检索结果-内蒙古大学图书馆

distributed data storage Systems for data Survivability in Wireless Sensor Networks using Decentralized Erasure Codes

引用

COMPUTER NETWORKS 2016年第0期97卷 113-127页

作者： Al-Awami, Louai Hassanein, Hossam S. King Fahd Univ Petr & Minerals Dept Comp Engn Dhahran 31261 Saudi Arabia Queens Univ Sch Comp Kingston ON Canada

Achieving reliability in Wireless Sensor Networks (WSNs) is challenging due to the limited resources available. In this study, we investigate the design of data survivability schemes using decentralized storage systems in WSNs. We propose a data storage system design based on Decentralized Erasure Codes (DEC) that features a simple and decentralized construction of the target code. The proposed framework allows sensor nodes to cooperate to build an erasure code-based storage that can tolerate a given failure/erasure rate. Code construction and decoding can both be performed randomly allowing for a distributed operation with no prior setup or coordination between source nodes. Further, we present two approaches that utilize Random Linear Network Coding (RLNC) to enhance the proposed scheme in order to achieve energy efficiency. We present the theoretical basis of the schemes then validate and evaluate their performance through simulations. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Wireless Sensor Network data Survivability Decentralized Erasure Codes Network Coding distributed data storage

来源：评论

学校读者我要写书评

暂无评论

distributed data storage in Sensor Networks Based on Raptor Codes

Distributed Data Storage in Sensor Networks Based on Raptor ...

引用

IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Jafarizadeh, Saber Jamalipour, Abbas Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia

ISBN: (纸本)9781467325691

In this paper an algorithm for distributed data storage in large-scale sensor networks has been proposed. The main objective is to distribute the generated information throughout the network to increase its lifetime. At the same time it is desired that the original data can be recovered later by collecting the contents of a limited number of sensor nodes. In the scenario considered here the sensor nodes have limited energy and memory and each sensor saves only one encoded packet. Also sensors do not hold any routing table and no global information regarding network topology is available. The algorithm proposed here is based on Raptor codes and it inherits their linear time encoding and decoding complexity. Random walks are used for disseminating data amongst sensor nodes. Major benefits of the algorithm presented here is that it utilizes the online decoding property of Raptor codes by achieving the desired code degree distribution and for estimating the required global information regarding network topology, no excessive random walks and transmissions are used.

关键词： Sensor networks distributed data storage Raptor codes Random walk

来源：评论

学校读者我要写书评

暂无评论

Volatility-Based Measurements Allocation for distributed data storage in Mobile Crowd Sensing

引用

IEEE SYSTEMS JOURNAL 2023年第4期17卷 6665-6675页

作者： Peng, Jiaxin Zhou, Siwang Liu, Xingting Hunan Univ Coll Comp Sci & Elect Engn Changsha 410008 Peoples R China

For the implementation of distributed storage frameworks in the context of mobile crowd sensing (MCS), compressed sensing (CS) theory provides significant support, mainly because of the essential characteristic that CS theory will contain global information when encoding any measurements. Therefore, with limited measurement resources, the rational allocation of measurement resources becomes the most critical factor affecting recovery accuracy when using CS to recover the data. Unfortunately, the latest distributed storage frameworks do not take into account the importance of measurement resource allocation, which directly leads to a significant loss of data recovery accuracy. Therefore, to address this issue, this article proposes a volatility-based allocation strategy for the measurement resource. First, we process the target monitoring region in blocks. Next, we calculate the magnitude of fluctuations between adjacent reconstructed data by volatility, which is used to assess the importance of the different areas. Finally, a volatility-based measurement allocation scheme is proposed by fully considering the importance of different areas. It is important to note that the introduction of the concept of "volatility" in the context of MCS makes it feasible to correctly differentiate the importance of individual parts of the targetmonitoring regionwithout any prior knowledge by employing extremely fuzzy recovery data. In addition, extensive experiments show that our measurement allocation scheme improves data recovery accuracy by 44% for uneven data distribution scenarios and 25% for even data distribution scenarios, compared with the randommeasurement allocation used in the state-of-the-art MCS distributed storage framework.

