In typical video mash-up systems, a group of source videos are compiled off-line into a single composite object. This improves rendering performance, but limits the possibilities for dynamic composition of personalized content. This paper discusses systems and network issues for enabling client-side dynamic composition of video mash-ups. In particular, this paper describes a novel algorithm to support accurate, low-delay seamless composition of independent clips. We report on an intelligent application-steered scheme that allows system layers to prefetch and discard predicted frames before the rendering moment of indexed content. This approach unifies application-level quality-of-experience specification with system layer quality-of-service processing. To evaluate our scheme, several experiments are conducted and substantial performance improvements are observed in terms of accuracy and low delay.
{"title":"Accurate and low-delay seeking within and across mash-ups of highly-compressed videos","authors":"Bo Gao, Jack Jansen, Pablo César, D. Bulterman","doi":"10.1145/1989240.1989266","DOIUrl":"https://doi.org/10.1145/1989240.1989266","url":null,"abstract":"In typical video mash-up systems, a group of source videos are compiled off-line into a single composite object. This improves rendering performance, but limits the possibilities for dynamic composition of personalized content. This paper discusses systems and network issues for enabling client-side dynamic composition of video mash-ups. In particular, this paper describes a novel algorithm to support accurate, low-delay seamless composition of independent clips. We report on an intelligent application-steered scheme that allows system layers to prefetch and discard predicted frames before the rendering moment of indexed content. This approach unifies application-level quality-of-experience specification with system layer quality-of-service processing. To evaluate our scheme, several experiments are conducted and substantial performance improvements are observed in terms of accuracy and low delay.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"127 45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117171761","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}
The pervasive usage of mobile devices and wireless networking support have enabled more and more Internet stream- ing services to all kinds of heterogeneous mobile devices. However, Internet mobile streaming services are challenged by the inherently limited on-device resources, device heterogeneity, and the bulk amount of streaming data. In this paper, focusing on resource utilization and streaming quality on mobile devices, we investigate 10 deployed Internet mobile streaming services that employ client-server, client-proxy-server, and P2P architectures from a client's perspective. We find that (1) existing Internet mobile streaming services mainly use the client-server architecture and commonly adopt burst traffic delivery that can save battery power consumption on mobile devices; (2) to deal with device heterogeneity, some streaming services have already utilized intermediate nodes (often the user's home computer) for online transcoding with a client-proxy-server architecture, but currently they lack power-friendly design for mobile devices; (3) a mobile device in P2P streaming consumes significantly more battery power mainly due to the inevitable P2P control traffic and uploading traffic to other peers. These findings provide us new insights to further optimize Internet mobile streaming in the future.
{"title":"A measurement study of resource utilization in internet mobile streaming","authors":"Yao Liu, Fei Li, Lei Guo, Songqing Chen","doi":"10.1145/1989240.1989250","DOIUrl":"https://doi.org/10.1145/1989240.1989250","url":null,"abstract":"The pervasive usage of mobile devices and wireless networking support have enabled more and more Internet stream- ing services to all kinds of heterogeneous mobile devices. However, Internet mobile streaming services are challenged by the inherently limited on-device resources, device heterogeneity, and the bulk amount of streaming data. In this paper, focusing on resource utilization and streaming quality on mobile devices, we investigate 10 deployed Internet mobile streaming services that employ client-server, client-proxy-server, and P2P architectures from a client's perspective. We find that (1) existing Internet mobile streaming services mainly use the client-server architecture and commonly adopt burst traffic delivery that can save battery power consumption on mobile devices; (2) to deal with device heterogeneity, some streaming services have already utilized intermediate nodes (often the user's home computer) for online transcoding with a client-proxy-server architecture, but currently they lack power-friendly design for mobile devices; (3) a mobile device in P2P streaming consumes significantly more battery power mainly due to the inevitable P2P control traffic and uploading traffic to other peers. These findings provide us new insights to further optimize Internet mobile streaming in the future.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127439691","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}
Kristian Evensen, Andreas Petlund, Håkon Riiser, Paul Vigmostad, D. Kaspar, C. Griwodz, P. Halvorsen
A well known challenge with mobile video streaming is fluctuating bandwidth. As the client devices move in and out of network coverage areas, the users may experience varying signal strengths, competition for the available resources and periods of network outage. These conditions have a significant effect on video quality. In this paper, we present a video streaming solution for roaming clients that is able to compensate for the effects of oscillating bandwidth through bandwidth prediction and video quality scheduling. We combine our existing adaptive segmented HTTP streaming system with 1) an application layer framework for creating transparent multi-link applications, and 2) a location based QoS information system containing GPS coordinates and accompanying bandwidth measurements, populated through crowd-sourcing. Additionally, we use real-time traffic information to improve the prediction by, for example, estimating the length of a commute route. To evaluate our prototype, we performed real-world experiments using a popular tram route in Oslo, Norway. The client connected to multiple networks, and the results show that our solution increases the perceived video quality significantly. Also, we used simulations to evaluate the potential of aggregating bandwidth along the route.
