With great increase of mobile service in recent years,high quality of experience(QoE) is becoming a comprehensive and major goal for service provider.To unify evaluations of different services,mean opinion score(MOS) ...With great increase of mobile service in recent years,high quality of experience(QoE) is becoming a comprehensive and major goal for service provider.To unify evaluations of different services,mean opinion score(MOS) as a subjective assessment is usually adopted for accurate and convincing reflection of user perceived quality.In this paper,we consider the effect of the burst transmission of best effort(BE) traffic on the uses with real time video traffic in the same cell.We extend the rate scaling process which was initially used to shape burstiness of BE users as interference to handle the scenario that BE users act as resource competitors with video users.A power reallocation strategy between the two types of users is presented and an algorithm further improving the fairness of BE users is proposed.The simulation results demonstrate that the proposed algorithm can not only promote the QoE of both types of users,but also guarantee the fairness among users.展开更多
User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube h...User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the users' watching and sharing activities.The substantial benefit is to further augment its service and monetize more videos,which is crucial to both YouTube and its partners,as well as to other providers of relevant services.In this paper,our main contribution is to analyze the massive amounts of video data from a YouTube partner's view.We make effective use of Insight,a new analytics service of YouTube that offers simple data analysis for partners.To provide the practical guidance from the raw Insight data,we enable more complex investigations for the inherent features that affect the popularity of the videos.Our findings facilitate YouTube partners to re-design current video publishing strategies,having more opportunities to attract more views.展开更多
This study aims to demonstrate the importance of the role of quantitative methods to maximize corporate profits, where the researcher reviewed the related literature, where most of them pointed out that the industrial...This study aims to demonstrate the importance of the role of quantitative methods to maximize corporate profits, where the researcher reviewed the related literature, where most of them pointed out that the industrial companies, and service providers also apply these methods, especially breakeven point, and linear programming in order to maximize profits.展开更多
基金supported by China National S&T Major Project 2013ZX03003002003Beijing Natural Science Foundation No.4152047+1 种基金the 863 project No.2014AA01A701111 Project of China under Grant B14010
文摘With great increase of mobile service in recent years,high quality of experience(QoE) is becoming a comprehensive and major goal for service provider.To unify evaluations of different services,mean opinion score(MOS) as a subjective assessment is usually adopted for accurate and convincing reflection of user perceived quality.In this paper,we consider the effect of the burst transmission of best effort(BE) traffic on the uses with real time video traffic in the same cell.We extend the rate scaling process which was initially used to shape burstiness of BE users as interference to handle the scenario that BE users act as resource competitors with video users.A power reallocation strategy between the two types of users is presented and an algorithm further improving the fairness of BE users is proposed.The simulation results demonstrate that the proposed algorithm can not only promote the QoE of both types of users,but also guarantee the fairness among users.
文摘User generated content,e.g.,from YouTube,the most popular online video sharing site,is one of the major sources of today's big data and it is crucial to understand their inherent characteristics.Recently,YouTube has started working with content providers(known as YouTube partners) to promote the users' watching and sharing activities.The substantial benefit is to further augment its service and monetize more videos,which is crucial to both YouTube and its partners,as well as to other providers of relevant services.In this paper,our main contribution is to analyze the massive amounts of video data from a YouTube partner's view.We make effective use of Insight,a new analytics service of YouTube that offers simple data analysis for partners.To provide the practical guidance from the raw Insight data,we enable more complex investigations for the inherent features that affect the popularity of the videos.Our findings facilitate YouTube partners to re-design current video publishing strategies,having more opportunities to attract more views.
文摘This study aims to demonstrate the importance of the role of quantitative methods to maximize corporate profits, where the researcher reviewed the related literature, where most of them pointed out that the industrial companies, and service providers also apply these methods, especially breakeven point, and linear programming in order to maximize profits.