关键词： Compressed sensing distributed data storage measurements allocation mobile crowd sensing (MCS)

来源：评论

学校读者我要写书评

暂无评论

A distributed data storage protocol for heterogeneous wireless sensor networks with mobile sinks

引用

AD HOC NETWORKS 2013年第5期11卷 1588-1602页

作者： Maia, Guilherme Guidoni, Daniel L. Viana, Aline C. Aquino, Andre L. L. Mini, Raquel A. F. Loureiro, Antonio A. F. Univ Fed Minas Gerais Belo Horizonte MG Brazil INRIA Orsay France Univ Fed Alagoas Maceio AL Brazil Pontif Catholic Univ Belo Horizonte MG Brazil

This paper presents ProFlex, a distributed data storage protocol for large-scale Heterogeneous Wireless Sensor Networks (HWSNs) with mobile sinks. ProFlex guarantees robustness in data collection by intelligently managing data replication among selected storage nodes in the network. Contrarily to related protocols in the literature, ProFlex considers the resource constraints of sensor nodes and constructs multiple data replication structures, which are managed by more powerful nodes. Additionally, ProFlex takes advantage of the higher communication range of such powerful nodes and uses the long-range links to improve data distribution by storage nodes. When compared with related protocols, we show through simulation that Proflex has an acceptable performance under message loss scenarios, decreases the overhead of transmitted messages, and decreases the occurrence of the energy hole problem. Moreover, we propose an improvement that allows the protocol to leverage the inherent data correlation and redundancy of wireless sensor networks in order to decrease even further the protocol's overhead without affecting the quality of the data distribution by storage nodes. (c) 2013 Elsevier B.V. All rights reserved.

关键词： distributed data storage Heterogeneous wireless sensor networks Mobile sinks

来源：评论

学校读者我要写书评

暂无评论

Identity-Based Secure distributed data storage Schemes

引用

IEEE TRANSACTIONS ON COMPUTERS 2014年第4期63卷 941-953页

作者： Han, Jinguang Susilo, Willy Mu, Yi Univ Wollongong Ctr Comp & Informat Secur Res Sch Comp Sci & Software Engn Wollongong NSW 2522 Australia Nanjing Univ Finance & Econ Jiangsu Prov Key Lab E Business Nanjing 210003 Jiangsu Peoples R China

Secure distributed data storage can shift the burden of maintaining a large number of files from the owner to proxy servers. Proxy servers can convert encrypted files for the owner to encrypted files for the receiver without the necessity of knowing the content of the original files. In practice, the original files will be removed by the owner for the sake of space efficiency. Hence, the issues on confidentiality and integrity of the outsourced data must be addressed carefully. In this paper, we propose two identity-based secure distributed data storage (IBSDDS) schemes. Our schemes can capture the following properties: (1) The file owner can decide the access permission independently without the help of the private key generator (PKG);(2) For one query, a receiver can only access one file, instead of all files of the owner;(3) Our schemes are secure against the collusion attacks, namely even if the receiver can compromise the proxy servers, he cannot obtain the owner's secret key. Although the first scheme is only secure against the chosen plaintext attacks (CPA), the second scheme is secure against the chosen ciphertext attacks (CCA). To the best of our knowledge, it is the first IBSDDS schemes where an access permission is made by the owner for an exact file and collusion attacks can be protected in the standard model.

