Recent years have witnessed the blooming of mobile devices and applications.Mobile users not only expect a faster broadband connection to access Internet and interact with each other,but also demand ubiquitous enjoyin...Recent years have witnessed the blooming of mobile devices and applications.Mobile users not only expect a faster broadband connection to access Internet and interact with each other,but also demand ubiquitous enjoying of video contents and services.However,this trend is seriously hindered by the fact that mobile devices have limited resources in terms of computation,storage,展开更多
In cellular networks, the proximity devices may share files directly without going through the e NBs, which is called Device-to-Device communications(D2D). It has been considered as a potential technological component...In cellular networks, the proximity devices may share files directly without going through the e NBs, which is called Device-to-Device communications(D2D). It has been considered as a potential technological component for the next generation of communication. In this paper, we investigate a novel framework to distribute video files from some other proximity devices through users' media cloud assisted D2 D communication. The main contributions of this work lie in: 1) Providing an efficient algorithm Media Cloud Cluster Selecting Scheme(MCCSS) to achieve the reasonable cluster; 2) Distributing the optimum updating files to the cluster heads, in order to minimize the expected D2 D communication transmission hop for files; 3) Proposing a minimum the hop method, which can ensure the user obtain required file as soon as possible. Extensive simulation results have demonstrated the efficiency of the proposed scheme.展开更多
Nowadays, media cloud and machine learning have become two hot research domains. On the one hand, the increasing user de- mand on multimedia services has triggered the emergence of media cloud, which uses cloud comput...Nowadays, media cloud and machine learning have become two hot research domains. On the one hand, the increasing user de- mand on multimedia services has triggered the emergence of media cloud, which uses cloud computing to better host media servic- es. On the other hand, machine learning techniques have been successfully applied in a variety of multimedia applications as well as a list of infrastructure and platform services. In this article, we present a tutorial survey on the way of using machine learning techniques to address the emerging challenges in the infrastructure and platform layer of media cloud. Specifically, we begin with a review on the basic concepts of various machine learning techniques. Then, we examine the system architecture of media cloud, focusing on the functionalities in the infrastructure and platform layer. For each of these function and its corresponding challenge, we further illustrate the adoptable machine learning based approaches. Finally, we present an outlook on the open issues in this intersectional domain. The objective of this article is to provide a quick reference to inspire the researchers from either machine learning or media cloud area.展开更多
In this paper, we define mobile cloud computing and describe how it can be used for delivering advanced any-media services to both nomadic and mobile users. We focus on service delivery that is localized and personali...In this paper, we define mobile cloud computing and describe how it can be used for delivering advanced any-media services to both nomadic and mobile users. We focus on service delivery that is localized and personalized and suggest that virtualization and tighter cross-layer communication allows for convergence and seamless transition of services. These are also creating new and never-before seen ways of developing and delivering personalized any-media services. We discuss current paradigms for implementing cloud-based any-media services that generate revenue. Future research topics and requirements for evolving network and service elements are also discussed.展开更多
Recently, the online social networks have emerged as one of the important platforms for social users. Among millions of users, famous person from entertainment circle arouse our interest. They promote social relations...Recently, the online social networks have emerged as one of the important platforms for social users. Among millions of users, famous person from entertainment circle arouse our interest. They promote social relationship and establish their reputation via these platforms. To analyze the social influence of entertainment stars we propose and implement a public cloud based framework to crawl celebrities' social messages from Sina Weibo, store the gathered messages and conduct various analysis to assess the socia influence. It consist of three key components: task generation, resource management and task scheduling, and influence analysis. The task generation is responsible of acquiring celebrities' socia accounts and issue crawling tasks. We propose a cross-media method to extract social accounts from webpages. The resource management and task scheduling will dynamic adjust the rented resource to minimize the total computing cost while keeping Qo S. We propose a dynamic instance provisioning strategy based on the large deviation principle. The influence analysis will undertake various types of analysis, such as fan count, posting frequency, textual analysis, and so on. More than 10,000 celebrities' microblogs have been gathered so far, and some related gainers, such as celebrities and ad agencies can gain the illumination brought by our analysis.展开更多
