Dr. rer. nat. Lam Dinh-Xuan

Oct 2014 - Oct 2018

Dissertation:

Quality of Experience Assessment of Cloud Applications and Performance Evaluation of VNF-Based QoE Monitoring

Publications

2018[ to top ]

Quality of Experience Assessment of Cloud Applications and Performance Evaluation of VNF-Based QoE Monitoring Dinh-Xuan, Lam PhD thesis, Universitiy of Würzburg. (2018, October).
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@phdthesis{info3-dissertation-2018-2, author = {Dinh-Xuan, Lam}, keywords = {sys:hidden:supervisor:phuoc.tran-gia}, month = 10, school = {Universitiy of Würzburg}, title = {Quality of Experience Assessment of Cloud Applications and Performance Evaluation of VNF-Based QoE Monitoring}, year = 2018 }

%0 Thesis %1 info3-dissertation-2018-2 %A Dinh-Xuan, Lam %D 2018 %T Quality of Experience Assessment of Cloud Applications and Performance Evaluation of VNF-Based QoE Monitoring
Impact of VNF Placements on QoE Monitoring in the Cloud Dinh-Xuan, Lam; Popp, Christian; Burger, Valentin; Wamser, Florian; Hoßfeld, Tobias in International Journal of Network Management (2018). (NEM-18-0120.R1)
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@article{info3-article-2018-6, author = {Dinh-Xuan, Lam and Popp, Christian and Burger, Valentin and Wamser, Florian and Hoßfeld, Tobias}, journal = {International Journal of Network Management}, keywords = {video-quality}, month = 10, number = {NEM-18-0120.R1}, title = {Impact of VNF Placements on QoE Monitoring in the Cloud}, year = 2018 }

%0 Journal Article %1 info3-article-2018-6 %A Dinh-Xuan, Lam %A Popp, Christian %A Burger, Valentin %A Wamser, Florian %A Hoßfeld, Tobias %D 2018 %J International Journal of Network Management %N NEM-18-0120.R1 %T Impact of VNF Placements on QoE Monitoring in the Cloud
Orchestration and Monitoring in Fog Computing for Personal Edge Cloud Service Support Wamser, Florian; Lombardo, Chiara; Vassilakis, Constantinos; Dinh-Xuan, Lam; Lago, Paolo; Bruschi, Roberto; Tran-Gia, Phuoc in 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN) (2018).
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@inproceedings{info3-inproceedings-2018-30, author = {Wamser, Florian and Lombardo, Chiara and Vassilakis, Constantinos and Dinh-Xuan, Lam and Lago, Paolo and Bruschi, Roberto and Tran-Gia, Phuoc}, booktitle = {2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN)}, keywords = {can}, month = 6, title = {Orchestration and Monitoring in Fog Computing for Personal Edge Cloud Service Support}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-30 %A Wamser, Florian %A Lombardo, Chiara %A Vassilakis, Constantinos %A Dinh-Xuan, Lam %A Lago, Paolo %A Bruschi, Roberto %A Tran-Gia, Phuoc %B 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN) %D 2018 %T Orchestration and Monitoring in Fog Computing for Personal Edge Cloud Service Support
Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud Dinh-Xuan, Lam; Seufert, Michael; Wamser, Florian; Vassilakis, Constantinos; Zafeiropoulos, Anastasios; Tran-Gia, Phuoc in 30th International Teletraffic Congress (ITC30) (2018).
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The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.

@inproceedings{info3-inproceedings-2018-14, abstract = {The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.}, address = {Vienna, Austria}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Vassilakis, Constantinos and Zafeiropoulos, Anastasios and Tran-Gia, Phuoc}, booktitle = {30th International Teletraffic Congress (ITC30)}, keywords = {can}, month = 9, title = {Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-14 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Vassilakis, Constantinos %A Zafeiropoulos, Anastasios %A Tran-Gia, Phuoc %B 30th International Teletraffic Congress (ITC30) %C Vienna, Austria %D 2018 %T Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud %X The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.
A Generic Approach to Video Buffer Modeling using Discrete-Time Analysis Burger, Valentin; Zinner, Thomas; Dinh-Xuan, Lam; Wamser, Florian; Tran-Gia, Phuoc in ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) (2018). 14(33) 23.
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@article{info3-article-2018-1, author = {Burger, Valentin and Zinner, Thomas and Dinh-Xuan, Lam and Wamser, Florian and Tran-Gia, Phuoc}, journal = {ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)}, keywords = {sys:hidden:article}, month = 4, number = 33, pages = 23, title = {A Generic Approach to Video Buffer Modeling using Discrete-Time Analysis}, volume = 14, year = 2018 }

%0 Journal Article %1 info3-article-2018-1 %A Burger, Valentin %A Zinner, Thomas %A Dinh-Xuan, Lam %A Wamser, Florian %A Tran-Gia, Phuoc %D 2018 %J ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) %N 33 %P 23 %T A Generic Approach to Video Buffer Modeling using Discrete-Time Analysis %V 14

2017[ to top ]

Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF Dinh-Xuan, Lam; Seufert, Michael; Wamser, Florian; Tran-Gia, Phuoc in 1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management) (2017).
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The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.