关键词： distributed data storage identity-based system access control security

来源：评论

学校读者我要写书评

暂无评论

Self-Verifiable Attribute-Based Keyword Search Scheme for distributed data storage in Fog Computing With Fast Decryption

引用

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2022年第1期19卷 271-288页

作者： Gu, Ke Zhang, Wenbin Li, Xiong Jia, Weijia Univ Sci & Technol Sch Comp & Commun Engn Changsha 410114 Peoples R China Univ Elect Sci & Technol China Sch Comp Sci & Engn Inst Cyber Secur Chengdu 611731 Peoples R China Beijing Normal Univ Hong Kong Baptist Univ United Int Coll Guangdong Key Lab AI & Multimodal Data Proc Zhuhai 519087 Guangdong Peoples R China

Presently many searchable encryption schemes have been proposed for cloud and fog computing, which use fog nodes (or fog servers) to partly undertake some computational tasks. However, these related schemes still retain cloud servers to undertake most computational tasks, which result in large communication costs between edge devices and cloud servers. Therefore, in this paper we propose a self-verifiable attribute-based keyword search scheme for distributed data storage (SV-KSDS) in full fog computing, where each decryption operation on the data required by a user must meet the negotiated decryption rule between fog servers. Our SV-KSDS scheme first provides attribute-based distributed data storage among fog servers through the (w, sigma) threshold secret-sharing scheme, where fog servers can provide self-verifiable keyword search and data decryption for terminal users. Compared with the data storage in cloud computing, our scheme extends it to the distributed structure while providing fine-grained access control for distributed data storage through attribute-based encryption. The access control policy of our scheme is constructed on linear secret-sharing scheme, whose security is reduced to the decisional bilinear Diffie-Hellman assumption against chosen-keyword attack and the decisional q-parallel bilinear Diffie-Hellman assumption against chosen-plaintext attack in the standard model. Based on theoretical analysis and practical testing, our SV-KSDS scheme generates less computation and communication costs, which further unloads some computational tasks from terminal users to fog servers so as to reduce computing costs of terminal users.

关键词： Keyword search Attribute-based encryption distributed data storage Secret-sharing Fog computing

来源：评论

学校读者我要写书评

暂无评论

Feasible Region of Secure and distributed data storage in Adversarial Networks

引用

IEEE INTERNET OF THINGS JOURNAL 2022年第11期9卷 8980-8988页

作者： Ren, Jian Li, Jian Li, Tongtong Mutka, Matt W. Michigan State Univ Dept Elect & Comp Engn E Lansing MI 48824 USA Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China

Large volumes of data are being generated daily from IoT networks, healthcare, and many other applications, which makes secure, reliable, and cost-effective data storage a critical infrastructure of the computing system. Existing data storage largely depends on centralized clouds, which is not only costly but also vulnerable to single points of failure and other types of security attacks. Moreover, cloud providers will have full access to user data and revision history beyond user control. To provide data security, data encryption has to be used, which requires extensive computing power and cumbersome key management. distributed storage system (DSS) is being widely viewed as a natural solution to future online data storage due to improved access time and lower storage cost. However, the existing DSS also has the limitations of low storage efficiency and weak data security. In this article, we investigate multi-layer code-based distributed data storage systems that can achieve inherit content confidentiality and optimal storage efficiency. Our comprehensive performance analysis shows that the optimal code can improve the feasible region in reliable data storage by 50% under various adversarial attack scenarios.

关键词： Memory Peer-to-peer computing Codes Cloud computing Reliability Internet of Things Encryption Adversarial networks distributed data storage feasible storage region optimal

来源：评论

学校读者我要写书评

暂无评论

On construction of a distributed data storage system in cloud

引用

COMPUTING 2016年第1-2期98卷 93-118页

作者： Yang, Chao-Tung Shih, Wen-Chung Huang, Chih-Lin Jiang, Fuu-Cheng Chu, William Cheng-Chung Tunghai Univ Dept Comp Sci Taichung 40704 Taiwan Asia Univ Dept Appl Informat & Multimedia Taichung Taiwan

In the past, people have focused on cluster computing and grid computing. Now, however, this focus has shifted to cloud computing. Irrespective of what techniques are used, there are always storage requirements. The challenge people face in this area is the huge amount of data to be stored, and its complexity. People are now using many cloud applications. As a result, service providers must serve increasingly more people, causing more and more connections involving substantially more data. These problems could have been solved in the past, but in the age of cloud computing, they have become more complex. This paper focuses on cloud computing infrastructure, and especially data services. The goal of this paper is to implement a high performance and load balancing, and able-to-be-replicated system that provides data storage for private cloud users through a virtualization system. This system extends and enhances the functionality of the Hadoop distributed system. The proposed approach also implements a resource monitor of machine status factors such as CPU, memory, and network usage to help optimize the virtualization system and data storage system. To prove and extend the usability of this design, a synchronize app was also developed running on Android based on our distributed data storage.

