James She

IPTV over WiMAX: Key Success Factors, Challenges, and Solutions [Advances in Mobile Multimedia]

The advances in broadband Internet access and scalable video technologies have made it possible for Internet Protocol television (IPTV) to become the next killer application for modern Internet carriers in metropolitan areas. With the recent release of IEEE 802.16d/e (worldwide interoperability for microwave access or WiMAX), broadband wireless access (BWA) is envisioned to further extend IPTV services to a new application scenario with wireless and mobility dimensions. It is a very strategic but challenging leverage for a carrier to glimpse the potential of IPTV by using WiMAX as the access network. Challenges are posed for IPTV over WiMAX due to multicasting under a diversity of fading conditions. A cross-layer design framework based on a novel two-level superposition coded multicasting (SCM) scheme is introduced. Simulation results show that much improved video quality is achievable with our approach.

A Framework of Cross-Layer Superposition Coded Multicast for Robust IPTV Services over WiMAX

A cross-layer design (CLD) framework for robust and efficient video multicasting over IEEE 802.16 (or WiMAX) is introduced. In the framework, multiple description coding on scalable video bitstreams at the source for achieving multi-resolution robustness is jointly designed with superposition coding (i.e., multi-resolution modulation) on multicast signals at the channel to overcome the channel diversity problem in wireless multicast. The resulting cross-layer coded multicast signals enable us to recover some lost bitstreams in high quality layers, which is not possible if multi-resolution modulation is used alone for multicasting as in previous works. Simulation results show that indeed our joint design outperforms the scheme using only superposition coded multicast by achieving better video quality for users under multi-user channel diversity.

A cross-layer design framework for robust IPTV services over IEEE 802.16 networks

This paper introduces a cross-layer design framework for robust and efficient video multicasting over IEEE 802.16 (also known as WiMAX) networks in metropolitan areas. In the framework, multiple description coding (MDC) on scalable video bitstreams at the source for achieving multiresolution robustness is jointly designed with superposition coding (SCM) on multicast signals at the channel to overcome multiuser channel diversity in wireless multicast. The coded multicast signals under the proposed framework can cope with multiuser channel diversity and mitigate the impact due to short-term channel fluctuations, which are the two most challenging issues in achieving robust and efficient video multicasting in metropolitan areas. We formulate the proposed framework and analyze its video quality performance in terms of the total receivable/ recoverable bitstreams by a receiver. A heuristic methodology is developed for system parameter selection and performance optimization that can be applied to practical scenarios of video multicasting for IPTV services in WiMAX. Simulation is conducted based on actual standard video sequences to verify the proposed methodology on parameter selection and performance optimization. Performance gains of the proposed cross-layer design framework in the presence of fading channel diversity are demonstrated.

Cooperative Coded Video Multicast for IPTV Services under EPON-WiMAX Integration

This article introduces a novel framework of cooperative coded video multicast (CCVM) for provisioning IPTV services in metropolitan area access networks based on the emerging integration of Ethernet passive optical networks and WiMAX. The framework of CCVM is formed through the central coordination and synchronization at the optical line terminal and advanced coding techniques across different system layers. A cross-layer design of video multicasting on a single ONU-BS is first introduced for dealing with the multi-user channel diversity and short-term channel fluctuations, where the scalable video coding with multiple description coding (MDC) at the source and physical layer superposition coding techniques at the channel are jointly considered. This approach is further extended into the scenario that involves multiple ONU-BSs for cooperative communications to tackle intercell interference. Finally, the efficiency of the proposed framework is demonstrated via a case study on the employment of CCVM strategy under the collaboration of multiple distributed ONU-BSs.

An Analysis of Verifications in Microblogging Social Networks -- Sina Weibo

Sina Weibo (Weibo) is a fast growing microblogging social network with total user size closer to Twitter. Weibo adopts a mechanism to verify users, so that the public can identify true accounts of celebrities and official channels of certain organizations. The verification mechanism builds trust and authenticity to the source, and hence, stimulates people to actively participate on the platform. However, how the verifications affect the user behaviors in microblogging social networks have never been fully investigated. This paper analyzes the Weibo social network with verifications, by comparing the user microblogging behaviors between verified users and unverified users and studying the social network evolvements of these two group of users. In addition, a method is proposed to approximately reconstruct the network evolvement, and lower bound quasi-densification exponents for the social networks are found. Empirical evidence demonstrates that verifications play a significant role in motivating users to have more interactions in a social network.