{"title":"Mobile video streaming using location-based network prediction and transparent handover","authors":"Kristian Evensen, Andreas Petlund, Håkon Riiser, Paul Vigmostad, D. Kaspar, C. Griwodz, P. Halvorsen","doi":"10.1145/1989240.1989248","DOIUrl":"https://doi.org/10.1145/1989240.1989248","url":null,"abstract":"A well known challenge with mobile video streaming is fluctuating bandwidth. As the client devices move in and out of network coverage areas, the users may experience varying signal strengths, competition for the available resources and periods of network outage. These conditions have a significant effect on video quality. In this paper, we present a video streaming solution for roaming clients that is able to compensate for the effects of oscillating bandwidth through bandwidth prediction and video quality scheduling. We combine our existing adaptive segmented HTTP streaming system with 1) an application layer framework for creating transparent multi-link applications, and 2) a location based QoS information system containing GPS coordinates and accompanying bandwidth measurements, populated through crowd-sourcing. Additionally, we use real-time traffic information to improve the prediction by, for example, estimating the length of a commute route. To evaluate our prototype, we performed real-world experiments using a popular tram route in Oslo, Norway. The client connected to multiple networks, and the results show that our solution increases the perceived video quality significantly. Also, we used simulations to evaluate the potential of aggregating bandwidth along the route.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132063075","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}
J. Taibo, V. M. Gulías, Pablo Montero, Samuel Rivas
Motion estimation is known to be one of the most expensive tasks in video coding as it is usually performed through blind search-based methods. However, in the particular case of computer-generated video, the rendering stage provides useful information to speed up the process. In this paper, we propose a fast motion estimation algorithm, designed to run completely inside the GPU, to compute the optical flow required to estimate motion vectors at the same time as the graphical rendering process by using high-level information about the objects, viewpoints and effects that define each frame. The proposed method takes advantage of GPU parallelism and avoids bottlenecks in the CPU-GPU communication as the entire rendering and encoding process is performed completely inside the GPU. Avoiding search, motion estimation has very little overhead, negligible when compared with rendering and (the rest of the) video encoding costs while maintaining reasonably good quality. Performance evaluation is done with a CUDA implementation for MPEG-2 video, though results are valid for other formats, and it has been tested as part of the rendering and encoding engine of a real-world system that provides server-side visually-rich interactive applications to lightweight clients equipped with standard MPEG video decoders.
