Disseminating Multilayer Multimedia Content Over Challenged Networks

We present a complete system, called Challenged Content Delivery Network (CCDN), to efficiently deliver multimedia content to mobile users who live in developing countries, rural areas, or over-populated cities with no or weak network infrastructure. These mobile users do not have always-on Internet access. We demo our CCDN, implemented on a Linux server, Raspberry Pi proxies, and Android phones from three aspects: multimedia, networking, and machine learning tools. We propose multiple optimization algorithm modules that compute personalized distribution plans, and maximize the overall user experience. CCDN allows people living in area with challenged networks access to multimedia content, like news reports, using mobile devices, such as smartphones. This in turn will help in eliminating the digital divide, which refers to information inequality to persons with different Internet accessing abilities.

This chapter presents an ambient intelligence framework whose goal is to facilitate the information needs of mobility impaired users on the move. This framework couples users with geographically distributed services and the corresponding multimedia content, enabling access to context-sensitive information based on user geographic location and the use case under consideration. It provides a multi-modal facility that is realized through a set of mobile devices and user interfaces that address the needs of ten different types of user impairments. The overall ambient intelligence framework enables users who are equipped with mobile devices to access multimedia content in order to undertake activities relevant to one or more of the following domains: transportation, tourism and leisure, personal support services, work, business, education, social relations and community building. User experience is being explored against those activities through a specific usage scenario.

User-provided multimedia content distribution architecture in mobile and ubiquitous communication networks

In cellular networks, base station must reserve some resource for the possible handoff which affects the energy efficiency of the system. In this paper, we establish a theoretical model to maximizing the energy efficiency (EE) from the aspects of users' mobility and service duration. After analyzing the probability of handoff in service with user mobility and service characteristics, we introduce a dynamic energy efficiency (DEE) function. With the DEE function, an optimization problem under the constraint of maximal power is formulated to determine the optimal cell radius to maximize the DEE. We prove the existence of the unique optimal cell radius and propose an algorithm to solve the problem. Numerical results show the relationship between the optimal cell radius and different users' mobility and service characteristics, and indicate that the optimal radius is increasing both in the users' average velocity and in the average service duration. This work can provide a reliable theoretical basis for green design of cellular networks.

In the recent years, there has been an increasing demand for streaming high quality multimedia content over wireless networks. Demand for triple play services (voice, video, data) by a number of simultaneously communicating users often results in lack of acceptable multimedia quality. In addition, the large transmission distance and the limited battery power of the hand-held wireless device serves as a major bottleneck over transmitting video directly from the network operator to the end-users. There has been no successful mechanism developed till date that would provide live video streaming over wireless networks. In this paper, clusterDAM – a novel cluster-based architecture is proposed for delivering adaptive multimedia content over two-hop wireless networks. An intermediate relay node serves as a proxy-client-server between the base station and the mobile users which ensures that the multimedia delivery is adapted in real-time according to the channel conditions and the quality of the multimedia content. An extensive simulation-based analysis with different kinds of network traffic and protocols indicate that the cluster-DAM architecture is significantly superior to the traditional single-hop design, not only in terms of the perceived video quality, but also in terms of the loss rate and the average bit rate.

As one of essential techniques to support the multimedia transmissions over the fifth generation (5G) mobile wireless networks, the statistical quality of service (QoS) provisioning has been proved to be effective in statistically guaranteeing time sensitive video transmission over time-varying wireless channels. But, how to efficiently design and implement statistical QoS provisioning enabled wireless network remains as the open challenging problem. To overcome these challenges, in this paper we propose the hierarchical-caching architecture to efficiently implement the statistical QoS guarantees in 5G wireless networks, which cooperatively caches the popular multimedia data contents at different wireless network caching tiers, efficiently trading the widely available storage resources for precious wireless bandwidth resources. However, the hierarchical caching scheme imposes the multi-hop wireless link statistical delay-bounded QoS provisioning problem when the requested multimedia data contents are fetched across tiers. In particular, we develop two hierarchical caching schemes to adaptively cache the delay bounded multimedia data contents: (1) caching in mobile users, which yields the single-hop wireless transmission and (2) caching in routers, which yields the tandem two-hop wireless transmission. To maximize the average effective capacity when cached data contents dynamically switch between these two schemes, we apply the Markov chain model to derive the optimal departure rates for data contents leaving cacheable mobile users and routers, respectively. U sing these two departure rates, we develop the optimal caching schemes in terms of the probability distribution of how long to cache the data contents and the probability of where to cache the data contents. Finally, we evaluate and validate these two optimized caching schemes through numerical analyses.