关键词： Cloud computing distributed data storage data as a service distributed file system

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient distributed data storage for Wireless Sensor Networks Based on Compressed Sensing and Network Coding

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2013年第10期12卷 5087-5099页

作者： Yang, Xianjun Tao, Xiaofeng Dutkiewicz, Eryk Huang, Xiaojing Guo, Y. Jay Cui, Qimei Beijing Univ Posts & Telecommun Wireless Technol Innovat Inst Key Lab Univ Wireless Commun Minist Educ Beijing 100088 Peoples R China Macquarie Univ WiMed Res Ctr Sydney NSW 2109 Australia Macquarie Univ Sydney NSW 2109 Australia CSIRO ICT Ctr Sydney NSW Australia

Recently, distributed data storage (DDS) for Wireless Sensor Networks (WSNs) has attracted great attention, especially in catastrophic scenarios. Since power consumption is one of the most critical factors that affect the lifetime of WSNs, the energy efficiency of DDS in WSNs is investigated in this paper. Based on Compressed Sensing (CS) and network coding theories, we propose a Compressed Network Coding based distributed data storage (CNCDS) scheme by exploiting the correlation of sensor readings. The CNCDS scheme achieves high energy efficiency by reducing the total number of transmissions Nt(tot) and receptions Nr(tot) during the data dissemination process. Theoretical analysis proves that the CNCDS scheme guarantees good CS recovery performance. In order to theoretically verify the efficiency of the CNCDS scheme, the expressions for Nt(tot) and Nr(tot) are derived based on random geometric graphs (RGG) theory. Furthermore, based on the derived expressions, an adaptive CNCDS scheme is proposed to further reduce Nt(tot) and Nr(tot). Simulation results validate that, compared with the conventional ICstorage scheme, the proposed CNCDS scheme reduces Nt(tot), Nr(tot), and the CS recovery mean squared error (MSE) by up to 55%, 74%, and 76% respectively. In addition, compared with the CNCDS scheme, the adaptive CNCDS scheme further reduces Nt(tot) and Nr(tot) by up to 63% and 32% respectively.

关键词： Compressed sensing distributed data storage network coding random geometric graph wireless sensor network

来源：评论

学校读者我要写书评

暂无评论

Spatiotemporal Compressive Network Coding for Energy-Efficient distributed data storage in Wireless Sensor Networks

引用

IEEE COMMUNICATIONS LETTERS 2015年第5期19卷 803-806页

作者： Gong, Bo Cheng, Peng Chen, Zhuo Liu, Ning Gui, Lin de Hoog, Frank Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China CSIRO Digital Prod Flagship Marsfield NSW 2122 Australia

distributed data storage (DDS) provides a promising approach to the reliable recovery of the whole sensor readings in a wireless sensor network (WSN) by visiting a small subset of sensor nodes. To reduce the number of transmissions/receptions, various DDS schemes based on compressive sensing (CS) have been proposed in the literature. However, these schemes only exploit the spatial correlation among sensor readings from geographically neighboring nodes, and the potential temporal correlation over multiple time slots within a frame duration is ignored. This results in energy inefficiency of DDS within the WSN. In this letter, we take a new approach, and exploit spatial and temporal (spatiotemporal) correlations among sensor readings simultaneously. A novel DDS coding scheme, referred to as spatiotemporal compressive network coding (ST-CNC), is proposed to collect sensor readings across the WSN in a more energy-efficient manner. Compared with the existing DDS schemes with CS, the proposed scheme significantly reduces the number of transmissions and receptions with similar recovery performance.

关键词： Compressive sensing spatiotemporal correlation network coding distributed data storage wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：