{"title":"GPU-based fast motion estimation for on-the-fly encoding of computer-generated video streams","authors":"J. Taibo, V. M. Gulías, Pablo Montero, Samuel Rivas","doi":"10.1145/1989240.1989260","DOIUrl":"https://doi.org/10.1145/1989240.1989260","url":null,"abstract":"Motion estimation is known to be one of the most expensive tasks in video coding as it is usually performed through blind search-based methods. However, in the particular case of computer-generated video, the rendering stage provides useful information to speed up the process. In this paper, we propose a fast motion estimation algorithm, designed to run completely inside the GPU, to compute the optical flow required to estimate motion vectors at the same time as the graphical rendering process by using high-level information about the objects, viewpoints and effects that define each frame. The proposed method takes advantage of GPU parallelism and avoids bottlenecks in the CPU-GPU communication as the entire rendering and encoding process is performed completely inside the GPU. Avoiding search, motion estimation has very little overhead, negligible when compared with rendering and (the rest of the) video encoding costs while maintaining reasonably good quality. Performance evaluation is done with a CUDA implementation for MPEG-2 video, though results are valid for other formats, and it has been tested as part of the rendering and encoding engine of a real-world system that provides server-side visually-rich interactive applications to lightweight clients equipped with standard MPEG video decoders.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131249801","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}
To provide enhanced multimedia services for heterogeneous networks and terminal devices, Scalable Video Coding (SVC) has been developed to embed different quality of video in a single bitstream. Similar to classical compressed video transmission, different packets of a video bitstream have different impacts on received video quality. Therefore, distortion modeling and estimation are necessary in designing a robust video transmission strategy under various network conditions. In the paper, we present the first scheme of packet loss induced distortion modeling and estimation in SVC transmission. The proposed scheme is applicable to numerous video communication and networking scenarios in which accurate distortion information can be utilized to enhance the performance of video transmission. One major challenge in scalable video distortion estimation is due to the adoption of more complicated prediction structure in SVC, which makes the tracking of error propagation much more difficult than the non-scalable encoded video. In this research, we tackle such challenge by systematically tracking the propagation of errors under various prediction trajectories. Supplemental information about the compressed video is embedded into data packets to substantially simplify the modeling and estimation. Moreover, with supplemental data of inter prediction information, distortion estimation can be processed without parsing video bitstream which results in much lower computation and memory cost. With negligible effects on the data size, experimental results show that the proposed scheme is able to track and estimate the distortion with very high accuracy. This first ever scalable video transmission distortion modeling and estimation scheme can be deployed at either gateways or receivers because of its low computation and memory cost.
{"title":"Scalable video transmission: packet loss induced distortion modeling and estimation","authors":"Shujie Liu, Chang Wen Chen","doi":"10.1145/1989240.1989268","DOIUrl":"https://doi.org/10.1145/1989240.1989268","url":null,"abstract":"To provide enhanced multimedia services for heterogeneous networks and terminal devices, Scalable Video Coding (SVC) has been developed to embed different quality of video in a single bitstream. Similar to classical compressed video transmission, different packets of a video bitstream have different impacts on received video quality. Therefore, distortion modeling and estimation are necessary in designing a robust video transmission strategy under various network conditions. In the paper, we present the first scheme of packet loss induced distortion modeling and estimation in SVC transmission. The proposed scheme is applicable to numerous video communication and networking scenarios in which accurate distortion information can be utilized to enhance the performance of video transmission. One major challenge in scalable video distortion estimation is due to the adoption of more complicated prediction structure in SVC, which makes the tracking of error propagation much more difficult than the non-scalable encoded video. In this research, we tackle such challenge by systematically tracking the propagation of errors under various prediction trajectories. Supplemental information about the compressed video is embedded into data packets to substantially simplify the modeling and estimation. Moreover, with supplemental data of inter prediction information, distortion estimation can be processed without parsing video bitstream which results in much lower computation and memory cost. With negligible effects on the data size, experimental results show that the proposed scheme is able to track and estimate the distortion with very high accuracy. This first ever scalable video transmission distortion modeling and estimation scheme can be deployed at either gateways or receivers because of its low computation and memory cost.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123413949","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}
Geolocation of IP addresses is used for determining authenticity of webpages, delivering specific country or location related content and advertisements, or to add security for online transactions. Although IP geolocation databases exist, it is sometimes useful to validate their entries or create new, independent databases using independent sources of information. We propose and demonstrate a method whereby collecting and analyzing online game server discovery traffic over short periods of time can allow us to detect in which timezone a certain prefix or AS is located. Our method provides very good estimates of various AS timezones which we verify using publicly available IP geolocation databases.
