Virtual data center is a new form of cloud computing concept applied to data center. As one of the most important challenges, virtual data center embedding problem has attracted much attention from researchers. In dat...Virtual data center is a new form of cloud computing concept applied to data center. As one of the most important challenges, virtual data center embedding problem has attracted much attention from researchers. In data centers, energy issue is very important for the reality that data center energy consumption has increased by dozens of times in the last decade. In this paper, we are concerned about the cost-aware multi-domain virtual data center embedding problem. In order to solve this problem, this paper first addresses the energy consumption model. The model includes the energy consumption model of the virtual machine node and the virtual switch node, to quantify the energy consumption in the virtual data center embedding process. Based on the energy consumption model above, this paper presents a heuristic algorithm for cost-aware multi-domain virtual data center embedding. The algorithm consists of two steps: inter-domain embedding and intra-domain embedding. Inter-domain virtual data center embedding refers to dividing virtual data center requests into several slices to select the appropriate single data center. Intra-domain virtual data center refers to embedding virtual data center requests in each data center. We first propose an inter-domain virtual data center embedding algorithm based on label propagation to select the appropriate single data center. We then propose a cost-aware virtual data center embedding algorithm to perform the intra-domain data center embedding. Extensive simulation results show that our proposed algorithm in this paper can effectively reduce the energy consumption while ensuring the success ratio of embedding.展开更多
From the viewpoint of systems science, this article takes Xiaosha River artificial wetland under planning and construction as object of study based on the systems theory and takes the accomplished and running project ...From the viewpoint of systems science, this article takes Xiaosha River artificial wetland under planning and construction as object of study based on the systems theory and takes the accomplished and running project of Xinxuehe artificial wetland as reference. The virtual data of quantity and quality of inflow and the quality of outflow of Xiaosha River artificial wetland are built up according to the running experience, forecasting model and theoretical method of the reference project as well as the comparison analysis of the similarity and difference of the two example projects. The virtual data are used to study the building of forecasting model of BP neural network of Xiaosha River artificial wetland.展开更多
The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputi...The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and Computer Network Information Center in Chinese Academy of Sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).展开更多
The growth of generated data in the industry requires new efficient big data integration approaches for uniform data access by end-users to perform better business operations.Data virtualization systems,including Onto...The growth of generated data in the industry requires new efficient big data integration approaches for uniform data access by end-users to perform better business operations.Data virtualization systems,including Ontology-Based Data Access(ODBA)query data on-the-fly against the original data sources without any prior data materialization.Existing approaches by design use a fixed model e.g.,TABULAR as the only Virtual Data Model-a uniform schema built on-the-fly to load,transform,and join relevant data.While other data models,such as GRAPH or DOCUMENT,are more flexible and,thus,can be more suitable for some common types of queries,such as join or nested queries.Those queries are hard to predict because they depend on many criteria,such as query plan,data model,data size,and operations.To address the problem of selecting the optimal virtual data model for queries on large datasets,we present a new approach that(1)builds on the principal of OBDA to query and join large heterogeneous data in a distributed manner and(2)calls a deep learning method to predict the optimal virtual data model using features extracted from SPARQL queries.OPTIMA-implementation of our approach currently leverages state-of-the-art Big Data technologies,Apache-Spark and Graphx,and implements two virtual data models,GRAPH and TABULAR,and supports out-of-the-box five data sources models:property graph,document-based,e.g.,wide-columnar,relational,and tabular,stored in Neo4j,MongoDB,Cassandra,MySQL,and CSV respectively.Extensive experiments show that our approach is returning the optimal virtual model with an accuracy of 0.831,thus,a reduction in query execution time of over 40%for the tabular model selection and over 30%for the graph model selection.展开更多
Digital transformation has been corner stone of business innovation in the last decade, and these innovations have dramatically changed the definition and boundaries of enterprise business applications. Introduction o...Digital transformation has been corner stone of business innovation in the last decade, and these innovations have dramatically changed the definition and boundaries of enterprise business applications. Introduction of new products/ services, version management of existing products/ services, management of customer/partner connections, management of multi-channel service delivery (web, social media, web etc.), merger/acquisitions of new businesses and adoption of new innovations/technologies will drive data growth in business applications. These datasets exist in different sharing nothing business applications at different locations and in various forms. So, to make sense of this information and derive insight, it is essential to break the data silos, streamline data retrieval and simplify information access across the entire organization. The information access framework must support just-in-time processing capabilities to bring data from multiple sources, be fast and powerful enough to transform and process huge amounts of data quickly, and be agile enough to accommodate new data sources per user needs. This paper discusses the SAP HANA Smart Data Access data-virtualization technology to enable unified access to heterogenous data across the organization and analysis of huge volume of data in real-time using SAP HANA in-memory platform.展开更多
