEEE Transaction onInformation Theory,2009,55(4):1721-1729
[32] M. Li, J. Shu. On cyclic lowest density MDS array codes constructed using starters[C]. InProceedings of2010IEEE International Symp on Information Theory. Piscataway,2010,1315-1319
[33] J. Hafner. WEAVER codes: highly fault tolerant erasure codes for storage systems[C]. InProceedings of the4th conference on USENIX Conference on File and Storage Technologies,San Francisco,2005,6-16
[34] J. L. Hafner. HoVer erasure codes for disk arrays[C]. In Proceedings of2006InternationalConference on Dependable Systems and Networks, Piscataway,2010,217-226
[35] G. Feng, R. H. Deng, F. Bao, et al. New efficient MDS array codes for RAID Part II: Rabin-likecodes for tolerating multiple (≥4) failures[J]. IEEE Transaction on Computers,2005,54(12):1473-1483
[36] A. Thusoo, D. Borthakur, R. Murthy, et al. Data warehousing and analytics infrastructure atFacebook[C]. In Proceedings of SIGMOD2010, New York,2010,1013-1020
[37] S. Reed, G. Solomon. Polynomial codes over certain finite fields[J]. Journal of the Society forIndustrial and Applied Mathematics,1960,8(2):300-304
[38] M. Rabin. Efficient dispersal of information for security loading balancing and fault tolerance[J]. Journal of the Association for Computing Machinery,1989,36(2):335-348
[39] Y. Chen, J. Edler, A. Goldberg, et al. A prototype implementation of archival intermemory[C].In Proceedings of the4th ACM conference on Digital libraries, New York,1999,28-37
[40] J. Plank. A tutorial on Reed-Solomon coding for fault-tolerance in RAID-like systems[J].Software-Practice and Experience,1997,27(9):995-1012
[41] J. Plank, Y. Ding. Note: Correction to the1997tutorial on Reed-Solomon coding[J].Software-Practice and Experience,2005,35(2):189-194
[42] R. M. Roth, A. Lempel. On MDS codes via Cauchy Matrices[J]. IEEE Transaction onInformation Theory,1989,35(6),1314-1319
[43] J. Blomer, M. Kalfane, M. Karpinski, et al. An XOR-based erasure-resilient coding scheme[R].Berkeley, California: International Computer Science Institute, August20,1995
[44] J. Plank, L. Xu. Optimizing Cauchy Reed-Solomon codes for fault-tolerant network storageapplications[C]. In Proceedings of IEEE International Symposium on Network Computing andApplications, Cambridge,2006,173-180
[45] J. Plank, C. Schuman, B. Robison. Heuristics for optimizing matrix-based erasure codes forfault-tolerant storage systems[C]. In Proceedings of IEEE/IFIP International Conference onDependable Systems and Networks, Boston,2012,1-12
[46] B. Calder, J. Wang, A. Ogus et al. Windows Azure storage: A highly available cloud storageservice with strong consistency[C]. In Proceedings of the23rd ACM Symposium on OperatingSystems Principles, New York,2011,143-157
[47] R. Gallager. Low-density parity-check codes[J]. IEEE Transaction on Information Theory,1962,8(1):21-28
[48] M. Luby, M. Mitzenmacher, A. Shokrollahi et al. Efficient erasure correcting codes[J]. IEEETransaction on Information Theory,2001,47(2):569-584
[49]王意洁,卢锡城.基于TORNADO码的复制算法[J].国防科技大学学报,2004,26(3):39-42
[50] B. Gaidioz, B. Koblitz, N. Santos. Exploring high performance distributed file storage usingLDPC codes[J]. Parallel Computing,2007,33(2):264-274
