Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245972
Haitao Li, Jiangchuan Liu, Ke Xu, Song Wen
Recent statistics suggest that online social network (OSN) users regularly share video contents from video sharing sites (VSSes), and a significant amount of views of VSSes are indeed from OSN users nowadays. By crawling and comparing the statistics of same videos shared in both RenRen (the largest Facebook-like OSN in China) and Youku (the largest Youtube-like VSS in China), we find that the huge and distinguished video requests from OSNs have substantially changed the workload of VSSes. In particular, OSNs amplify the skewness of video popularity so largely that about 0.31% most popular videos account for 80% of total views. Another interesting phenomenon is that many popular videos in VSSes may not receive many requests in OSNs. To further understand these findings, we track the propagation process of videos shared in RenRen since their introduction to this OSN, and analyze the effect of potential parameters to such process, including the number of initiators (users who bring the video to the OSN directly from a VSS), branching factor (the number of users who watch the friend's shared video), and share rate (the probability that the viewers of a video will further share this video). Beyond our expectation, none of these factors determine a video's popularity in an OSN. Instead, it shows great randomness for the number of a video's potential requests when it is shared to an OSN. By modifying the basic Galton-Watson stochastic branching process, we develop a simple yet effective model to simulate the video propagation process in an OSN. Simulation results show that it can well capture the randomness of a video's popularity and the skewed video popularity distribution.
{"title":"Understanding video propagation in online social networks","authors":"Haitao Li, Jiangchuan Liu, Ke Xu, Song Wen","doi":"10.1109/IWQoS.2012.6245972","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245972","url":null,"abstract":"Recent statistics suggest that online social network (OSN) users regularly share video contents from video sharing sites (VSSes), and a significant amount of views of VSSes are indeed from OSN users nowadays. By crawling and comparing the statistics of same videos shared in both RenRen (the largest Facebook-like OSN in China) and Youku (the largest Youtube-like VSS in China), we find that the huge and distinguished video requests from OSNs have substantially changed the workload of VSSes. In particular, OSNs amplify the skewness of video popularity so largely that about 0.31% most popular videos account for 80% of total views. Another interesting phenomenon is that many popular videos in VSSes may not receive many requests in OSNs. To further understand these findings, we track the propagation process of videos shared in RenRen since their introduction to this OSN, and analyze the effect of potential parameters to such process, including the number of initiators (users who bring the video to the OSN directly from a VSS), branching factor (the number of users who watch the friend's shared video), and share rate (the probability that the viewers of a video will further share this video). Beyond our expectation, none of these factors determine a video's popularity in an OSN. Instead, it shows great randomness for the number of a video's potential requests when it is shared to an OSN. By modifying the basic Galton-Watson stochastic branching process, we develop a simple yet effective model to simulate the video propagation process in an OSN. Simulation results show that it can well capture the randomness of a video's popularity and the skewed video popularity distribution.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123335359","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245982
Umamaheswari Devi, Ramana Polavarapu, Malolan Chetlur, S. Kalyanaraman
Video objects are much larger in size than traditional web objects and tend not to be viewed in entirety. Hence, caching them partially is a promising approach. Also, the projected growth in video traffic over wireless cellular networks calls for resource-efficient caching mechanisms in the wireless edge to lower traffic over the cellular backhaul and peering links and their associated costs. An evaluation of traditional partial caching solutions proposed in the literature shows that known solutions are not robust to video viewing patterns, increasing object pool size, changing object popularity, or limitation in the resources available for caching at the wireless network elements. In this paper, to overcome the limitations, we propose a novel approach that adopts a flexible segmentation policy and generalizes both LRU and LFU when applied to segmented accesses, and in our simulations, is shown to significantly lower wireless backhaul traffic (by around 20-30% and in some cases even higher).
