Emergence and adoption of cloud computing have become widely prevalent given the value proposition it brings to an enterprise in terms of agility and cost effectiveness. Big data analytical capabilities (specifically treating storage/system management as a big data problem for a service provider) using Cloud delivery models is defined as Analytics as a Service or Software as a Service. This service simplifies obtaining useful insights from an operational enterprise data center leading to cost and performance optimizations.Software defined environments decouple the control planes from the data planes that were often vertically integrated in a traditional networking or storage systems. The decoupling between the control planes and the data planes enables opportunities for improved security, resiliency and IT optimization in general. This talk describes our novel approach in hosting the systems management platform (a.k.a. control plane) in the cloud offered to enterprises in Software as a Service (SaaS) model. Specifically, in this presentation, focus is on the analytics layer with SaaS paradigm enabling data centers to visualize, optimize and forecast infrastructure via a simple capture, analyze and govern framework. At the core, it uses big data analytics to extract actionable insights from system management metrics data. Our system is developed in research and deployed across customers, where core focus is on agility, elasticity and scalability of the analytics framework. We demonstrate few system/storage management analytics case studies to demonstrate cost and performance optimization for both cloud consumer as well as service provider. Actionable insights generated from the analytics platform are implemented in an automated fashion via an OpenStack based platform.
{"title":"Cloud Storage Infrastructure Optimization Analytics","authors":"R. Routray","doi":"10.1109/IC2E.2015.83","DOIUrl":"https://doi.org/10.1109/IC2E.2015.83","url":null,"abstract":"Emergence and adoption of cloud computing have become widely prevalent given the value proposition it brings to an enterprise in terms of agility and cost effectiveness. Big data analytical capabilities (specifically treating storage/system management as a big data problem for a service provider) using Cloud delivery models is defined as Analytics as a Service or Software as a Service. This service simplifies obtaining useful insights from an operational enterprise data center leading to cost and performance optimizations.Software defined environments decouple the control planes from the data planes that were often vertically integrated in a traditional networking or storage systems. The decoupling between the control planes and the data planes enables opportunities for improved security, resiliency and IT optimization in general. This talk describes our novel approach in hosting the systems management platform (a.k.a. control plane) in the cloud offered to enterprises in Software as a Service (SaaS) model. Specifically, in this presentation, focus is on the analytics layer with SaaS paradigm enabling data centers to visualize, optimize and forecast infrastructure via a simple capture, analyze and govern framework. At the core, it uses big data analytics to extract actionable insights from system management metrics data. Our system is developed in research and deployed across customers, where core focus is on agility, elasticity and scalability of the analytics framework. We demonstrate few system/storage management analytics case studies to demonstrate cost and performance optimization for both cloud consumer as well as service provider. Actionable insights generated from the analytics platform are implemented in an automated fashion via an OpenStack based platform.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125668156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stefan Berger, Kenneth A. Goldman, D. Pendarakis, D. Safford, Enriquillo Valdez, Mimi Zohar
In this work we present Scalable Attestation, a method which combines both secure boot and trusted boot technologies, and extends them up into the host, its programs, and up into the guest's operating system and workloads, to both detect and prevent integrity attacks. Anchored in hardware, this integrity appraisal and attestation protects persistent data (files) from remote attack, even if the attack is root privileged. As an added benefit of a hardware rooted attestation, we gain a simple hardware based geolocation attestation to help enforce regulatory requirements. This design is implemented in multiple cloud test beds based on the QEMU/KVM hypervisor, Open Stack, and Open Attestation, and is shown to provide significant additional integrity protection at negligible cost.
{"title":"Scalable Attestation: A Step Toward Secure and Trusted Clouds","authors":"Stefan Berger, Kenneth A. Goldman, D. Pendarakis, D. Safford, Enriquillo Valdez, Mimi Zohar","doi":"10.1109/MCC.2015.97","DOIUrl":"https://doi.org/10.1109/MCC.2015.97","url":null,"abstract":"In this work we present Scalable Attestation, a method which combines both secure boot and trusted boot technologies, and extends them up into the host, its programs, and up into the guest's operating system and workloads, to both detect and prevent integrity attacks. Anchored in hardware, this integrity appraisal and attestation protects persistent data (files) from remote attack, even if the attack is root privileged. As an added benefit of a hardware rooted attestation, we gain a simple hardware based geolocation attestation to help enforce regulatory requirements. This design is implemented in multiple cloud test beds based on the QEMU/KVM hypervisor, Open Stack, and Open Attestation, and is shown to provide significant additional integrity protection at negligible cost.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132337958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Software Defined Networking (SDN) has become a promising network architecture that simplifies the network control, management and deployment of differentiated services. SDN architecture decouples control and data planes. Control functions are moved to a logically centralized entity called controller. The underlying infrastructure solely performs forwarding. Most of the previous studies focus on using SDN in data centers. In this paper, we propose scalable routing and resource management model for SDN based intra-domain networks. To virtualize the underlying network, we use pre-established multi-paths (PMP) between each ingress-egress switch. SDN-Controller performs admission control, routing, load balancing and path resizing functions based on these paths. The experimental results show that the proposed model significantly improves routing and signaling scalability, network resource utilization and decreases admission control time.
