January / February 2014


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Special Issue on Mobile Cloud Computing

This issue of Cloud-Link is about mobile cloud computing, which is a cloud computing topic that is gaining interest recently. Two special magazine issues and six related articles have been selected to provide a general overview of the recent works on mobile cloud computing in different aspects. In general, mobile cloud computing seeks to enhance mobile computing using the immense and scalable cloud computing resources to provide more effective services (e.g., through offloading mobile applications to run in the cloud). The special issue on “Mobile Cloud Computing” of IEEE Wireless Communications (published in June 2013) includes seven articles, covering applications/services, communications and migration of virtual machines. Another special issue on “Cloud-assisted Mobile Computing and Pervasive Services” of IEEE Network (published in September/October 2013) includes nine articles. They generally cover three main areas: mobile cloud computing architectures, computation offloading methods and cloud assisted applications/services. The survey paper “A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing” reviews distributed application processing frameworks to facilitate application offloading. The paper “Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel” studies an offloading algorithm with the aim of saving energy under a stochastic wireless networking environment. One potential application of mobile cloud computing is to support multimedia services. The papers “Adaptive Mobile Cloud Computing to Enable Rich Mobile Multimedia Applications” and “A Network and Device Aware QoS Approach for Cloud-Based Mobile Streaming” study the use of mobile cloud computing to support rich mobile multimedia applications and mobile streaming services, respectively. To develop effective mobile streaming service, it is important to understand the traffic characteristics at the servers. The paper “Measurement and Analysis of an Internet Streaming Service to Mobile Devices” studies this important issue. Last but not least, the paper “CAM: Cloud-Assisted Privacy Preserving Mobile Health Monitoring” studies a cloud-based mobile health monitoring service with the focus of ensuring privacy and enhancing security.

We hope that the aforementioned special magazine issues and articles can provide you with useful references to explore this important and interesting topic further. Articles have been selected for this issue based on various considerations (e.g., variety, relevancy, anticipated readers' interests) and unavoidably there are many other useful and insightful articles that have not been included. You are also encouraged to search through IEEE Xplore and other databases for further reading.

The next issue (March/April 2014) of Cloud-Link will be “Big Data”. If you would like to recommend any useful articles, please email them to hcbchan@ieee.org. Furthermore, we are looking for topics for the upcoming issues. If you have any suggestions, please also let us know.

Henry Chan, Victor Leung, Jens Jensen and Tomasz Wiktor Wlodarczyk
Editor and Associate Editors

Articles in this issue

Measurement and Analysis of an Internet Streaming Service to Mobile Devices

By Yao Liu, Fei Li, Lei Guo, Bo Shen, Songqing Chen and Yingjie Lan

Published in IEEE Transactions on Parallel and Distributed Systems, November 2013

Receiving Internet streaming services on various mobile devices is getting increasingly popular, and cloud platforms have also been gradually employed for delivering streaming services to mobile devices. While a number of studies have been conducted at the client side to understand and characterize Internet mobile streaming delivery, little is known about the server side, particularly for the recent cloud-based Internet mobile streaming delivery. In this work, we aim to investigate the Internet mobile streaming service at the server side. For this purpose, we have collected a 4-month server-side log on the cloud (with 1,002 TB delivered video traffic) from a top Internet mobile streaming service provider serving worldwide mobile users. Through trace analysis, we find that 1) a major challenge for providing Internet mobile streaming services is rooted from the mobile device hardware and software heterogeneity. In this workload, we find over 3,400 different hardware models with more than 100 different screen resolutions running 14 different mobile OS and three audio codecs and four video codecs. 2) To deal with the device heterogeneity, CPU-intensive transcoding is used on the cloud to customize the video to the appropriate versions at runtime for different devices. A video clip could be transcoded into more than 40 different versions to serve requests from different devices. 3) Compared to videos in traditional Internet streaming, mobile streaming videos are typically of much smaller size (a median of 1.68 MBytes) and shorter duration (a median of 2.7 minutes). Furthermore, the daily mobile user accesses are more skewed following a Zipf-like distribution but users' interests also quickly shift. Considering the huge demand of CPU cycles for online transcoding, we further examine server-side caching to reduce the total CPU cycle demand from the cloud. We show that a policy considering different versions of a video altogether outperforms other intuitive ones when the cache size is limited.