{"title":"On the partial caching of streaming video","authors":"Umamaheswari Devi, Ramana Polavarapu, Malolan Chetlur, S. Kalyanaraman","doi":"10.1109/IWQoS.2012.6245982","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245982","url":null,"abstract":"Video objects are much larger in size than traditional web objects and tend not to be viewed in entirety. Hence, caching them partially is a promising approach. Also, the projected growth in video traffic over wireless cellular networks calls for resource-efficient caching mechanisms in the wireless edge to lower traffic over the cellular backhaul and peering links and their associated costs. An evaluation of traditional partial caching solutions proposed in the literature shows that known solutions are not robust to video viewing patterns, increasing object pool size, changing object popularity, or limitation in the resources available for caching at the wireless network elements. In this paper, to overcome the limitations, we propose a novel approach that adopts a flexible segmentation policy and generalizes both LRU and LFU when applied to segmented accesses, and in our simulations, is shown to significantly lower wireless backhaul traffic (by around 20-30% and in some cases even higher).","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116520215","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245998
Libin Yang, W. Lou
In this paper, we provide a comprehensive treatment of QoS guarantee for mobile streaming applications through a contract-ruled approach. We envision a peer-to-peer streaming system as a QoS trading market, where the involved parties, Services Provider (SP), End User (EU) and assisting peers, are all real economic entities that are organized with contractual constraints for achieving a stable and guaranteed QoS output. The QoS trading in the market is classified into two parts, a basic contract that establishes the business agreement between an interested EU and a SP and a subcontract that achieves a desired joint QoS output. The proposed scheme can benefit all parties.
{"title":"A contract-ruled economic model for QoS guarantee in mobile peer-to-peer streaming services","authors":"Libin Yang, W. Lou","doi":"10.1109/IWQoS.2012.6245998","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245998","url":null,"abstract":"In this paper, we provide a comprehensive treatment of QoS guarantee for mobile streaming applications through a contract-ruled approach. We envision a peer-to-peer streaming system as a QoS trading market, where the involved parties, Services Provider (SP), End User (EU) and assisting peers, are all real economic entities that are organized with contractual constraints for achieving a stable and guaranteed QoS output. The QoS trading in the market is classified into two parts, a basic contract that establishes the business agreement between an interested EU and a SP and a subcontract that achieves a desired joint QoS output. The proposed scheme can benefit all parties.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127387327","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245994
Shan-Hsiang Shen, Aditya Akella
Network resources are often limited, so how to use them efficiently is an issue that arises in many important scenarios. Many recent proposals rely on a central controller to carefully orchestrate resources across multiple network locations. The central controller gathers network information and relative levels of usage of different resources and calculates optimized task allocation arrangements to maximize some global benefit. Examples of architectures that use this framework include coordinated sampling (cSamp [1]) and redundancy elimination (SmartRE [2]). However, a centralized solution creates practical problems as it is susceptible to overload, and the controller is a single point of failure. In this paper, we present a distributed solution called decor that achieves global optimization based on local information that closes to centralized approaches in terms of performance. In decor, the responsibility of resource monitoring and information gathering is spread among multiple nodes; thus, no single point is overloaded. Allocation of tasks is also done in a similar distributed fashion. decor can easily scale up to large networks, and the partial network failures do not affect DECOR's functioning in other parts of the network. decor can be applied to most of path-based applications. We describe in detail how to apply it to distributed SmartRE and implement it in the Click software router.
{"title":"DECOR: A distributed coordinated resource monitoring system","authors":"Shan-Hsiang Shen, Aditya Akella","doi":"10.1109/IWQoS.2012.6245994","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245994","url":null,"abstract":"Network resources are often limited, so how to use them efficiently is an issue that arises in many important scenarios. Many recent proposals rely on a central controller to carefully orchestrate resources across multiple network locations. The central controller gathers network information and relative levels of usage of different resources and calculates optimized task allocation arrangements to maximize some global benefit. Examples of architectures that use this framework include coordinated sampling (cSamp [1]) and redundancy elimination (SmartRE [2]). However, a centralized solution creates practical problems as it is susceptible to overload, and the controller is a single point of failure. In this paper, we present a distributed solution called decor that achieves global optimization based on local information that closes to centralized approaches in terms of performance. In decor, the responsibility of resource monitoring and information gathering is spread among multiple nodes; thus, no single point is overloaded. Allocation of tasks is also done in a similar distributed fashion. decor can easily scale up to large networks, and the partial network failures do not affect DECOR's functioning in other parts of the network. decor can be applied to most of path-based applications. We describe in detail how to apply it to distributed SmartRE and implement it in the Click software router.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130255876","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245985
D. Giatsios, I. Koutsopoulos, T. Korakis
Queue-based cross-layer optimization algorithms have recently been a subject of intensive research in wireless networks. Their purpose is to guarantee stable operation and to achieve some form of fairness among users, whenever the traffic demand exceeds network capacity. Despite the plethora of work in this field, the scenario where one or more nodes declare false queue backlog values in order to gain throughput advantage remains unexplored. In this paper we examine this type of selfish misbehavior, concentrating on a specific class of algorithms, the so-called quadratic Lyapunov-function-based algorithms (QLA). In particular, the effect of backlog misreporting on a single-hop access network with contending stations is evaluated through simulations. A simple framework for the detection of misbehaving nodes is proposed, under the assumption that the access-point is aware of the utility functions of the stations. The detection approach exploits the fact that under QLA the throughput of a node must be approximately equal to an “expected” value, derived from the reported queue backlogs.