{"title":"An SDN Based Intra-Domain Routing and Resource Management Model","authors":"M. R. Çelenlioglu, H. A. Mantar","doi":"10.1109/IC2E.2015.47","DOIUrl":"https://doi.org/10.1109/IC2E.2015.47","url":null,"abstract":"Software Defined Networking (SDN) has become a promising network architecture that simplifies the network control, management and deployment of differentiated services. SDN architecture decouples control and data planes. Control functions are moved to a logically centralized entity called controller. The underlying infrastructure solely performs forwarding. Most of the previous studies focus on using SDN in data centers. In this paper, we propose scalable routing and resource management model for SDN based intra-domain networks. To virtualize the underlying network, we use pre-established multi-paths (PMP) between each ingress-egress switch. SDN-Controller performs admission control, routing, load balancing and path resizing functions based on these paths. The experimental results show that the proposed model significantly improves routing and signaling scalability, network resource utilization and decreases admission control time.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132112001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Tawalbeh, Y. Haddad, Omar Khamis, Fahd M. Al-Dosari, E. Benkhelifa
This paper proposes an efficient software based data possession mobile cloud computing framework. The proposed design utilizes the characteristics of two frameworks. The first one is the provable data possession design built for resource-constrained mobile devices and it uses the advantage of trusted computing technology, and the second framework is a lightweight resilient storage outsourcing design for mobile cloud computing systems. Our software based framework utilizes the strength aspects in both mentioned frameworks to gain better performance and security. The evaluation and comparison results showed that our design has better flexibility and efficiency than other related frameworks.
{"title":"Efficient Software-Based Mobile Cloud Computing Framework","authors":"L. Tawalbeh, Y. Haddad, Omar Khamis, Fahd M. Al-Dosari, E. Benkhelifa","doi":"10.1109/IC2E.2015.48","DOIUrl":"https://doi.org/10.1109/IC2E.2015.48","url":null,"abstract":"This paper proposes an efficient software based data possession mobile cloud computing framework. The proposed design utilizes the characteristics of two frameworks. The first one is the provable data possession design built for resource-constrained mobile devices and it uses the advantage of trusted computing technology, and the second framework is a lightweight resilient storage outsourcing design for mobile cloud computing systems. Our software based framework utilizes the strength aspects in both mentioned frameworks to gain better performance and security. The evaluation and comparison results showed that our design has better flexibility and efficiency than other related frameworks.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131391075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Software-Defined Networking (SDN) is revolutionizing data center networks for cloud computing with its ability to enable network virtualization and powerful network resource management that are crucial in any multi-tenant environment. In order to support sophisticated network control logic, the data plane of a switch should have a flexible Flow Table Pipeline (FTP). However, the FTP on state-of-the-art SDN switches is hardware-defined, which greatly limits the advantages of using FTP in cloud computing systems. This paper removes this limitation by introducing software-defined FTP (SDFTP), which provides an extremely flexible FTP as the southbound interface of the SDN control plane. SDFTP offers arbitrary number of pipeline stages and adaptive flow table sizing at runtime by building Software-Defined Flow Tables (SDFTs). Our analysis shows that SDFTP could create 138 times more adaptively sized pipeline stages than the hardware-defined data plane while maintaining comparable performance.