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Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel

By Weiwen Zhang, Yonggang Wen, Guan, K., Kilper, D., Haiyun Luo and Wu, D.O.

Published in IEEE Transactions on Communications, September 2013

This paper provides a theoretical framework of energy-optimal mobile cloud computing under stochastic wireless channel. Our objective is to conserve energy for the mobile device, by optimally executing mobile applications in the mobile device (i.e., mobile execution) or offloading to the cloud (i.e., cloud execution). One can, in the former case sequentially reconfigure the CPU frequency; or in the latter case dynamically vary the data transmission rate to the cloud, in response to the stochastic channel condition. We formulate both scheduling problems as constrained optimization problems, and obtain closed-form solutions for optimal scheduling policies. Furthermore, for the energy-optimal execution strategy of applications with small output data (e.g., CloudAV), we derive a threshold policy, which states that the data consumption rate, defined as the ratio between the data size (L) and the delay constraint (T), is compared to a threshold which depends on both the energy consumption model and the wireless channel model. Finally, numerical results suggest that a significant amount of energy can be saved for the mobile device by optimally offloading mobile applications to the cloud in some cases. Our theoretical framework and numerical investigations will shed lights on system implementation of mobile cloud computing under stochastic wireless channel.

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Special Issue on Cloud-assisted Mobile Computing and Pervasive Services


Published in IEEE Network, September/October 2013

Mobile cloud computing service models: a user-centric approach
By Dijiang Huang, Tianyi Xing and Huijun Wu

Follow me cloud: interworking federated clouds and distributed mobile networks
By Taleb, T. and Ksentini, A.

A distributed cloud architecture for mobile multimedia services
By Felemban, M., Basalamah, S. and Ghafoor, A.

When mobile terminals meet the cloud: computation offloading as the bridge
By Xiaoqiang Ma, Yuan Zhao, Lei Zhang, Haiyang Wang and Limei Peng

Toward a unified elastic computing platform for smartphones with cloud support
By Weiwen Zhang, Yonggang Wen, Jun Wu and Hui Li

CitySee: not only a wireless sensor network
By Yunhao Liu, Xufei Mao, Yuan He, Kebin Liu, Wei Gong and Jiliang Wang

Toward cloud-based vehicular networks with efficient resource management
By Rong Yu, Yan Zhang, Gjessing, S., Wenlong Xia and Kun Yang

Cloud-enabled wireless body area networks for pervasive healthcare
By Wan, J., Zou, C., Ullah, S., Lai, C.-F., Zhou, M. and Wang, X.

An auto-scaling mechanism for virtual resources to support mobile, pervasive, real-time healthcare applications in cloud computing
By Ahn, Y.W., Cheng, A.M.K., Baek, J., Jo, M. and Chen, H.-H.

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A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing

By Shiraz, M., Gani, A., Khokhar, R.H. and Buyya, R.

Published in IEEE Communications Surveys & Tutorials, Third Quarter 2013

The latest developments in mobile devices technology have made smartphones as the future computing and service access devices. Users expect to run computational intensive applications on Smart Mobile Devices (SMDs) in the same way as powerful stationary computers. However in spite of all the advancements in recent years, SMDs are still low potential computing devices, which are constrained by CPU potentials, memory capacity and battery life time. Mobile Cloud Computing (MCC) is the latest practical solution for alleviating this incapacitation by extending the services and resources of computational clouds to SMDs on demand basis. In MCC, application offloading is ascertained as a software level solution for augmenting application processing capabilities of SMDs. The current offloading algorithms offload computational intensive applications to remote servers by employing different cloud models. A challenging aspect of such algorithms is the establishment of distributed application processing platform at runtime which requires additional computing resources on SMDs. This paper reviews existing Distributed Application Processing Frameworks (DAPFs) for SMDs in MCC domain. The objective is to highlight issues and challenges to existing DAPFs in developing, implementing, and executing computational intensive mobile applications within MCC domain. It proposes thematic taxonomy of current DAPFs, reviews current offloading frameworks by using thematic taxonomy and analyzes the implications and critical aspects of current offloading frameworks. Further, it investigates commonalities and deviations in such frameworks on the basis significant parameters such as offloading scope, migration granularity, partitioning approach, and migration pattern. Finally, we put forward open research issues in distributed application processing for MCC that remain to be addressed.