This paper addresses the problem of selecting a route for every pair of communicating nodes in a virtual circuit data network in order to minimize the average delay encountered by messages. The problem was previously ...This paper addresses the problem of selecting a route for every pair of communicating nodes in a virtual circuit data network in order to minimize the average delay encountered by messages. The problem was previously modeled as a network of M/M/1 queues. Agenetic algorithm to solve this problem is presented. Extensive computational results across a variety of networks are reported. These results indicate that the presented solution procedure outperforms the other methods in the literature and is effective for a wide range of traffic loads.展开更多
Natural mortality coefficient (M) was estimated from fish abundance (N) and catch (C) data using a Virtual Population Analysis (VPA) model. Monte Carlo simulations were used to evaluate the impact of different error d...Natural mortality coefficient (M) was estimated from fish abundance (N) and catch (C) data using a Virtual Population Analysis (VPA) model. Monte Carlo simulations were used to evaluate the impact of different error distributions for the simulated data on the estimates of M. Among the four error structures (normal, lognormal, Poisson and gamma), simulations of normally dis-tributed errors produced the most viable estimates for M, with the lowest relative estimation errors (REEs) and median mean absolute deviations (MADs) for the ratio of the true to the estimated Ms. In contrast, the lognormal distribution had the largest REE value. Errors with different coefficients of variation (CV) were added to N and C. In general, when CVs in the data were less than 10%, reliable estimates of M were obtained. For normal and lognormal distributions, the estimates of M were more sensitive to the CVs in N than in C; when only C had error the estimates were close to the true. For Poisson and gamma distributions, opposite results were obtained. For instance, the estimates were more sensitive to the CVs in C than in N, with the largest REE from the scenario of error only in C. Two scenarios of high and low fishing mortality coefficient (F) were generated, and the simulation results showed that the method performed better for the scenario with low F. This method was also applied to the published data for the anchovy (Engraulis japonicus) of the Yellow Sea. Viable estimates of M were obtained for young groups, which may be explained by the fact that the great uncertainties in N and C observed for older Yellow Sea anchovy introduced large variation in the corresponding estimates of M.展开更多
Testability virtual test is a new test method for testability verification, which has the advantages such as low cost, few restrictions and large sample of test data. It can be used to make up the deficiency of testab...Testability virtual test is a new test method for testability verification, which has the advantages such as low cost, few restrictions and large sample of test data. It can be used to make up the deficiency of testability physical test. In order to take the advantage of testability virtual test data effectively and to improve the accuracy of testability evaluation, a testability integrated eval- uation method is proposed in this paper based on testability virtual test data. Considering the char- acteristic of testability virtual test data, the credibility analysis method for testability virtual test data is studied firstly. Then the integrated calculation method is proposed fusing the testability vir- tual and physical test data. Finally, certain helicopter heading and attitude system is presented to demonstrate the proposed method. The results show that the testability integrated evaluation method is feasible and effective.展开更多
This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To som...This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To some extent,the virtual cluster simplifies network topology and management,achieves automatic conFig.uration and saves the IP address.It is a kind of low-cost expansion method of aggregation equipment port density.展开更多
Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the ph...Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.展开更多
Resource Scheduling is crucial to data centers. However, most previous works focus only on one-dimensional resource models which ignoring the fact that multiple resources simultaneously utilized, including CPU, memory...Resource Scheduling is crucial to data centers. However, most previous works focus only on one-dimensional resource models which ignoring the fact that multiple resources simultaneously utilized, including CPU, memory and network bandwidth. As cloud computing allows uncoordinated and heterogeneous users to share a data center, competition for multiple resources has become increasingly severe. Motivated by the differences on integrated utilization obtained from different packing schemes, in this paper we take the scheduling problem as a multi-dimensional combinatorial optimization problem with constraint satisfaction. With NP hardness, we present Multiple attribute decision based Integrated Resource Scheduling (MIRS), and a novel heuristic algorithm to gain the approximate optimal solution. Refers to simulation results, in face of various workload sets, our algorithm has significant superiorities in terms of efficiency and performance compared with previous methods.展开更多