{"title":"Dishonest reporting in queue-based cross-layer network optimization","authors":"D. Giatsios, I. Koutsopoulos, T. Korakis","doi":"10.1109/IWQoS.2012.6245985","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245985","url":null,"abstract":"Queue-based cross-layer optimization algorithms have recently been a subject of intensive research in wireless networks. Their purpose is to guarantee stable operation and to achieve some form of fairness among users, whenever the traffic demand exceeds network capacity. Despite the plethora of work in this field, the scenario where one or more nodes declare false queue backlog values in order to gain throughput advantage remains unexplored. In this paper we examine this type of selfish misbehavior, concentrating on a specific class of algorithms, the so-called quadratic Lyapunov-function-based algorithms (QLA). In particular, the effect of backlog misreporting on a single-hop access network with contending stations is evaluated through simulations. A simple framework for the detection of misbehaving nodes is proposed, under the assumption that the access-point is aware of the utility functions of the stations. The detection approach exploits the fact that under QLA the throughput of a node must be approximately equal to an “expected” value, derived from the reported queue backlogs.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131678297","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245967
Haiyang Wang, R. Shea, Feng Wang, Jiangchuan Liu
Powered by cloud computing, Dropbox not only provides reliable file storage but also enables effective file synchronization and user collaboration. This new generation of service, beyond conventional client/server or peer-to-peer file hosting with storage only, has attracted a vast number of Internet users. It is however known that the synchronization delay of Dropbox-like systems is increasing with their expansion, often beyond the accepted level for practical collaboration. In this paper, we present an initial measurement to understand the design and performance bottleneck of the proprietary Dropbox system. Our measurement identifies the cloud servers/instances utilized by Dropbox, revealing its hybrid design with both Amazon's S3 (for storage) and Amazon's EC2 (for computation). The mix of bandwidth-intensive tasks (such as content delivery) and computation-intensive tasks (such as compare hash values for the contents) in Dropbox enables seamless collaboration and file synchronization among multiple users; yet their interference, revealed in our experiments, creates a severe bottleneck that prolongs the synchronization delay with virtual machines in the cloud, which has not seen in conventional physical machines. We thus re-model the resource provisioning problem in the Dropbox-like systems and present an interference-aware solution that smartly allocates the Dropbox tasks to different cloud instances. Evaluation results show that our solution remarkably reduces the synchronization delay for this new generation of file hosting service.
{"title":"On the impact of virtualization on Dropbox-like cloud file storage/synchronization services","authors":"Haiyang Wang, R. Shea, Feng Wang, Jiangchuan Liu","doi":"10.1109/IWQoS.2012.6245967","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245967","url":null,"abstract":"Powered by cloud computing, Dropbox not only provides reliable file storage but also enables effective file synchronization and user collaboration. This new generation of service, beyond conventional client/server or peer-to-peer file hosting with storage only, has attracted a vast number of Internet users. It is however known that the synchronization delay of Dropbox-like systems is increasing with their expansion, often beyond the accepted level for practical collaboration. In this paper, we present an initial measurement to understand the design and performance bottleneck of the proprietary Dropbox system. Our measurement identifies the cloud servers/instances utilized by Dropbox, revealing its hybrid design with both Amazon's S3 (for storage) and Amazon's EC2 (for computation). The mix of bandwidth-intensive tasks (such as content delivery) and computation-intensive tasks (such as compare hash values for the contents) in Dropbox enables seamless collaboration and file synchronization among multiple users; yet their interference, revealed in our experiments, creates a severe bottleneck that prolongs the synchronization delay with virtual machines in the cloud, which has not seen in conventional physical machines. We thus re-model the resource provisioning problem in the Dropbox-like systems and present an interference-aware solution that smartly allocates the Dropbox tasks to different cloud instances. Evaluation results show that our solution remarkably reduces the synchronization delay for this new generation of file hosting service.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121209096","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245979
Yipeng Zhou, T. Fu, D. Chiu
We consider a P2P-assisted content storage and delivery system to support a streaming Video-on-Demand (VoD) service. In this system, the peers are part of the service provider (e.g. set-top boxes) with limited storage space. Servers with ample storage and bandwidth are deployed to guarantee the availability and quality, but it is desirable to minimize the server utilization to reduce costs. Based on experience of implementing a deployed P2P VoD system, it was suggested in [1] that a movie's availability should be proportional to the movie's popularity. Based on further refinement, it is observed [2] that performance can be further improved by more (than proportional) availability for cold movies in P2P system. In this paper, we show that as the number of movies becomes large and there is some skewness in movie popularity, then one cannot expect the P2P part of the system to reduce server load as well as provide availability to all movies at the same time. It is a trade-off between coverage of movies and streaming throughput provided by the P2P system. If the goal is to minimize server load, under some reasonable conditions, we show that it is best to store and replicate only the hottest K* movies in the P2P part of the system. We also study the relationship between the skewness of the movie popularity distribution, P2P resources and the value of K*. Finally, we use simulation to validate our results.