{"title":"Inferring the time-zones of prefixes and autonomous systems by monitoring game server discovery traffic","authors":"Mattia Rossi, P. Branch, G. Armitage","doi":"10.1145/1989240.1989258","DOIUrl":"https://doi.org/10.1145/1989240.1989258","url":null,"abstract":"Geolocation of IP addresses is used for determining authenticity of webpages, delivering specific country or location related content and advertisements, or to add security for online transactions. Although IP geolocation databases exist, it is sometimes useful to validate their entries or create new, independent databases using independent sources of information. We propose and demonstrate a method whereby collecting and analyzing online game server discovery traffic over short periods of time can allow us to detect in which timezone a certain prefix or AS is located. Our method provides very good estimates of various AS timezones which we verify using publicly available IP geolocation databases.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125533730","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}
Bandwidth usage in large-scale Video on Demand (VoD) systems varies rapidly over time, due to unpredictable dynamics in user demand and network conditions. Such bandwidth volatility makes it hard to provision the exact amount of server resources that matches the demand in each video channel, posing significant challenges to achieving quality assurance and efficient resource allocation at the same time. In this paper, we seek to statistically model time-varying traffic volatility in VoD servers, leveraging heteroscedastic models first used to interpret economic time series, with the goal of forecasting not only traffic patterns but also traffic volatility. We present the application of volatility forecast to efficient resource allocation that provides probabilistic service level guarantees to user groups. We also discuss volatility reduction from diversification, and its implications to new strategies for cost-effective server management. Our study is based on monitoring the workload of a large-scale commercial VoD system widely deployed on the Internet.
{"title":"Understanding demand volatility in large VoD systems","authors":"Di Niu, Baochun Li, Shuqiao Zhao","doi":"10.1145/1989240.1989252","DOIUrl":"https://doi.org/10.1145/1989240.1989252","url":null,"abstract":"Bandwidth usage in large-scale Video on Demand (VoD) systems varies rapidly over time, due to unpredictable dynamics in user demand and network conditions. Such bandwidth volatility makes it hard to provision the exact amount of server resources that matches the demand in each video channel, posing significant challenges to achieving quality assurance and efficient resource allocation at the same time. In this paper, we seek to statistically model time-varying traffic volatility in VoD servers, leveraging heteroscedastic models first used to interpret economic time series, with the goal of forecasting not only traffic patterns but also traffic volatility. We present the application of volatility forecast to efficient resource allocation that provides probabilistic service level guarantees to user groups. We also discuss volatility reduction from diversification, and its implications to new strategies for cost-effective server management. Our study is based on monitoring the workload of a large-scale commercial VoD system widely deployed on the Internet.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129735107","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}
Osama Abboud, Konstantin Pussep, D. Stingl, R. Steinmetz
There are currently two concurrent trends in the Internet. First, the number of Internet users and their connection speeds are increasing rapidly. Second, Internet-based applications are dominating how people receive information, communicate, and entertain themselves. Therefore, we are witnessing an enormous increase in IP-based multimedia traffic, which is putting an enormous strain on the network. Additionally, router and network virtualization are gaining importance, enabling more intelligent networks. Therefore, we argue that networks should not be merely bystanders to this multimedia revolution. In this paper we present a media-aware network solution based on router virtualization that aims at striking a balance between intelligence and adaptation at the edge and in the core of the network. Using an extensive simulative study, we demonstrate that our media-aware network not only helps in enhancing streaming performance during bottlenecks, but also minimizes the side effects of congestions on user perceived quality, making it a need for future Internet multimedia applications.
