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Optimal data placement and Replication Approach for SIoT with Edge

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Computer Systems Science & Engineering 2022年第5期41卷 661-676页

作者： B.Prabhu Shankar S.Chitra Department of Information Technology Er Perumal Manimekalai College of EngineeringHosur635117TamilnaduIndia Department of Computer Science and Engineering Er Perumal Manimekalai College of EngineeringHosur63117TamilnaduIndia

Social networks(SNs)are sources with extreme number of users around the world who are all sharing data like images,audio,and video to their friends using IoT *** concept is the so-called Social Internet of Things(SIot).The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources,and this task demands an efficient storage *** this kind of large volume of data storage,the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low *** major issue is the way to store the data and replicate these large data items optimally and allocate the request from the data center *** efficient storage of these data,we use edge server,which is part of the cloud server,in this ***,the data are distributed and stored with quick access,which will reduce the latency with *** proposed data placement approach learns with machine learning(ML)algorithm called radial basis kernel function assisted with support vector machine(RBF-SVM)to classify the data center for storing the user and friend’s data from the SIoT *** learning algorithms will be used to predict the workload of the data stored in the data center as either edge or cloud depending on the existing time *** data placement with dynamic nature is also optimized using the proposed dynamic graph partitioning(GP)method to meet the individual user’s demand of low latency with minimum *** way will keep the SIoT data placement efficient and effective over ***,this proposed data placement and replication approach introduces three kinds of innovations compared with the existing data placement approach.(i)Rather than storing the user data in a single cloud,this study uses the edge server closest to the SIoT devices for faster access with reduced response time.(ii)The classification algorithm called RBF-SVM is used to find storage for

关键词： data placement data replication social network social internet of things edge computing cloud computing graph partitioning support vector machine machine learning radial basis function latency storage cost

Improved Harris Hawks Optimization Algorithm Based data placement Strategy for Integrated Cloud and Edge Computing

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Intelligent Automation & Soft Computing 2023年第7期37卷 887-904页

作者： V.Nivethitha G.Aghila National Institute of Technology Puducherry Karaikal609609India

Cloud computing is considered to facilitate a more cost-effective way to deploy scientific *** individual tasks of a scientific work-flow necessitate a diversified number of large states that are spatially located in different datacenters,thereby resulting in huge delays during data *** computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private ***,this fixed storage strategy creates huge amount of bottleneck in its storage *** this juncture,integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and optimizing the energy and time incurred in data transmission across different datacentres remains a *** this paper,Adaptive Cooperative Foraging and Dispersed Foraging Strategies-Improved Harris Hawks Optimization Algorithm(ACF-DFS-HHOA)is proposed for optimizing the energy and data transmission time in the event of placing data for a specific scientific *** ACF-DFS-HHOA considered the factors influencing transmission delay and energy consumption of data centers into account during the process of rationalizing the data placement of scientific *** adaptive cooperative and dispersed foraging strategy is included in HHOA to guide the position updates that improve population diversity and effectively prevent the algorithm from being trapped into local optimality *** experimental results of ACF-DFS-HHOA confirmed its predominance in minimizing energy and data transmission time incurred during workflow execution.

关键词： Edge computing cloud computing scientific workflow data placement energy of datacenters data transmission time

Novel data placement Algorithm for Distributed Storage System Based on Fault-Tolerant Domain

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Journal of Shanghai Jiaotong university(Science) 2021年第4期26卷 463-470页

作者： SHI Lianxing WANG Zhiheng LI Xiaoyong School of Cyber Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China School of Electronic Information Engineering Shanghai DianJi UniversityShanghai200240China

The 3-replica redundancy strategy is widely used to solve the problem of data reliability in large-scale distributed storage systems. However, its storage capacity utilization is only 33%. In this paper, a data placement algorithm based on fault-tolerant domain (FTD) is proposed. Owing to the fine-grained design of the FTD, the data reliability of systems using two replicas is comparable to that of current mainstream systems using three replicas, and the capacity utilization is increased to 50%. Moreover, the proposed FTD provides a new concept for the design of distributed storage systems. Distributed storage systems can take FTDs as the units for data placement, data migration, data repair and so on. In addition, fault detection can be performed independently and concurrently within the FTDs.

关键词： data reliability failure domain fault-tolerant domain data placement storage system distributed system

Graphical-based data placement algorithm for cloud workflow

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High Technology Letters 2014年第2期20卷 179-186页

作者：张鹏 Wang Guiling Han Yanbo Wang Jing North China University of Technology Institute of Computing Technology Chinese Academy of Sciences Graduate School of Chinese Academy of Sciences

When workflow task needs several datasets from different locations m cloud, data transfer becomes a challenge. To avoid the unnecessary data transfer, a graphical-based data placement algo- rithm for cloud workflow is proposed. The algorithm uses affinity graph to group datasets while keeping a polynomial time complexity. By integrating the algorithm, the workflow engine can intelligently select locations in which the data will reside to avoid the unnecessary data transfer during the initial stage and runtime stage. Simulations show that the proposed algorithm can effectively reduce data transfer during the workflow＇ s execution.