Nowadays, Social Network Analysis is considered a hot research topic. In this paper, we propose a novel data model for Multimedia Social Networks, i.e. particular social media networks that combine information on users belonging to one or more social communities together with the multimedia content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and represent in a simple way all the different kinds of relationships that are typical of social media networks, and in particular among multimedia contents, users and multimedia content and users themselves.

With the development of fifth generation (5G) communications systems, heterogeneous networks (HetNets) have become a research hotspot. However, most of the existing work assumes that the user is static in HetNets. This hypothesis can greatly simplify system models, nevertheless it is not always accurate enough, because the user mobility has a significant effect on the performances of HetNets. Therefore, this paper studies the influence of the infinite user mobility in HetNets by using tools from stochastic geometry. The local delay and energy efficiency of HetNets based on Poisson point process (PPP) and Poisson cluster process (PCP) respectively are derived, the latter being more accurate to model the hot spot areas than the former. It was found that user mobility can reduce obviously the local delay and improve the energy efficiency under the high SIR regime. Moreover, the local delay is larger and the energy efficiency is lower under PCP than under PPP for infinite user mobility. In addition, the user mobility can reduce the function of the discontinuous transmission (DTX) scheme, which is used to improve the energy efficiency. Finally, the simulation results verify the accuracy of the numerical analyses.

In this paper, we propose a machine learning-based mobility robustness optimization algorithm to optimize handover parameters for seamless mobility under dynamic small-cell networks. Small cells can be arbitrarily deployed, portable, and turned on and off to fulfill wireless traffic demands or energy efficiency. As a result, the small-cell network topology dynamically varies challenging network optimization, especially handover optimization. Previous studies have only considered dynamics due to user mobility in a specific static network topology. To optimize handovers under dynamic network topologies, together with user mobility, we propose an algorithm consisting of two steps: topology adaptation and mobility adaptation. To adapt to a dynamic topology, the algorithm obtains prior knowledge, which presents a belief distribution of the optimal handover parameters, for the current network topology as coarse optimization. In the second step, the algorithm fine-tunes the handover parameters to adapt to user mobility based on reinforcement learning, which utilizes the knowledge obtained during the first step. Under a dynamic small-cell network, we showed that the proposed algorithm reduced adaptation time to 4.17% of the time needed by a comparative machine-based algorithm. Furthermore, the proposed algorithm improved the user satisfaction rate to 416.7% compared to the previous work.

We formulate the optimum personal paging area problem as an interval estimation problem, with an aim to reduce the paging signaling cost by minimizing the size of the paging area. A paging algorithm is developed to set-up the optimal one-step paging area that contains the locations of a mobile user with a high probability and thus to gain a coverage that is matched to the user's time-varying mobility pattern. With a particular mobility model, the effects of the user's mobility characteristics and the system parameters on the performance of the paging procedure are investigated.

Today's multimedia content generation and sharing have been dramatically boosted by the deep penetration of broadband wireless accesses and the much improved processing power of smart mobile terminals. Mobile users can now instantly capture and share short video clips (usually of several seconds) anywhere and anytime, and consume them with convenient touch screen operations. The instant video clip sharing has emerged as a mainstream application; such pioneers as Twitter's Vine, Miaopai, Instagram, and Snapchat have seen great acceptance, particularly by the youth community. In this paper, we present an initial study on instant video clip sharing. Taking Twitter's Vine as a representative, we systematically investigate its distinct mobile interface, service framework, and user watching behaviors, revealing how this mainstream multimedia service type differentiates from its traditional counterparts. Our trace measurement and analysis demonstrate that instant mobile video clips have a much shorter lifespan and highly skewed popularity that quickly decays over time. This is further aggravated by the unique screen scrolling operation for video browsing. As such, the download-and-watch scheduling used by existing platforms can hardly achieve quality user experience and cost efficiency. We closely investigate and model the input user gestures for scrolling, including drag and fling , and analyze the scheduling policy, partitioning it into prefetching scheduling and watch-time download scheduling. We develop effective solutions toward both subproblems as well as their integration with screen scrolling. The superiority of our enhancement is demonstrated by extensive trace-driven evaluation.