[51] J. Plank, M. Thomason. On the practical use of LDPC codes for distributed storageapplications[C]. In Proceedings of Dependable Systems and Networks, Florenct,2004,115-214
[52] J. Plank, A. Buchsbaum, R. Collins, et al. Small parity-check erasure codes-exploration andobservations[C]. In Proceedings of Dependable Systems and Networks, Yokohama,2005,326-335
[53] M. Luby. LT codes[C]. In Proceedings of IEEE Symposium on Foundations of ComputerScience, New York,2002,271-280
[54] J. Cooley, J. Mineweaser, L. Servi, et al. Software-based erasure codes for scalable distributedstorage[C]. In Proceedings of Mass Storage Systems and Technologies, New York,2003,157-164
[55] H. Xia, A. Chien, RobuSTore: Robust performance for distributed storage systems[C]. InProceedings of Supercomputing2007, New York,2007,1-11,2007
[56] A. Dimakis, P. Godfrey, J. Wainwright, et al. Network coding for distributed storage systems
[C]. In Proceedings of the26th IEEE International Conference on Computer Communications,Anchorage, Alaska,2007,2000-2008
[57]徐俊明.图论及其应用(第二版)[M].合肥:北京中国科学技术大学出版社,2005,125-128
[58]叶中行.信息论基础(第二版)[M].北京:高等教育出版社,2007,192-202
[59] A. Dimakis, P. Godfrey, Y. Wu, et al. Network coding for distributed storage systems[J]. IEEETransactions on Information Theory,2010,56(9):4539-4551
[60] A. Dimakis, K. Ramchandran, Y. Wu, et al. A survey on network codes for distributed storage[J].Proceedings of the IEEE,2011,99(3):476-489
[61]常乾,许胤龙,项利萍,等.基于EVENODD码的单盘故障快速恢复算法[J].计算机应用与软件,2011,28(6):15-18
[62] L. Xiang, Y. Xu, J. C. S. Lui, et al. Optimal recovery of single disk failure in RDP code storagesystems[J]. ACM SIGMETRICS Performance Evaluation Review,2010,38(1):119–130
[63] O. Khan, R. Burn, J. Plank, et al. Rethinking erasure codes for cloud file systems: minimizingI/O for recovery and degraded reads[C]. In Proceedings of the10th USENIX Conference onFile and Storage Technologies, New York,2012,2-15
[64] Z. Wang, A. G. Dimakis, J. Bruck. Rebuilding for Array Codes in Distributed StorageSystems[C]. In Proceedings of Workshop on the Application of Communication Theory toEmerging Memory Technologies, New York,2010,1-7
[65] W. J. Bolosky, J. R. Douceur, D. Ely, et al. Feasibility of a serverless distributed file systemdeployed on an existing set of desktop PCs[J]. ACM SIGMETRICS Performance EvaluationRevies,2000,28(1):34-43
[66] J. M. Busca, F. Picconi, P. Sens. Pastis: A highly-scalable multi-user peet-to-peer file system[C].In Proceedings of the11th European Conference on Parallel, Lisbon, Portugal,2005,1173-1182
[67] F. Dabek, M. F. Kaashoek, D. Karger, et al. Wide-area cooperative storage with CFS[C]. InProceedings of ACM Symposium on Operating Systems Principles, Canada,2001,205-215
[68] I. Stoica, R. Morris, D. Karger, et al. Chord: A scalable peer-to-peer lookup service for internetapplications[J]. IEEE ACM Transactions on Networking,2003,11(1):17-31
[69] Z. Zhang, Q. Lian, S. Lin, et al. Bitvault: a highly reliable distributed data retention platform[J].ACM SIGOPS Operating Systems Review,2007,41(2):27-36
[70] C. Cooper. On the rank of random matrices[J]. Random Structures and Algorithms,2000,16(2):209-232
[71] C. Cooper. On the distribution of rank of a random matrix over a finite field[J]. RandomStructures and Algorithms,2000,17(3-4):197-212