{"title":"Division-of-labor between server and P2P for streaming VoD","authors":"Yipeng Zhou, T. Fu, D. Chiu","doi":"10.1109/IWQoS.2012.6245979","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245979","url":null,"abstract":"We consider a P2P-assisted content storage and delivery system to support a streaming Video-on-Demand (VoD) service. In this system, the peers are part of the service provider (e.g. set-top boxes) with limited storage space. Servers with ample storage and bandwidth are deployed to guarantee the availability and quality, but it is desirable to minimize the server utilization to reduce costs. Based on experience of implementing a deployed P2P VoD system, it was suggested in [1] that a movie's availability should be proportional to the movie's popularity. Based on further refinement, it is observed [2] that performance can be further improved by more (than proportional) availability for cold movies in P2P system. In this paper, we show that as the number of movies becomes large and there is some skewness in movie popularity, then one cannot expect the P2P part of the system to reduce server load as well as provide availability to all movies at the same time. It is a trade-off between coverage of movies and streaming throughput provided by the P2P system. If the goal is to minimize server load, under some reasonable conditions, we show that it is best to store and replicate only the hottest K* movies in the P2P part of the system. We also study the relationship between the skewness of the movie popularity distribution, P2P resources and the value of K*. Finally, we use simulation to validate our results.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127814750","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245970
A. Jarray, A. Karmouch
In this paper, our focus is on the embedding problem which consists on the mapping of VN resources onto physical infrastructure network. More specifically, we consider the problem of optimizing the Physical Infrastructure Provider's (PIP) profit while minimizing the dissatisfaction of VN customers. We propose to dynamically partition the PIP resources over VN requests belonging to different Quality of Service (QoS) classes using periodical auction mechanism. We formulate the dynamic embedding problem as an Integer Linear Program (ILP) that allows us to: (i) maximize the PIP profit, and (ii) calculate the optimal embedding scheme of VN requests without disruption of those previously accepted in order to uphold QoS guarantees.
{"title":"Periodical auctioning for QoS aware virtual network embedding","authors":"A. Jarray, A. Karmouch","doi":"10.1109/IWQoS.2012.6245970","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245970","url":null,"abstract":"In this paper, our focus is on the embedding problem which consists on the mapping of VN resources onto physical infrastructure network. More specifically, we consider the problem of optimizing the Physical Infrastructure Provider's (PIP) profit while minimizing the dissatisfaction of VN customers. We propose to dynamically partition the PIP resources over VN requests belonging to different Quality of Service (QoS) classes using periodical auction mechanism. We formulate the dynamic embedding problem as an Integer Linear Program (ILP) that allows us to: (i) maximize the PIP profit, and (ii) calculate the optimal embedding scheme of VN requests without disruption of those previously accepted in order to uphold QoS guarantees.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133272926","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245984
Vijay Gabale, P. Dutta, Ravi Kokku, S. Kalyanaraman
The Internet is witnessing a rapid increase in video traffic. Due to the scalability and the cost-savings offered by cloud-computing, Internet video service providers are increasingly delivering their content from multi-tenant cloud data centers. One of the major challenges faced by such a video service provider is the management of the Quality-of-Experience (QoE) of the end-users in the presence of Variable Bit Rate (VBR) video flows, time varying network conditions in the Internet, and the bounded egress bandwidth provided by the data center. To this end, we present InSite, a light-weight and easy-to-deploy solution for managing the QoE of a set of video flows of a service provider, which are served from a data center. InSite is deployed at the egress of a data center, between the video servers and the clients, and manages the video flows that are transmitted over TCP. The solution uses a novel generalized binary search technique to concurrently search for the appropriate flow rates for a set of flows, with the goal of maximizing the QoE-fairness across the flows, as opposed to TCP-fairness. The search takes into account the total egress bandwidth allocated for the set of video flows at the data center, the unknown and possibly time-varying capacities of any remote bottleneck links, and the playout buffer sizes of the video flows. The solution is also designed to operate with minimal modifications to the video servers and the clients. In our evaluations using extensive ns-3 simulations and a testbed implementation for serving videos over TCP, we observe that deploying InSite achieves several folds reduction in playout stalls over a system without InSite.