With the rapid development of the mobile Internet, mobile reading has transcended the limitation of time and space, becoming an indispensable part of people’s living and learning. As the direct service object of mobile reading APP, users’ subjective use experience is decisive in the success or failure. It is of great significance to identify the key influencing factors of user experience of mobile reading APP. It is conducive not only to improving users reading experience and increasing users stickiness but also to improving mobile reading service quality, which is essential to promote the healthy and sustainable development of mobile reading APP. From the perspective of user experience, content analysis and questionnaire survey are used to construct the index system of influencing factors of mobile reading APP user experience, which includes 6 dimensions of reliability, usefulness, thoughtfulness, interactivity, security, and compatibility, and 21 influencing factors. Based on the decision-making trial and evaluation laboratory (DEMATEL) method, introducing the triangular fuzzy number, the fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) model is established, extending the single value of the comparison matrix to a fuzzy interval and then giving the decision makers a proper judgment space. The key influencing factors of mobile reading APP user experience are identified by algorithm design. Ultimately, the 10 key influencing factors of mobile reading APP user experience are identified, which are information quality, content richness, value fit, copyright protection, timeliness, personalized service, reading function richness, interpersonal interaction, system performance, and privacy protection, and suggestions for improving the user experience of mobile reading APP are put forward to provide reference for mobile reading APP developers. The research results not only enrich and perfect the theoretical and practical research in the mobile reading field to a certain extent, providing a new research perspective for the field of mobile reading, but also effectively solve the defects of the traditional DEMATEL method that expert judgment is subjectively biased and difficult to express with an exact number directly. The research expands the application scope of DEMATEL.

Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user's viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user's acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanying the quantitative method (acceptance assessment), we used a qualitative interview method to obtain a deeper understanding of a user's assessment criteria and to support the quantitative results from a user's perspective. Based on the results from data analysis, we advocate two user-driven strategies to adaptively provide an acceptable quality and to predict a good user experience, respectively. There are two main contributions from this paper. Firstly, the field user study allows a consideration of more influencing factors into the research on user experience of mobile video. And these influences are further demonstrated by user's opinions. Secondly, the proposed strategies — user-driven acceptance threshold adaptation and user experience prediction — will be valuable in mobile video delivery for optimizing user experience.

Mobile applications beyond pure mobile telephony are becoming more and more popular for everyday users. In recent years, with the advent of 3G mobile networks such as UMTS and also higher computing power and storage capabilities of mobile devices, multimedia has reached the mobile user. The user’s individual usage context and needs are becoming more and more important for the design of mobile applications. However, the concepts needed to achieve real comprehensiv user-centric mobile applications are just evolving. In this paper, we present selected concepts and prototypes from our research in the field of mobile multimedia systems that specifically address the mobile user’s needs. We shortly discuss the aspects of user-centered mobile applications and the challenges we see. Our selected research approaches and prototypes show different concepts towards better supporting the concrete user by mobile applications. In this context, we take a look on the specific challenges of image and video retrieval that arise from placing the user in the center of the mobile application design. In our point of view, user-centered mobile multimedia applications pose interesting challenges not only to the retrieval of multimedia content but introduce new challenges and potentials from acquisition, enhancement, storage, retrieval and delivery to the usage of mobile multimedia content.

Multimedia service offloading architecture through device-to-device (D2D) communication is an efficient technique in the fifth generation (5G) wireless networks to improve the base station (BS) bandwidth efficiency by mobile users downloading the multimedia big data from a nearby mobile device using D2D transmission mode. However, the multimedia big data offloading architecture imposes the two-hop wireless link statistical delay-bounded quality of service (QoS) provisioning problem when two mobile users request the same multimedia data content simultaneously with one mobile user downloading the data from BS and forwarding the data to another mobile user using D2D transmission. One of the most important challenges of this multi-media big data D2D offloading architecture lies in how to support this two-hop wireless link transmission with guaranteeing the statistical delay bounded QoS requirements for its both individual hops. To overcome these difficulties, in this paper we propose the optimal transmit power allocation scheme for each single hop which maximizes the overall two-hop effective capacity under three conditions: (1) transmit power allocations are constants; (2) transmit power allocations only depend on the signal-to-noise ratio (SNR) for each link; and (3) transmit power allocations depend on SNRs and the individual QoS requirements for both links. Finally, we evaluate and validate our proposed two-hop wireless link statistical delay bounded QoS provisioning schemes over multimedia D2D offloading architecture through numerical analyses.