Nanotechnology-Enabled Wireless Sensor Networks: From a Device Perspective

The advancement of wireless communications and integrated circuit technology has enabled the development of low-cost sensor networks. The sensor networks can be used for various application areas (disaster recovery, health, military, homeland security, environment, home, etc.). For each application area, there are different technical issues that researchers are currently resolving. However, many of them are trying to tackle the limitations of this field from a network perspective. Sometimes, the effectiveness of some proposed approaches must be complemented by the supports of hardware design. This article points out the possibilities of overcoming the same problem set from a device perspective by taking advantage of the merits of nanotechnologies. At the same time, open research issues and challenges are identified to spark new interests and developments in this field

Convergence of interactive displays with smart mobile devices for effective advertising: A survey

The trend of replacing public static signages with digital displays creates opportunities for interactive display systems, which can be used in collaborative workspaces, social gaming platforms and advertising. Based on marketing communication concepts and existing models for consumer behavior, three stages, namely attraction, interaction and conation, are defined in this article to analyze the effectiveness of interactive display advertising. By reviewing various methods and strategies employed by existing systems with attraction, interaction and conation stages, this article concludes that smart mobile devices should be integrated as a component to increase the effectiveness of interactive displays as advertising tools. Future research challenges related to this topic are also discussed.

Collaborative Variational Autoencoder for Recommender Systems

Modern recommender systems usually employ collaborative filtering with rating information to recommend items to users due to its successful performance. However, because of the drawbacks of collaborative-based methods such as sparsity, cold start, etc., more attention has been drawn to hybrid methods that consider both the rating and content information. Most of the previous works in this area cannot learn a good representation from content for recommendation task or consider only text modality of the content, thus their methods are very limited in current multimedia scenario. This paper proposes a Bayesian generative model called collaborative variational autoencoder (CVAE) that considers both rating and content for recommendation in multimedia scenario. The model learns deep latent representations from content data in an unsupervised manner and also learns implicit relationships between items and users from both content and rating. Unlike previous works with denoising criteria, the proposed CVAE learns a latent distribution for content in latent space instead of observation space through an inference network and can be easily extended to other multimedia modalities other than text. Experiments show that CVAE is able to significantly outperform the state-of-the-art recommendation methods with more robust performance.

Connection Discovery Using Big Data of User-Shared Images in Social Media

Billions of user-shared images are generated by individuals in many social networks today, and this particular form of user data is widely accessible to others due to the nature of online social sharing. When user social graphs are only accessible to exclusive parties, these user-shared images are proved to be an easier and effective alternative to discover user connections. This work investigated over 360 000 user shared images from two social networks, Skyrock and 163 Weibo, in which 3 million follower/ followee relationships are involved. It is observed that the shared images from users with a follower / followee relationship show relatively higher similarities . A multimedia big data system that utilizes this observed phenomenon is proposed as an alternative to user- generated tags and social graphs for follower/followee recommendation and gender identification. To the best of our knowledge, this is the first attempt in this field to prove and formulate such a phenomenon for mass user-shared images along with more practical prediction methods. These findings are useful for information or services recommendations in any social network with intensive image sharing, as well as for other interesting personalization applications, particularly when there is no access to those exclusive user social graphs.

Layered Adaptive Modulation and Coding for 4G Wireless Networks

Emerging 4G standards, such as WiMAX, LTE, and TD-SCDMA, have adopted the proven technique of Adaptive Modulation and Coding (AMC) to dynamically react to channel fluctuations while maintaining bit- error rate targets of the transmission. To mitigate the vicious effects due to stale channel state indication (CSI) problem, this paper introduces a novel framework by incorporating AMC with layered transmission through Superposition Coding (SPC). A Markov chain model is adopted under this framework, to effectively assist the system in selecting the optimal modulation and coding scheme for each layer in every multi-resolution unicast transmission. Extensive simulation is conducted to verify the proposed framework and compare it with a number of counterparts. The results demonstrate that the proposed framework can achieve a much better spectrum efficiency due to improved robustness by addressing the stale CSI problem at each multi-resolution modulated transmission.