{"title":"InSite: QoE-aware video delivery from cloud data centers","authors":"Vijay Gabale, P. Dutta, Ravi Kokku, S. Kalyanaraman","doi":"10.1109/IWQoS.2012.6245984","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245984","url":null,"abstract":"The Internet is witnessing a rapid increase in video traffic. Due to the scalability and the cost-savings offered by cloud-computing, Internet video service providers are increasingly delivering their content from multi-tenant cloud data centers. One of the major challenges faced by such a video service provider is the management of the Quality-of-Experience (QoE) of the end-users in the presence of Variable Bit Rate (VBR) video flows, time varying network conditions in the Internet, and the bounded egress bandwidth provided by the data center. To this end, we present InSite, a light-weight and easy-to-deploy solution for managing the QoE of a set of video flows of a service provider, which are served from a data center. InSite is deployed at the egress of a data center, between the video servers and the clients, and manages the video flows that are transmitted over TCP. The solution uses a novel generalized binary search technique to concurrently search for the appropriate flow rates for a set of flows, with the goal of maximizing the QoE-fairness across the flows, as opposed to TCP-fairness. The search takes into account the total egress bandwidth allocated for the set of video flows at the data center, the unknown and possibly time-varying capacities of any remote bottleneck links, and the playout buffer sizes of the video flows. The solution is also designed to operate with minimal modifications to the video servers and the clients. In our evaluations using extensive ns-3 simulations and a testbed implementation for serving videos over TCP, we observe that deploying InSite achieves several folds reduction in playout stalls over a system without InSite.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116747254","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}
Pub Date : 2012-06-04DOI: 10.1109/IWQoS.2012.6245996
Zhenyu Wu, Yueping Zhang, V. Singh, Guofei Jiang, Haining Wang
With the ever-increasing number and complexity of applications deployed in data centers, the underlying network infrastructure can no longer sustain such a trend and exhibits several problems, such as resource fragmentation and low bisection bandwidth. In pursuit of a real-world applicable data center network (DCN) optimization approach that continuously maintains balanced network performance with high cost effectiveness, we design a topology independent resource allocation and optimization approach, NetDEO. Based on a swarm intelligence optimization model, NetDEO improves the scalability of the DCN by relocating virtual machines (VMs) and matching resource demand and availability. NetDEO is capable of (1) incrementally optimizing an existing VM placement in a data center; (2) deriving optimal deployment plans for newly added VMs; and (3) providing hardware upgrade suggestions and allowing the DCN to evolve as the workload changes over time. We evaluate the performance of NetDEO using realistic workload traces and simulated large-scale DCN under various topologies.
{"title":"NetDEO: Automating network design, evolution, and optimization","authors":"Zhenyu Wu, Yueping Zhang, V. Singh, Guofei Jiang, Haining Wang","doi":"10.1109/IWQoS.2012.6245996","DOIUrl":"https://doi.org/10.1109/IWQoS.2012.6245996","url":null,"abstract":"With the ever-increasing number and complexity of applications deployed in data centers, the underlying network infrastructure can no longer sustain such a trend and exhibits several problems, such as resource fragmentation and low bisection bandwidth. In pursuit of a real-world applicable data center network (DCN) optimization approach that continuously maintains balanced network performance with high cost effectiveness, we design a topology independent resource allocation and optimization approach, NetDEO. Based on a swarm intelligence optimization model, NetDEO improves the scalability of the DCN by relocating virtual machines (VMs) and matching resource demand and availability. NetDEO is capable of (1) incrementally optimizing an existing VM placement in a data center; (2) deriving optimal deployment plans for newly added VMs; and (3) providing hardware upgrade suggestions and allowing the DCN to evolve as the workload changes over time. We evaluate the performance of NetDEO using realistic workload traces and simulated large-scale DCN under various topologies.","PeriodicalId":178333,"journal":{"name":"2012 IEEE 20th International Workshop on Quality of Service","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115261247","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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