Based on the analysis of data centre(DC) traffic pattern, we introduced a holistic software-defined optical DC solution. Architecture-on-Demand based hybrid optical switched(OPS/OCS) data centre network(DCN) fabric is...Based on the analysis of data centre(DC) traffic pattern, we introduced a holistic software-defined optical DC solution. Architecture-on-Demand based hybrid optical switched(OPS/OCS) data centre network(DCN) fabric is introduced, which is able to realise different inter-and intra-cluster configurations and dynamically support diverse traffic in the DC. The optical DCN is controlled and managed by a software-defined networking(SDN) enabled control plane to achieve high programmability. Moreover, virtual data centre(VDC) composition is developed as an application of such softwaredefined optical DC to create VDC slices for different tenants.展开更多
In the modern era of 5th generation(5G)networks,the data generated by User Equipments(UE)has increased significantly,with data file sizes varying from modest sensor logs to enormous multimedia files.In modern telecomm...In the modern era of 5th generation(5G)networks,the data generated by User Equipments(UE)has increased significantly,with data file sizes varying from modest sensor logs to enormous multimedia files.In modern telecommunications networks,the need for high-end security and efficient management of these large data files is a great challenge for network designers.The proposed model provides the efficient real-time virtual data storage of UE data files(light and heavy)using an object storage system MinIO having inbuilt Software Development Kits(SDKs)that are compatible with Amazon(S3)Application Program Interface(API)making operations like file uploading,and data retrieval extremely efficient as compared to legacy virtual storage system requiring low-level HTTP requests for data management.To provide integrity,authenticity,and confidentiality(integrity checking via an authentication tag)to the data files of UE,the encrypted algorithm 256-bit oriented-Advanced Encryption Standard(256-AES)in Galois/Counter Mode(GCM)is utilized in combination with MinIO.The AES-based MinIO signifies in more secure and faster approach than older models like Cipher Block Chaining(CBC).The performance of the proposed model is analyzed using the Iperf utility to perform the Teletraffic parametric(bandwidth,throughput,latency,and transmission delay)analysis for three different cases namely:(a)light UE traffic(uploading and retrieval)(b)heavy UE traffic(uploading and retrieval)and(c)comparison of Teletraffic parameters namely:bandwidth(Bava),throughput(Tput),data transfer(D_(Trans)),latency(L_(ms)),and transmission delay(TDelay)obtained from proposed method with legacy virtual storage methods.The results show that the suggested MinIO-based system outperforms conventional systems in terms of latency,encryption efficiency,and performance under varying data load conditions.展开更多
基金supported in part by the following funding agencies of China:National Natural Science Foundation under Grant 61602050 and U1534201National Key Research and Development Program of China under Grant 2016QY01W0200
文摘Virtual data center is a new form of cloud computing concept applied to data center. As one of the most important challenges, virtual data center embedding problem has attracted much attention from researchers. In data centers, energy issue is very important for the reality that data center energy consumption has increased by dozens of times in the last decade. In this paper, we are concerned about the cost-aware multi-domain virtual data center embedding problem. In order to solve this problem, this paper first addresses the energy consumption model. The model includes the energy consumption model of the virtual machine node and the virtual switch node, to quantify the energy consumption in the virtual data center embedding process. Based on the energy consumption model above, this paper presents a heuristic algorithm for cost-aware multi-domain virtual data center embedding. The algorithm consists of two steps: inter-domain embedding and intra-domain embedding. Inter-domain virtual data center embedding refers to dividing virtual data center requests into several slices to select the appropriate single data center. Intra-domain virtual data center refers to embedding virtual data center requests in each data center. We first propose an inter-domain virtual data center embedding algorithm based on label propagation to select the appropriate single data center. We then propose a cost-aware virtual data center embedding algorithm to perform the intra-domain data center embedding. Extensive simulation results show that our proposed algorithm in this paper can effectively reduce the energy consumption while ensuring the success ratio of embedding.
文摘From the viewpoint of systems science, this article takes Xiaosha River artificial wetland under planning and construction as object of study based on the systems theory and takes the accomplished and running project of Xinxuehe artificial wetland as reference. The virtual data of quantity and quality of inflow and the quality of outflow of Xiaosha River artificial wetland are built up according to the running experience, forecasting model and theoretical method of the reference project as well as the comparison analysis of the similarity and difference of the two example projects. The virtual data are used to study the building of forecasting model of BP neural network of Xiaosha River artificial wetland.
基金supported by the National Key Research and Development Program of China(2018YFB0203901)the National Natural Science Foundation of China(Grant No.61772053)+1 种基金the Hebei Youth Talents Support Project(BJ2019008)the Natural Science Foundation of Hebei Province(F2020204003).
文摘The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and Computer Network Information Center in Chinese Academy of Sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).