[72]冯克勤.纠错码的代数理论[M].北京:清华大学出版社,2005,14-22
[73]万哲先.代数和编码[M].北京:高等教育出版社,2007,201-234
[74] S. Lin, D. J. Costello.差错控制编码[M].北京:机械工业出版社,2007,44-62
[75] R. Bhagwan, D. Moore, S. Savage et al. Replication strategies for highly available peer-to-peerstorage[R]. San Diego: University of California at San Diego, September10,2002
[76] B. Chun, F. Dabek, A. Haeberlen, et al. Efficient replica maintenance for distributed storagesystems[C]. In Proceedings of USENIX Symposium on Networked Systems Design andImplementation, New York,2006,1-14
[77] J. Tian and Y. Dai. Understanding the dynamic of peer-to-peer systems[C]. In Proceedings ofInternational Workshop on Peer-to-Peer Systems, New York,2007,11-17
[78] R. Bhagwan, D. Moore, S. Savage, et al Replication strategies for highly available peer-to-peerstorage[J]. Lecture Notes in Computer Science,2003,2584:153-158
[79] S. Nath, H. Yu, P. B. Gibbons, et al. Subtleties in tolerating correlated failures in wide-areastorage systems[C]. In Proceedings of USENIX Symposium on Networked Systems Design andImplementation, New York,2006,225-238
[80] T. S. J. Schwarz, E. L. Miller. Using algebraic signatures to check remotely administeredstorage[C]. In Proceedings of IEEE International Conference on Distributed ComputingSystems, New York,2006,71-82
[81] N. Oualha, M. Onen, Y. Roudier. A security protocol for self-organizing data storage[C]. InProceedings of International Information Security Conference, Milano, Italy,2008,675-679
[82] A. Datta, K. Aberer. Internet-scale storage systems under churn-a study of the steady-state usingmarkov models[C]. In Proceedings of IEEE International Conference on Peer-to-PeerComputing, Cambriage, UK,2006,133-144
[83] A. Duminuco, E. Biersack, T. En-Najjary. Proactive replication in distributed storage systemsusing machine availability estimation[C]. In Proceedings of ACM Conference on EmergingNetworking Experiments and Technologies, New York,2007,60-66
[84] B. Schroeder, G. Gibson. Disk failures in the real world: What does an MTTF of1000000meanto you?[C]. In Proceedings of the5th USENIX Conference on File and Storage Technologies,Berkeley, CA,2007,1-16
[85] E. Pinheiro, W. D. Weber, L. A. Barroso. Failure trends in a large disk drive population[C]. InProceedings of the5th USENIX Conference on File and Storage Technologies, Berkeley, CA,2007,17-28
[86]姚文斌,伍淳华.中国灾备标准和产业发展现状[J].中兴通讯技术,2010,16(5):1-4
[87]杨义先,姚文斌,陈钊.信息系统灾备技术综论[J].北京邮电大学学报,2010,33(2):1-6
[88]徐恒.中国容灾市场势头强劲—软件与服务唱主角[N].中国电子报,2009-03-27
[89] W. Zheng, B. Fang. Structure-independent disaster recovery: concept, architecture andimplementations[J]. Science in China, Series F: Information Sciences,2009,52(2):813-823
[90]田敬,代亚非. P2P持久存储研究[J].软件学报,2007,18(6):1379-1399
[91] G.Somasundaram, A. Shrivastava.信息存储与管理——数字信息的存储、管理和保护[M].北京:人民邮电出版社,2010,168-185
[92]王改性,师若鸣,扈彩艳,等.数据存储备份与灾难恢复[M].北京:电子工业出版社,2009,233-258
[93]高建秀,吴振新,孙硕.云存储在数字资源长期保存中的应用探讨[J].现代图书情报技术,2010,6(2):1-6
[94]金文新.高校图书馆存储系统的构建及其数据安全和备份方案研究[J].情报资料工作,2009,1(10):40-43
[95]陈臣.面向分散式存储的数字图书馆云存储方案研究[J].新世纪图书馆,2012,13(12):65-68
[96]万武南.分布式安全存储系统纠删码技术的研究[D].北京:中国科学院研究生院,2006,97-105
[97]陈峥.一类新的阵列纠删码理论及应用研究[D].北京:中国科学院研究生院,2009,43-56
[98]张永成.一种高性能数据容灾系统的关键技术研究[D].北京:中国科学院研究生院,2009,97-105