关键词： data placement affinity graph cloud computing workflow data transfer

Capability-Aware data placement for Heterogeneous Active Storage Systems

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Wuhan University Journal of Natural Sciences 2016年第3期21卷 249-256页

作者： LI Xiangyu HE Shuibing XU Xianbin WANG Yang School of Computer Wuhan University State Key Laboratory of High Performance Computing National University of Defense Technology School of Computer Science Wuhan Donghu University Shenzhen Institute of Advanced Technology Chinese Academy of Science

By moving computations from computing nodes to storage nodes, active storage technology provides an efficient for data-intensive high-performance computing applications. The existing studies have neglected the heterogeneity of storage nodes on the performance of active storage systems. We introduce CADP, a capability-aware data placement scheme for heterogeneous active storage systems to obtain high-performance data processing. The basic idea of CADP is to place data on storage nodes based on their computing capability and storage capability, so that the load-imbalance among heterogeneous servers can be avoided. We have implemented CADP under a parallel I/O system. The experimental results show that the proposed capability-aware data placement scheme can improve the active storage system performance significantly.

关键词： active storage parallel I/O system CADP data placement

GCSS:a global collaborative scheduling strategy for wide-area high-performance computing

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Frontiers of Computer Science 2022年第5期16卷 1-15页

作者： Yao SONG Limin XIAO Liang WANG Guangjun QIN Bing WEI Baicheng YAN Chenhao ZHANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China Smart City College Beijing Union UniversityBeijing 100101China

Wide-area high-performance computing is widely used for large-scale parallel computing applications owing to its high computing and storage ***,the geographical distribution of computing and storage resources makes efficient task distribution and data placement more *** achieve a higher system performance,this study proposes a two-level global collaborative scheduling strategy for wide-area high-performance computing *** collaborative scheduling strategy integrates lightweight solution selection,redundant data placement and task stealing mechanisms,optimizing task distribution and data placement to achieve efficient computing in wide-area *** experimental results indicate that compared with the state-of-the-art collaborative scheduling algorithm HPS+,the proposed scheduling strategy reduces the makespan by 23.24%,improves computing and storage resource utilization by 8.28%and 21.73%respectively,and achieves similar global data migration costs.

关键词： high-performance computing scheduling strategy task scheduling data placement

Striping and Scheduling for Large Scale Multimedia Servers

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Journal of Computer Science & Technology 2004年第6期19卷 885-895页

作者： Kyung-OhLee Jun-HoPark Yoon-YoungPark DepartmentofComputerScience SunmoonUniversity100TangJeonMyunKalsanRiAsansiChunNam336-840Korea

When designing a multimedia server, several things must be decided: which scheduling scheme to adopt, how to allocate multimedia objects on storage devices, and the round length with which the streams will be serviced. Several problems in the designing of large-scale multimedia servers are addressed, with the following contributions: (1) a striping scheme is proposed that minimizes the number of seeks and hence maximizes the performance; (2) a simple and efficient mechanism is presented to find the optimal striping unit size as well as the optimal round length, which exploits both the characteristics of VBR streams and the situation of resources in the system; and (3) the characteristics and resource requirements of several scheduling schemes are investigated in order to obtain a clear indication as to which scheme shows the best performance in realtime multimedia servicing. Based on our analysis and experimental results, the CSCAN scheme outperforms the other schemes. It is believed that the results are of value in the design of effective large-scale multimedia servers. Keywords realtime multimedia - storage server - scheduling - data placement - buffer management - variable bit rate This work was supported in part by the University IT Research Center Project and Sunmoon University Research Project.Kyung-Oh Lee is an associate professor in the Faculty of Computer and Information Sciences, Sunmoon University, Korea. He received his B.S., M.S. and Ph.D. degrees in computer science from Seoul National University in 1989, 1994 and 1999, respectively. His current research interests include multimedia system, database, mobile communication. He is a member of KIPS (Korea Information Processing Society).Jungho-Ho Park is a professor in the Divisions of Computer and Information Sciences, Sunmoon University, Korea. He received his M.S. and Ph.D. degrees in computer science from Osaka University in 1987 and 1990, respectively. His current research interests include d

关键词： realtime multimedia storage server scheduling data placement buffer management variable bit rate

Dynamic replication of web contents

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Science in China(Series F) 2007年第6期50卷 811-830页

作者： Amjad Mahmood Department of Computer Science University of Bahrain Kingdom of Bahrain

The phenomenal growth of the World Wide Web has brought huge increase in the traffic to the popular web sites. Long delays and denial of service experienced by the end-users, especially during the peak hours, continues to be the common problem while accessing popular sites. Replicating some of the objects at multiple sites in a distributed web-server environment is one of the possible solutions to improve the response time/latency. The decision of what and where to replicate requires solving a constraint optimization problem, which is NP-complete in gen- eral. In this paper, we consider the problem of placing copies of objects in a dis- tributed web server system to minimize the cost of serving read and write requests when the web servers have limited storage capacity. We formulate the problem as a 0-1 optimization problem and present a polynomial time greedy algorithm with backtracking to dynamically replicate objects at the appropriate sites to minimize a cost function. To reduce the solution search space, we present necessary condi- tions for a site to have a replica of an object in order to minimize the cost function. We present simulation results for a variety of problems to illustrate the accuracy and efficiency of the proposed algorithms and compare them with those of some well-known algorithms. The simulation results demonstrate the superiority of the proposed algorithms.

关键词： object replication Web distributed web-server system data placement Internet

data Storage Framework on Flash Memory using Object-based Storage Model

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Data Storage Framework on Flash Memory using Object-based St...