基金the financial support of Fraunhofer Cluster of Excellence (CCIT)
文摘The growth of generated data in the industry requires new efficient big data integration approaches for uniform data access by end-users to perform better business operations.Data virtualization systems,including Ontology-Based Data Access(ODBA)query data on-the-fly against the original data sources without any prior data materialization.Existing approaches by design use a fixed model e.g.,TABULAR as the only Virtual Data Model-a uniform schema built on-the-fly to load,transform,and join relevant data.While other data models,such as GRAPH or DOCUMENT,are more flexible and,thus,can be more suitable for some common types of queries,such as join or nested queries.Those queries are hard to predict because they depend on many criteria,such as query plan,data model,data size,and operations.To address the problem of selecting the optimal virtual data model for queries on large datasets,we present a new approach that(1)builds on the principal of OBDA to query and join large heterogeneous data in a distributed manner and(2)calls a deep learning method to predict the optimal virtual data model using features extracted from SPARQL queries.OPTIMA-implementation of our approach currently leverages state-of-the-art Big Data technologies,Apache-Spark and Graphx,and implements two virtual data models,GRAPH and TABULAR,and supports out-of-the-box five data sources models:property graph,document-based,e.g.,wide-columnar,relational,and tabular,stored in Neo4j,MongoDB,Cassandra,MySQL,and CSV respectively.Extensive experiments show that our approach is returning the optimal virtual model with an accuracy of 0.831,thus,a reduction in query execution time of over 40%for the tabular model selection and over 30%for the graph model selection.
文摘Digital transformation has been corner stone of business innovation in the last decade, and these innovations have dramatically changed the definition and boundaries of enterprise business applications. Introduction of new products/ services, version management of existing products/ services, management of customer/partner connections, management of multi-channel service delivery (web, social media, web etc.), merger/acquisitions of new businesses and adoption of new innovations/technologies will drive data growth in business applications. These datasets exist in different sharing nothing business applications at different locations and in various forms. So, to make sense of this information and derive insight, it is essential to break the data silos, streamline data retrieval and simplify information access across the entire organization. The information access framework must support just-in-time processing capabilities to bring data from multiple sources, be fast and powerful enough to transform and process huge amounts of data quickly, and be agile enough to accommodate new data sources per user needs. This paper discusses the SAP HANA Smart Data Access data-virtualization technology to enable unified access to heterogenous data across the organization and analysis of huge volume of data in real-time using SAP HANA in-memory platform.
文摘This paper addresses the problem of selecting a route for every pair of communicating nodes in a virtual circuit data network in order to minimize the average delay encountered by messages. The problem was previously modeled as a network of M/M/1 queues. Agenetic algorithm to solve this problem is presented. Extensive computational results across a variety of networks are reported. These results indicate that the presented solution procedure outperforms the other methods in the literature and is effective for a wide range of traffic loads.
文摘Natural mortality coefficient (M) was estimated from fish abundance (N) and catch (C) data using a Virtual Population Analysis (VPA) model. Monte Carlo simulations were used to evaluate the impact of different error distributions for the simulated data on the estimates of M. Among the four error structures (normal, lognormal, Poisson and gamma), simulations of normally dis-tributed errors produced the most viable estimates for M, with the lowest relative estimation errors (REEs) and median mean absolute deviations (MADs) for the ratio of the true to the estimated Ms. In contrast, the lognormal distribution had the largest REE value. Errors with different coefficients of variation (CV) were added to N and C. In general, when CVs in the data were less than 10%, reliable estimates of M were obtained. For normal and lognormal distributions, the estimates of M were more sensitive to the CVs in N than in C; when only C had error the estimates were close to the true. For Poisson and gamma distributions, opposite results were obtained. For instance, the estimates were more sensitive to the CVs in C than in N, with the largest REE from the scenario of error only in C. Two scenarios of high and low fishing mortality coefficient (F) were generated, and the simulation results showed that the method performed better for the scenario with low F. This method was also applied to the published data for the anchovy (Engraulis japonicus) of the Yellow Sea. Viable estimates of M were obtained for young groups, which may be explained by the fact that the great uncertainties in N and C observed for older Yellow Sea anchovy introduced large variation in the corresponding estimates of M.
基金supported by National Natural Science Foundation of China (No.51105369)
文摘Testability virtual test is a new test method for testability verification, which has the advantages such as low cost, few restrictions and large sample of test data. It can be used to make up the deficiency of testability physical test. In order to take the advantage of testability virtual test data effectively and to improve the accuracy of testability evaluation, a testability integrated eval- uation method is proposed in this paper based on testability virtual test data. Considering the char- acteristic of testability virtual test data, the credibility analysis method for testability virtual test data is studied firstly. Then the integrated calculation method is proposed fusing the testability vir- tual and physical test data. Finally, certain helicopter heading and attitude system is presented to demonstrate the proposed method. The results show that the testability integrated evaluation method is feasible and effective.