[99]方佳嘉.感官信息秘密分享技术及其应用研究[D].北京:中国科学院研究生院,2012,109-118
[100]王晓京,方佳嘉,蔡红亮,王一丁,等.视图的秘密分享及其代数编码方法[J].计算机应用,2012,32(3):669-678
[101]蔚赵春,周永庚,关佶红.无线传感器网络中数据存储与访问研究进展[J].电子学报,2008,36(10):2001-2010
[102]梁小满,马行坡.无线传感器网络数据存储技术研究进展[J].计算机应用研究,2009,26(2):439-443
[103]张希伟,戴海鹏,徐力杰,等.无线传感器网络中移动协助的数据收集策略研究[J].软件学报,2012,23(12):1-17
[104]任伟,任毅,张慧,等.无人值守无线传感器网络中一种安全高效的数据存活策略[J].计算机研究与发展,2009,46(12):2093-2100
[105] Z. Kong, S. A. Aly, E. Soljanin. Decentralized coding algorithms for distributed storage inwireless sensor networks[J]. IEEE Journal on Selected Areas in Communications,2010,28(2):261-267
[106]李挺,冯勇.无线传感器网络的安全路由研究[J].计算机应用研究,2012,29(12):4412-4419
[107] D. Vitali, A. Spognardi, A. Villani, et al. Replication schemes in unattended wireless sensornetworks[C]. In Proceedings of the4th IFIP International Conference on New Technologies,Mobility and Security, Paris,2011,1-5
[108] T. K. Madsen, A. Grauballe, M. G. Jensen, et al. Reliable cooperative information storage inwireless sensor networks[C]. In Proceedings of IEEE International Conference onTelecommunications, Petersburg,2008,1-6
[109] S. A. Aly, Z. Kong, E. Soljanin. Raptor codes based distributed storage algorithms for wirelesssensor networks[C]. In Proceedings of IEEE International Symposium on Information Theory,Toronto,2008,2051-2055
[110] S. Jafarizadeh, Jamalipour. Distributed data storage in large-scale sensor networks based on LTcodes[EB/OL]. http://arxiv.org/ftp/arxiv/papers/1201/1201.4479.pdf, December31,2012
[111] S. A. Aly, Z. Kong, E. Soljanin. Fountain codes based distributed storage alogorithms forlarge-scale wireless sensor networks[C]. In Proceedings of the7th IEEE InternationalConference on Information in Sensor Networks, Louis,2008,171-182
[112] C. Cooper, A. Frieze. The cover time of random geometric graphs[J]. Random Structures andAlgorithms,2011,38(3):324-349
[113] L. Tzevelekas, K. Oikonomou, I. Stavrakakis. Random walk with jumps in large-scale randomgeometric graphs[J]. Computer Communications,2010,33(13):1505-1514
[114] C. Avin, B. Krishnamachari. The power of choice in random walks: An empirical study[J].Computer Networks,2008,52(1):44-60
[115] C. Avin, B. Krishnamachari. The power of choice in random walks: An empirical study[C]. InProceedings of the9th ACM International Symposium on Modeling Analysis and Simulation ofWireless and Mobile Systems, New York,2006,219-228
[116] A. Shokrollahi. Raptor Codes[J]. IEEE Transactions on Information Theory,2006,52(6):2551-2567
[117] Z. Zhu, S. Liu, J. Zhang, et al. Performance analysis of LT codes with different degreedistribution[C]. In Proceedings of the5th International Workshop on Chaos-fractals Theoriesand Applications, Dalian, Liaoning, China,2012,142-146
[118] N. Alon, C. Avin, M. Koucky, et al. Many random walks are faster than one[C]. In Proceedingsof the20th Annual ACM Symposium on Parallel Algorithms and Architectures, New York,2008,119-128
[119] N. Alon, C. Avin, M. Koucky, et al. Many random walks are faster than one[J]. Combinatorics,Probability and Computing,2011,20(4):481-502
[120] C. Cooper, A. Frieze, T. Radzik. Multiple random walks in random regular graphs[J]. SIAMJournal on Discrete Mathematics,2009,23(4):1738-1761