{"title":"Software-Defined Flow Table Pipeline","authors":"Xiaoye Sun, T. Ng, Guohui Wang","doi":"10.1109/IC2E.2015.52","DOIUrl":"https://doi.org/10.1109/IC2E.2015.52","url":null,"abstract":"Software-Defined Networking (SDN) is revolutionizing data center networks for cloud computing with its ability to enable network virtualization and powerful network resource management that are crucial in any multi-tenant environment. In order to support sophisticated network control logic, the data plane of a switch should have a flexible Flow Table Pipeline (FTP). However, the FTP on state-of-the-art SDN switches is hardware-defined, which greatly limits the advantages of using FTP in cloud computing systems. This paper removes this limitation by introducing software-defined FTP (SDFTP), which provides an extremely flexible FTP as the southbound interface of the SDN control plane. SDFTP offers arbitrary number of pipeline stages and adaptive flow table sizing at runtime by building Software-Defined Flow Tables (SDFTs). Our analysis shows that SDFTP could create 138 times more adaptively sized pipeline stages than the hardware-defined data plane while maintaining comparable performance.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"44 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129194579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With increasing demands for High Performance Computing (HPC), new ideas and methods are emerged to utilize computing resources more efficiently. Cloud Computing appears to provide benefits such as resource pooling, broad network access and cost efficiency for the HPC applications. However, moving the HPC applications to the cloud can face several key challenges, primarily, the virtualization overhead, multi-tenancy and network latency. Software-Defined Networking (SDN) as an emerging technology appears to pave the road and provide dynamic manipulation of cloud networking such as topology, routing, and bandwidth allocation. This paper presents a new scheme called ASETS which targets dynamic configuration and monitoring of cloud networking using SDN to improve the performance of HPC applications and in particular task scheduling for HPC as a service on the cloud (HPCaaS). Further, SETSA, (SDN-Empowered Task Scheduler Algorithm) is proposed as a novel task scheduling algorithm for the offered ASETS architecture. SETSA monitors the network bandwidth to take advantage of its changes when submitting tasks to the virtual machines. Empirical analysis of the algorithm in different case scenarios show that SETSA has significant potentials to improve the performance of HPCaaS platforms by increasing the bandwidth efficiency and decreasing task turnaround time. In addition, SETSAW, (SETSA Window) is proposed as an improvement of the SETSA algorithm.
{"title":"ASETS: A SDN Empowered Task Scheduling System for HPCaaS on the Cloud","authors":"S. Jamalian, H. Rajaei","doi":"10.1109/IC2E.2015.56","DOIUrl":"https://doi.org/10.1109/IC2E.2015.56","url":null,"abstract":"With increasing demands for High Performance Computing (HPC), new ideas and methods are emerged to utilize computing resources more efficiently. Cloud Computing appears to provide benefits such as resource pooling, broad network access and cost efficiency for the HPC applications. However, moving the HPC applications to the cloud can face several key challenges, primarily, the virtualization overhead, multi-tenancy and network latency. Software-Defined Networking (SDN) as an emerging technology appears to pave the road and provide dynamic manipulation of cloud networking such as topology, routing, and bandwidth allocation. This paper presents a new scheme called ASETS which targets dynamic configuration and monitoring of cloud networking using SDN to improve the performance of HPC applications and in particular task scheduling for HPC as a service on the cloud (HPCaaS). Further, SETSA, (SDN-Empowered Task Scheduler Algorithm) is proposed as a novel task scheduling algorithm for the offered ASETS architecture. SETSA monitors the network bandwidth to take advantage of its changes when submitting tasks to the virtual machines. Empirical analysis of the algorithm in different case scenarios show that SETSA has significant potentials to improve the performance of HPCaaS platforms by increasing the bandwidth efficiency and decreasing task turnaround time. In addition, SETSAW, (SETSA Window) is proposed as an improvement of the SETSA algorithm.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"371 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123483261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Kanstrén, S. Lehtonen, R. Savola, Hilkka Kukkohovi, Kimmo Hätönen
Operational security assurance of a networked system requires providing constant and up-to-date evidence of its operational state. In a cloud-based environment we deploy our services as virtual guests running on external hosts. As this environment is not under our full control, we have to find ways to provide assurance that the security information provided from this environment is accurate, and our software is running in the expected environment. In this paper, we present an architecture for providing increased confidence in measurements of such cloud-based deployments. The architecture is based on a set of deployed measurement probes and trusted platform modules (TPM) across both the host infrastructure and guest virtual machines. The TPM are used to verify the integrity of the probes and measurements they provide. This allows us to ensure that the system is running in the expected environment, the monitoring probes have not been tampered with, and the integrity of measurement data provided is maintained. Overall this gives us a basis for increased confidence in the security of running parts of our system in an external cloud-based environment.
{"title":"Architecture for High Confidence Cloud Security Monitoring","authors":"T. Kanstrén, S. Lehtonen, R. Savola, Hilkka Kukkohovi, Kimmo Hätönen","doi":"10.1109/IC2E.2015.21","DOIUrl":"https://doi.org/10.1109/IC2E.2015.21","url":null,"abstract":"Operational security assurance of a networked system requires providing constant and up-to-date evidence of its operational state. In a cloud-based environment we deploy our services as virtual guests running on external hosts. As this environment is not under our full control, we have to find ways to provide assurance that the security information provided from this environment is accurate, and our software is running in the expected environment. In this paper, we present an architecture for providing increased confidence in measurements of such cloud-based deployments. The architecture is based on a set of deployed measurement probes and trusted platform modules (TPM) across both the host infrastructure and guest virtual machines. The TPM are used to verify the integrity of the probes and measurements they provide. This allows us to ensure that the system is running in the expected environment, the monitoring probes have not been tampered with, and the integrity of measurement data provided is maintained. Overall this gives us a basis for increased confidence in the security of running parts of our system in an external cloud-based environment.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114569675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Searchable encryption allows a client to encrypt its document collection in such a way that the encrypted collection can still be searched. The most immediate application of searchable encryption is privacy / confidentiality preserving cloud storage, where it enables a client to securely outsource its document collection to an untrusted cloud provider without sacrificing the ability to search over it. Our research focuses on developing a novel searchable encryption framework that allows the cloud server to perform multi-keyword ranked search as well as substring search incorporating position information. We present some advances that we have accomplished in this area. We then layout our planned research work and a timeline to accomplish this.