The worldwide change and transformations are taking place in socio-techno cultures. In the epicenter of all these Information and Communication Technologies (ICTs), the Internet is the backbone and paving salient comm...The worldwide change and transformations are taking place in socio-techno cultures. In the epicenter of all these Information and Communication Technologies (ICTs), the Internet is the backbone and paving salient communications and computations Medias like the emergence of social networking sites (SNSs). These SNSs are facilitating globalized entertainment, socialization, communications, and information sharing over hand-held electronic gazettes/mobiles like Facebook, Twitter, Instagram, Skype, and WhatsApp etc. The positive side of these SNSs is making the world a social village but apart from these positive aspects, there is another trait of multifold adversities/disruptions or negative effects which still have not been exposed and drawn attention. The remedial action for such adversities is needed to be designed and developed. The all age groups and genders are typically involved and resulting in wastage of time, money and peace of minds. The adverse effects of social media users in a Higher Learning Institutions are getting worse day-by-day. The prime aim of this research study is to design an automatic Surveillance System Framework for alleviation of the social media disruptions in these institutions. This framework aims to design and develop a surveillance system and access control guidelines for judiciously alleviating the misuse of social media. The study used MS form, Protopie, adobe XD and InVision for data collection, framework design and prototype development respectively. This research is an attempt to apply an explanatory and applied research design science approach using survey, interviews and technical observations-based primary data analytics. The study concluded with a cloud-based automatic surveillance, auto alerts and control system framework (DPS-KA-AT) and functionally validated by a system framework prototype. In the survey and interview, the 66% respondents’ response was “YES”, while 34% “NO” when enquired for the need assessment of the automatic surveillance and control system towards alleviation of the social media adversities or disruptions. This percentage indicates that the highest number of respondent or the highest number of higher learning institutions communities need an urgent automatic monitoring, surveillance and control system towards alleviation of such adversities/disruptions. The study concluded with a remark “a concrete and Automatic Surveillance and Control System Framework can be a great instrumental for minimizing the adversities of social media in higher learning institutions”.展开更多
Social media data is now widely used by many academic researchers. However, long-term social media data collection projects, which most typically involve collecting data from public-use APIs, often encounter issues wh...Social media data is now widely used by many academic researchers. However, long-term social media data collection projects, which most typically involve collecting data from public-use APIs, often encounter issues when relying on local area network servers (LANs) to collect high-volume streaming social media data over long periods of time. In this paper, we present a cloud-based data collection, pre-processing, and archiving infrastructure, and argue that this system mitigates or resolves the problems most typically encountered when running social media data collection projects on LANs at minimal cloud-computing costs. We show how this approach works in different cloud computing architectures, and how to adapt the method to collect streaming data from other social media platforms. The contribution of our research lies in the development of methodologies that researchers can use to monitor and analyze phenomena including how public opinion and public discourse change in response to events, monitoring the evolution and change of misinformation campaigns, and studying how organizations and entities change how they present and frame information online.展开更多
文摘Recent years have witnessed the blooming of mobile devices and applications.Mobile users not only expect a faster broadband connection to access Internet and interact with each other,but also demand ubiquitous enjoying of video contents and services.However,this trend is seriously hindered by the fact that mobile devices have limited resources in terms of computation,storage,
基金supported by the National Natural Science Foundation of China(Grant No.61322104,61571240)the State Key Development Program of Basic Research of China(2013CB329005)+3 种基金the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe University Natural Science Research Foundation of Anhui Province(No.KJ2015A105,No.KJ2015A092)The open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications),Ministry of Education(NYKL201509)The open research fund of the State Key Laboratory of Integrated Services Networks,Xidian University(ISN17-04)
文摘In cellular networks, the proximity devices may share files directly without going through the e NBs, which is called Device-to-Device communications(D2D). It has been considered as a potential technological component for the next generation of communication. In this paper, we investigate a novel framework to distribute video files from some other proximity devices through users' media cloud assisted D2 D communication. The main contributions of this work lie in: 1) Providing an efficient algorithm Media Cloud Cluster Selecting Scheme(MCCSS) to achieve the reasonable cluster; 2) Distributing the optimum updating files to the cluster heads, in order to minimize the expected D2 D communication transmission hop for files; 3) Proposing a minimum the hop method, which can ensure the user obtain required file as soon as possible. Extensive simulation results have demonstrated the efficiency of the proposed scheme.
文摘Nowadays, media cloud and machine learning have become two hot research domains. On the one hand, the increasing user de- mand on multimedia services has triggered the emergence of media cloud, which uses cloud computing to better host media servic- es. On the other hand, machine learning techniques have been successfully applied in a variety of multimedia applications as well as a list of infrastructure and platform services. In this article, we present a tutorial survey on the way of using machine learning techniques to address the emerging challenges in the infrastructure and platform layer of media cloud. Specifically, we begin with a review on the basic concepts of various machine learning techniques. Then, we examine the system architecture of media cloud, focusing on the functionalities in the infrastructure and platform layer. For each of these function and its corresponding challenge, we further illustrate the adoptable machine learning based approaches. Finally, we present an outlook on the open issues in this intersectional domain. The objective of this article is to provide a quick reference to inspire the researchers from either machine learning or media cloud area.