{"title":"Media-aware networking for SVC-based P2P streaming","authors":"Osama Abboud, Konstantin Pussep, D. Stingl, R. Steinmetz","doi":"10.1145/1989240.1989246","DOIUrl":"https://doi.org/10.1145/1989240.1989246","url":null,"abstract":"There are currently two concurrent trends in the Internet. First, the number of Internet users and their connection speeds are increasing rapidly. Second, Internet-based applications are dominating how people receive information, communicate, and entertain themselves. Therefore, we are witnessing an enormous increase in IP-based multimedia traffic, which is putting an enormous strain on the network. Additionally, router and network virtualization are gaining importance, enabling more intelligent networks. Therefore, we argue that networks should not be merely bystanders to this multimedia revolution. In this paper we present a media-aware network solution based on router virtualization that aims at striking a balance between intelligence and adaptation at the edge and in the core of the network. Using an extensive simulative study, we demonstrate that our media-aware network not only helps in enhancing streaming performance during bottlenecks, but also minimizes the side effects of congestions on user perceived quality, making it a need for future Internet multimedia applications.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127738683","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}
Xiangwen Chen, Minghua Chen, Baochun Li, Yao Zhao, Yunnan Wu, Jin Li
In this paper, we attempt to revisit the problem of multi-party conferencing from a practical perspective, and to rethink the design space involved in this problem. We believe that an emphasis on low end-to-end delays between any two parties in the conference is a must, and the source sending rate in a session should adapt to bandwidth availability and congestion. We present Celerity, a multi-party conferencing solution specifically designed to achieve our objectives. It is entirely Peer-to-Peer (P2P), and as such eliminating the cost of maintaining centrally administered servers. It is designed to deliver video with low end-to-end delays, at quality levels commensurate with available network resources over arbitrary network topologies where bottlenecks can be anywhere in the network. This is in contrast to commonly assumed P2P scenarios where bandwidth bottlenecks reside only at the edge of the network. The highlight in our design is a distributed and adaptive rate control protocol, that can discover and adapt to arbitrary topologies and network conditions quickly, converging to efficient link rate allocations allowed by the underlying network. In accordance with adaptive link rate control, source video encoding rates are also dynamically controlled to present the best possible video quality in arbitrary and unpredictable network conditions. We have implemented Celerity in a prototype system and demonstrate its superior performance in a local experimental testbed.
{"title":"Celerity: towards low-delay multi-party conferencing over arbitrary network topologies","authors":"Xiangwen Chen, Minghua Chen, Baochun Li, Yao Zhao, Yunnan Wu, Jin Li","doi":"10.1145/1989240.1989270","DOIUrl":"https://doi.org/10.1145/1989240.1989270","url":null,"abstract":"In this paper, we attempt to revisit the problem of multi-party conferencing from a practical perspective, and to rethink the design space involved in this problem. We believe that an emphasis on low end-to-end delays between any two parties in the conference is a must, and the source sending rate in a session should adapt to bandwidth availability and congestion. We present Celerity, a multi-party conferencing solution specifically designed to achieve our objectives. It is entirely Peer-to-Peer (P2P), and as such eliminating the cost of maintaining centrally administered servers. It is designed to deliver video with low end-to-end delays, at quality levels commensurate with available network resources over arbitrary network topologies where bottlenecks can be anywhere in the network. This is in contrast to commonly assumed P2P scenarios where bandwidth bottlenecks reside only at the edge of the network. The highlight in our design is a distributed and adaptive rate control protocol, that can discover and adapt to arbitrary topologies and network conditions quickly, converging to efficient link rate allocations allowed by the underlying network. In accordance with adaptive link rate control, source video encoding rates are also dynamically controlled to present the best possible video quality in arbitrary and unpredictable network conditions. We have implemented Celerity in a prototype system and demonstrate its superior performance in a local experimental testbed.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125629094","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}
Today, OSN sites allow users to share data using a centrally controlled web infrastructure. However, if users shared data directly from home, they could potentially retain full control over the data (i.e., what to share, whom to share with). This paper investigates the feasibility of alternative decentralized architectures that allow users to share their data directly from home. Specifically, we (a) characterize social content workloads using data gathered from the popular Flickr and YouTube social networks and (b) characterize home networks using data gathered from residential gateways deployed in a number of households. We use the data from these measurements to evaluate the potential for delivering social content directly from users' homes.
{"title":"Sharing social content from home: a measurement-driven feasibility study","authors":"M. Marcon, Bimal Viswanath, M. Cha, K. Gummadi","doi":"10.1145/1989240.1989253","DOIUrl":"https://doi.org/10.1145/1989240.1989253","url":null,"abstract":"Today, OSN sites allow users to share data using a centrally controlled web infrastructure. However, if users shared data directly from home, they could potentially retain full control over the data (i.e., what to share, whom to share with). This paper investigates the feasibility of alternative decentralized architectures that allow users to share their data directly from home. Specifically, we (a) characterize social content workloads using data gathered from the popular Flickr and YouTube social networks and (b) characterize home networks using data gathered from residential gateways deployed in a number of households. We use the data from these measurements to evaluate the potential for delivering social content directly from users' homes.","PeriodicalId":254694,"journal":{"name":"Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132116751","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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