@inproceedings{info3-inproceedings-2017-3, abstract = {The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.}, address = {Lisbon, Portugal}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Tran-Gia, Phuoc}, booktitle = {1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management)}, keywords = {can}, month = 5, title = {Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-3 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Tran-Gia, Phuoc %B 1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management) %C Lisbon, Portugal %D 2017 %T Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF %X The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.

2016[ to top ]

QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service Dinh-Xuan, Lam; Seufert, Michael; Wamser, Florian; Tran-Gia, Phuoc in IEEE 6th International Conference on Communications and Electronics (ICCE) (2016).
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The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.

@inproceedings{info3-inproceedings-2016-16, abstract = {The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.}, address = {Ha Long, Vietnam}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Tran-Gia, Phuoc}, booktitle = {IEEE 6th International Conference on Communications and Electronics (ICCE)}, keywords = {can}, month = 7, title = {QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-16 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Tran-Gia, Phuoc %B IEEE 6th International Conference on Communications and Electronics (ICCE) %C Ha Long, Vietnam %D 2016 %T QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service %X The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.

2015[ to top ]

Analyzing the Impact of Delay and Packet Loss on Google Docs Dinh-Xuan, Lam; Schwartz, Christian; Hirth, Matthias; Wamser, Florian; Truong Thu, Huong in 7th International Conference on Mobile Networks and Management (2015).
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Software as a Service allows end users to use complex soft- ware directly from their browsers, transferring heavy computation to servers in the cloud. One use of this paradigm is word processing, former a classic use cases of Thin-Client computing. Similar to Thin-Client systems, the network parameters are an important influence factor for the cloud application performance. In this paper, we study Google Docs as an example for online word processing tools. We consider a traditional single user scenario as well as a collaborative scenario with two users working on one document simultaneously. We identify multiple relevant sub-processes per scenario as performance metrics and use a testbed to automatically evaluate the performance of Google Docs under varying network parameters. The main contributions of the paper are (1) the quantification of the impact of network parameters such as delay and packet loss on application performance metrics for both scenarios and (2) linear regression models to derive the application performance for giving network parameters.

@inproceedings{info3-inproceedings-2015-522, abstract = {Software as a Service allows end users to use complex soft- ware directly from their browsers, transferring heavy computation to servers in the cloud. One use of this paradigm is word processing, former a classic use cases of Thin-Client computing. Similar to Thin-Client systems, the network parameters are an important influence factor for the cloud application performance. In this paper, we study Google Docs as an example for online word processing tools. We consider a traditional single user scenario as well as a collaborative scenario with two users working on one document simultaneously. We identify multiple relevant sub-processes per scenario as performance metrics and use a testbed to automatically evaluate the performance of Google Docs under varying network parameters. The main contributions of the paper are (1) the quantification of the impact of network parameters such as delay and packet loss on application performance metrics for both scenarios and (2) linear regression models to derive the application performance for giving network parameters.}, address = {Santander, Spain}, author = {Dinh-Xuan, Lam and Schwartz, Christian and Hirth, Matthias and Wamser, Florian and Truong Thu, Huong}, booktitle = {7th International Conference on Mobile Networks and Management}, keywords = {can}, month = 9, title = {Analyzing the Impact of Delay and Packet Loss on Google Docs}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-522 %A Dinh-Xuan, Lam %A Schwartz, Christian %A Hirth, Matthias %A Wamser, Florian %A Truong Thu, Huong %B 7th International Conference on Mobile Networks and Management %C Santander, Spain %D 2015 %T Analyzing the Impact of Delay and Packet Loss on Google Docs %X Software as a Service allows end users to use complex soft- ware directly from their browsers, transferring heavy computation to servers in the cloud. One use of this paradigm is word processing, former a classic use cases of Thin-Client computing. Similar to Thin-Client systems, the network parameters are an important influence factor for the cloud application performance. In this paper, we study Google Docs as an example for online word processing tools. We consider a traditional single user scenario as well as a collaborative scenario with two users working on one document simultaneously. We identify multiple relevant sub-processes per scenario as performance metrics and use a testbed to automatically evaluate the performance of Google Docs under varying network parameters. The main contributions of the paper are (1) the quantification of the impact of network parameters such as delay and packet loss on application performance metrics for both scenarios and (2) linear regression models to derive the application performance for giving network parameters.

Dr. rer. nat. Lam Dinh-Xuan

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