文摘In this paper, we define mobile cloud computing and describe how it can be used for delivering advanced any-media services to both nomadic and mobile users. We focus on service delivery that is localized and personalized and suggest that virtualization and tighter cross-layer communication allows for convergence and seamless transition of services. These are also creating new and never-before seen ways of developing and delivering personalized any-media services. We discuss current paradigms for implementing cloud-based any-media services that generate revenue. Future research topics and requirements for evolving network and service elements are also discussed.
基金supported by the Soft Science Research Program of Science&Technology Department of Sichuan Province(2016ZR0097)
文摘Recently, the online social networks have emerged as one of the important platforms for social users. Among millions of users, famous person from entertainment circle arouse our interest. They promote social relationship and establish their reputation via these platforms. To analyze the social influence of entertainment stars we propose and implement a public cloud based framework to crawl celebrities' social messages from Sina Weibo, store the gathered messages and conduct various analysis to assess the socia influence. It consist of three key components: task generation, resource management and task scheduling, and influence analysis. The task generation is responsible of acquiring celebrities' socia accounts and issue crawling tasks. We propose a cross-media method to extract social accounts from webpages. The resource management and task scheduling will dynamic adjust the rented resource to minimize the total computing cost while keeping Qo S. We propose a dynamic instance provisioning strategy based on the large deviation principle. The influence analysis will undertake various types of analysis, such as fan count, posting frequency, textual analysis, and so on. More than 10,000 celebrities' microblogs have been gathered so far, and some related gainers, such as celebrities and ad agencies can gain the illumination brought by our analysis.
文摘The worldwide change and transformations are taking place in socio-techno cultures. In the epicenter of all these Information and Communication Technologies (ICTs), the Internet is the backbone and paving salient communications and computations Medias like the emergence of social networking sites (SNSs). These SNSs are facilitating globalized entertainment, socialization, communications, and information sharing over hand-held electronic gazettes/mobiles like Facebook, Twitter, Instagram, Skype, and WhatsApp etc. The positive side of these SNSs is making the world a social village but apart from these positive aspects, there is another trait of multifold adversities/disruptions or negative effects which still have not been exposed and drawn attention. The remedial action for such adversities is needed to be designed and developed. The all age groups and genders are typically involved and resulting in wastage of time, money and peace of minds. The adverse effects of social media users in a Higher Learning Institutions are getting worse day-by-day. The prime aim of this research study is to design an automatic Surveillance System Framework for alleviation of the social media disruptions in these institutions. This framework aims to design and develop a surveillance system and access control guidelines for judiciously alleviating the misuse of social media. The study used MS form, Protopie, adobe XD and InVision for data collection, framework design and prototype development respectively. This research is an attempt to apply an explanatory and applied research design science approach using survey, interviews and technical observations-based primary data analytics. The study concluded with a cloud-based automatic surveillance, auto alerts and control system framework (DPS-KA-AT) and functionally validated by a system framework prototype. In the survey and interview, the 66% respondents’ response was “YES”, while 34% “NO” when enquired for the need assessment of the automatic surveillance and control system towards alleviation of the social media adversities or disruptions. This percentage indicates that the highest number of respondent or the highest number of higher learning institutions communities need an urgent automatic monitoring, surveillance and control system towards alleviation of such adversities/disruptions. The study concluded with a remark “a concrete and Automatic Surveillance and Control System Framework can be a great instrumental for minimizing the adversities of social media in higher learning institutions”.
文摘Social media data is now widely used by many academic researchers. However, long-term social media data collection projects, which most typically involve collecting data from public-use APIs, often encounter issues when relying on local area network servers (LANs) to collect high-volume streaming social media data over long periods of time. In this paper, we present a cloud-based data collection, pre-processing, and archiving infrastructure, and argue that this system mitigates or resolves the problems most typically encountered when running social media data collection projects on LANs at minimal cloud-computing costs. We show how this approach works in different cloud computing architectures, and how to adapt the method to collect streaming data from other social media platforms. The contribution of our research lies in the development of methodologies that researchers can use to monitor and analyze phenomena including how public opinion and public discourse change in response to events, monitoring the evolution and change of misinformation campaigns, and studying how organizations and entities change how they present and frame information online.