{"title":"Towards a Practical and Efficient Search over Encrypted Data in the Cloud","authors":"M. Strizhov","doi":"10.1109/IC2E.2015.86","DOIUrl":"https://doi.org/10.1109/IC2E.2015.86","url":null,"abstract":"Searchable encryption allows a client to encrypt its document collection in such a way that the encrypted collection can still be searched. The most immediate application of searchable encryption is privacy / confidentiality preserving cloud storage, where it enables a client to securely outsource its document collection to an untrusted cloud provider without sacrificing the ability to search over it. Our research focuses on developing a novel searchable encryption framework that allows the cloud server to perform multi-keyword ranked search as well as substring search incorporating position information. We present some advances that we have accomplished in this area. We then layout our planned research work and a timeline to accomplish this.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114748857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jatinder Singh, Thomas Pasquier, J. Bacon, D. Eyers
Security is an ongoing challenge in cloud computing. Currently, cloud consumers have few mechanisms for managing their data within the cloud provider's infrastructure. Information Flow Control (IFC) involves attaching labels to data, to govern its flow throughout a system. We have worked on kernel-level IFC enforcement to protect data flows within a virtual machine (VM). This paper makes the case for, and demonstrates the feasibility of an IFC-enabled messaging middleware, to enforce IFC within and across applications, containers, VMs, and hosts. We detail how such middleware can integrate with local (kernel) enforcement mechanisms, and highlight the benefits of separating data management policy from application/service-logic.
{"title":"Integrating Messaging Middleware and Information Flow Control","authors":"Jatinder Singh, Thomas Pasquier, J. Bacon, D. Eyers","doi":"10.1109/IC2E.2015.13","DOIUrl":"https://doi.org/10.1109/IC2E.2015.13","url":null,"abstract":"Security is an ongoing challenge in cloud computing. Currently, cloud consumers have few mechanisms for managing their data within the cloud provider's infrastructure. Information Flow Control (IFC) involves attaching labels to data, to govern its flow throughout a system. We have worked on kernel-level IFC enforcement to protect data flows within a virtual machine (VM). This paper makes the case for, and demonstrates the feasibility of an IFC-enabled messaging middleware, to enforce IFC within and across applications, containers, VMs, and hosts. We detail how such middleware can integrate with local (kernel) enforcement mechanisms, and highlight the benefits of separating data management policy from application/service-logic.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116642372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amardeep Mehta, J. Durango, Johan Tordsson, E. Elmroth
We investigate methods for detection of rapid workload increases (load spikes) for cloud workloads. Such rapid and unexpected workload spikes are a main cause for poor performance or even crashing applications as the allocated cloud resources become insufficient. To detect the spikes early is fundamental to perform corrective management actions, like allocating additional resources, before the spikes become large enough to cause problems. For this, we propose a number of methods for early spike detection, based on established techniques from adaptive signal processing. A comparative evaluation shows, for example, to what extent the different methods manage to detect the spikes, how early the detection is made, and how frequently they falsely report spikes.
{"title":"Online Spike Detection in Cloud Workloads","authors":"Amardeep Mehta, J. Durango, Johan Tordsson, E. Elmroth","doi":"10.1109/IC2E.2015.50","DOIUrl":"https://doi.org/10.1109/IC2E.2015.50","url":null,"abstract":"We investigate methods for detection of rapid workload increases (load spikes) for cloud workloads. Such rapid and unexpected workload spikes are a main cause for poor performance or even crashing applications as the allocated cloud resources become insufficient. To detect the spikes early is fundamental to perform corrective management actions, like allocating additional resources, before the spikes become large enough to cause problems. For this, we propose a number of methods for early spike detection, based on established techniques from adaptive signal processing. A comparative evaluation shows, for example, to what extent the different methods manage to detect the spikes, how early the detection is made, and how frequently they falsely report spikes.","PeriodicalId":395715,"journal":{"name":"2015 IEEE International Conference on Cloud Engineering","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117173649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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