Streams in Mobile Clouds

Introduction In addition to recommend high quality articles to MMTC members, another goal of the Review Board is to promote MMTC and initiate helpful exchange between technical committees. Resulting from the hard work of Review Board members, we are glad to advise that, starting from this issue, the front page of our latest R-letter will be displayed on the SIGMM Records webpage. Names of R-article editors will also be included in the front page. This will certainly help establish a closer link between MMTC and SIGMM communities. R-letter is also becoming a regular contributor to IEEE Communications Society's Communications Technical News. The recent advent of ubiquitous network access and affordable mobile devices has led to an unprecedented traffic growth in wireless networks. Such exponential growth has brought several technical challenges; one is the ever-increasing network energy consumption, especially on Base Stations (BSs). Another important challenge is how to manage/utilize such gigantic amount of data generated by mobile users. The first paper, published in the IEEE Transactions on Wireless Communications, provided a new perspective on green cellular networks using hybrid energy, which consists of traditional grid and renewable green energy. The second paper, published in the IEEE Transactions on Multimedia, studied a mobile cloud-based stream mining system, where mobile users send their captured data streams to the cloud for mining. The topics of the regular category include video streaming, multiview video coding, natural language descriptions, shape similarity fusion, and 3D watermarking. The first paper, published in the IEEE Transactions on Vehicular Technology and edited by Koichi Adachi, proposes a novel bandwidth management system for live video streaming in a public-shared network. The second paper, published in the IEEE Transactions on Multimedia and edited by Carsten Griwodz, presents a joint bit allocation and rate control for the coding of multiview video plus depth based 3D video. The third paper is edited by Guillaume Lavoué and has been published within the Proceedings of IEEE International Conference on Computer Vision (ICCV) and proposed means for the automatic natural Language descriptions of images. The forth paper, published in the IEEE Transactions on Multimedia and edited by Jun Zhou, describes an effective shape similarity fusion method based on local data distribution. Finally, we revisit a paper by incorporating the authors' view. The fifth paper, published in IEEE Transactions on Image Processing and edited by Guillaume Lavoué and Adrian G. Bors, proposes improvements for a 3D digital …