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CAM: Cloud-Assisted Privacy Preserving Mobile Health Monitoring

By Huang Lin, Jun Shao, Chi Zhang and Yuguang Fang

Published in IEEE Transactions on Information Forensics and Security, June 2013

Cloud-assisted mobile health (mHealth) monitoring, which applies the prevailing mobile communications and cloud computing technologies to provide feedback decision support, has been considered as a revolutionary approach to improving the quality of healthcare service while lowering the healthcare cost. Unfortunately, it also poses a serious risk on both clients' privacy and intellectual property of monitoring service providers, which could deter the wide adoption of mHealth technology. This paper is to address this important problem and design a cloud-assisted privacy preserving mobile health monitoring system to protect the privacy of the involved parties and their data. Moreover, the outsourcing decryption technique and a newly proposed key private proxy reencryption are adapted to shift the computational complexity of the involved parties to the cloud without compromising clients' privacy and service providers' intellectual property. Finally, our security and performance analysis demonstrates the effectiveness of our proposed design.

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Adaptive Mobile Cloud Computing to Enable Rich Mobile Multimedia Applications

By Shaoxuan Wang, La Jolla and Dey, S.

Published in IEEE Transactions on Multimedia, June 2013

With worldwide shipments of smartphones (487.7 million) exceeding PCs (414.6 million including tablets) in 2011, and in the US alone, more users predicted to access the Internet from mobile devices than from PCs by 2015, clearly there is a desire to be able to use mobile devices and networks like we use PCs and wireline networks today. However, in spite of advances in the capabilities of mobile devices, a gap will continue to exist, and may even widen, with the requirements of rich multimedia applications. Mobile cloud computing can help bridge this gap, providing mobile applications the capabilities of cloud servers and storage together with the benefits of mobile devices and mobile connectivity, possibly enabling a new generation of truly ubiquitous multimedia applications on mobile devices: Cloud Mobile Media (CMM) applications.

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A Network and Device Aware QoS Approach for Cloud-Based Mobile Streaming

By Chin-Feng Lai, Honggang Wang, Han-Chieh Chao and Guofang Nan

Published in IEEE Transactions on Multimedia, June 2013

Cloud multimedia services provide an efficient, flexible, and scalable data processing method and offer a solution for the user demands of high quality and diversified multimedia. As intelligent mobile phones and wireless networks become more and more popular, network services for users are no longer limited to the home. Multimedia information can be obtained easily using mobile devices, allowing users to enjoy ubiquitous network services. Considering the limited bandwidth available for mobile streaming and different device requirements, this study presented a network and device-aware Quality of Service (QoS) approach that provides multimedia data suitable for a terminal unit environment via interactive mobile streaming services, further considering the overall network environment and adjusting the interactive transmission frequency and the dynamic multimedia transcoding, to avoid the waste of bandwidth and terminal power. Finally, this study realized a prototype of this architecture to validate the feasibility of the proposed method. According to the experiment, this method could provide efficient self-adaptive multimedia streaming services for varying bandwidth environments.

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Special Issue on Mobile Cloud Computing

Published in IEEE Wireless Communications, June 2013

Gearing resource-poor mobile devices with powerful clouds: architectures, challenges, and applications
By Fangming Liu, Peng Shu, Hai Jin, Linjie Ding, Jie Yu, Di Niu and Bo Li

Migrate or not? exploiting dynamic task migration in mobile cloud computing systems
By Gkatzikis, L. and Koutsopoulos, I.

Challenges on wireless heterogeneous networks for mobile cloud computing
By Lei Lei, Zhangdui Zhong, Kan Zheng, Jiadi Chen and Hanlin Meng

A survey of mobile cloud computing for rich media applications
By Yi Xu and Shiwen Mao

Exploring blind online scheduling for mobile cloud multimedia services
By Liang Zhou, Zhen Yang, Rodrigues, J.J.P.C. and Guizani, M.

Cloud-assisted real-time transrating for http live streaming
By Chin-Feng Lai, Han-Chieh Chao, Ying-Xun Lai and Jiafu Wan

Cloud-assisted adaptive video streaming and social-aware video prefetching for mobile users
By Xiaofei Wang, Kwon, T.T., Yanghee Choi, Haiyang Wang and Jiangchuan Liu

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