基金supported by the Collaboration Research on Key Techniques of Future Network between China,Japan and Korea(2010DFB13470)~~
文摘This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To some extent,the virtual cluster simplifies network topology and management,achieves automatic conFig.uration and saves the IP address.It is a kind of low-cost expansion method of aggregation equipment port density.
基金This research was partially supported by the National Grand Fundamental Research 973 Program of China under Grant （No. 2013CB329103）, Natural Science Foundation of China grant （No. 61271171）, the Fundamental Research Funds for the Central Universities （ZYGX2013J002, ZYGX2012J004, ZYGX2010J002, ZYGX2010J009）, Guangdong Science and Technology Project （2012B090500003, 2012B091000163, 2012556031）.
文摘Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.
基金supported in part by National Key Basic Research Program of China (973 program) under Grant No.2011CB302506Important National Science & Technology Specific Projects: Next-Generation Broadband Wireless Mobile Communications Network under Grant No.2011ZX03002-001-01Innovative Research Groups of the National Natural Science Foundation of China under Grant No.60821001
文摘Resource Scheduling is crucial to data centers. However, most previous works focus only on one-dimensional resource models which ignoring the fact that multiple resources simultaneously utilized, including CPU, memory and network bandwidth. As cloud computing allows uncoordinated and heterogeneous users to share a data center, competition for multiple resources has become increasingly severe. Motivated by the differences on integrated utilization obtained from different packing schemes, in this paper we take the scheduling problem as a multi-dimensional combinatorial optimization problem with constraint satisfaction. With NP hardness, we present Multiple attribute decision based Integrated Resource Scheduling (MIRS), and a novel heuristic algorithm to gain the approximate optimal solution. Refers to simulation results, in face of various workload sets, our algorithm has significant superiorities in terms of efficiency and performance compared with previous methods.
基金performed in the Projects " LIGHTNESS : Low latency and high throughput dynamic network infrastructures for high performance datacentre interconnects" (No. 318606) "COSIGN: Combining Optics and SDN In next Generation data centre Networks" (No. 619572) supported by European Commission FP7
文摘Based on the analysis of data centre(DC) traffic pattern, we introduced a holistic software-defined optical DC solution. Architecture-on-Demand based hybrid optical switched(OPS/OCS) data centre network(DCN) fabric is introduced, which is able to realise different inter-and intra-cluster configurations and dynamically support diverse traffic in the DC. The optical DCN is controlled and managed by a software-defined networking(SDN) enabled control plane to achieve high programmability. Moreover, virtual data centre(VDC) composition is developed as an application of such softwaredefined optical DC to create VDC slices for different tenants.
文摘In the modern era of 5th generation(5G)networks,the data generated by User Equipments(UE)has increased significantly,with data file sizes varying from modest sensor logs to enormous multimedia files.In modern telecommunications networks,the need for high-end security and efficient management of these large data files is a great challenge for network designers.The proposed model provides the efficient real-time virtual data storage of UE data files(light and heavy)using an object storage system MinIO having inbuilt Software Development Kits(SDKs)that are compatible with Amazon(S3)Application Program Interface(API)making operations like file uploading,and data retrieval extremely efficient as compared to legacy virtual storage system requiring low-level HTTP requests for data management.To provide integrity,authenticity,and confidentiality(integrity checking via an authentication tag)to the data files of UE,the encrypted algorithm 256-bit oriented-Advanced Encryption Standard(256-AES)in Galois/Counter Mode(GCM)is utilized in combination with MinIO.The AES-based MinIO signifies in more secure and faster approach than older models like Cipher Block Chaining(CBC).The performance of the proposed model is analyzed using the Iperf utility to perform the Teletraffic parametric(bandwidth,throughput,latency,and transmission delay)analysis for three different cases namely:(a)light UE traffic(uploading and retrieval)(b)heavy UE traffic(uploading and retrieval)and(c)comparison of Teletraffic parameters namely:bandwidth(Bava),throughput(Tput),data transfer(D_(Trans)),latency(L_(ms)),and transmission delay(TDelay)obtained from proposed method with legacy virtual storage methods.The results show that the suggested MinIO-based system outperforms conventional systems in terms of latency,encryption efficiency,and performance under varying data load conditions.
