Instant Social Networking with Startup Time Minimization Based on Mobile Cloud Computing

Mobile communication and handheld devices are currently extremely popular, and provide people with convenient and instant platforms for social networking. However, existing social networking services cannot offer efficient human-machine interfaces or intuitive user experiences. Mobile users must manually input account information and find targets from search results when attempting to add someone to their friend list on social networking sites, such as Facebook and Twitter. Additionally, mobile users may not be able to identify correct targets because some usernames are identical. Typos may occur during the input process due to unfamiliar identifiers, further increasing the total operation time. To encourage social initiation between mobile users, we design an instant social networking framework, called SocialYou, to minimize the startup time based on mobile cloud computing. SocialYou proposes an efficient architecture and innovative human-machine interfaces to alleviate the complexity and difficulty for mobile users using handheld devices. In particular, we implement an Android-based prototype to verify the feasibility and superiority of SocialYou. The experimental results show that SocialYou outperforms the existing methods and saves substantial amounts of operation time for mobile social networking.

[1]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[3]  Xinhe Xu,et al.  Face Detection Based on Facial Features , 2006, 2006 8th international Conference on Signal Processing.

[4]  Shinji Hayashi,et al.  A Detection Technique for Degraded Face Images , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[5]  Caifeng Shan,et al.  Local features based facial expression recognition with face registration errors , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[6]  Markus Ringnér,et al.  What is principal component analysis? , 2008, Nature Biotechnology.

[7]  Jong-Hwan Kim,et al.  Fast and Robust Face Detection Using Evolutionary Pruning , 2008, IEEE Transactions on Evolutionary Computation.

[8]  Eugene Marinelli,et al.  Hyrax: Cloud Computing on Mobile Devices using MapReduce , 2009 .

[9]  Domingo Mery,et al.  Face Recognition with Local Binary Patterns, Spatial Pyramid Histograms and Naive Bayes Nearest Neighbor Classification , 2009, 2009 International Conference of the Chilean Computer Science Society.

[10]  Mahmoud Hassaballah,et al.  Eye Detection Using Intensity and Appearance Information , 2009, MVA.

[11]  Dongman Lee,et al.  A virtual cloud computing provider for mobile devices , 2010, MCS '10.

[12]  Byung-Gon Chun,et al.  Dynamically partitioning applications between weak devices and clouds , 2010, MCS '10.

[13]  Yung-Hsiang Lu,et al.  Cloud Computing for Mobile Users: Can Offloading Computation Save Energy? , 2010, Computer.

[14]  Irwin King,et al.  Introduction to Social Computing , 2010, DASFAA.

[15]  Chen Wen,et al.  Advertising Effectiveness in Social Networking Sites: Social Ties, Expertise, and Product Type , 2012, IEEE Transactions on Engineering Management.

[16]  Cong Geng,et al.  Fully automatic face recognition framework based on local and global features , 2013, Machine Vision and Applications.

[17]  Wendi B. Heinzelman,et al.  Cloud-Vision: Real-time face recognition using a mobile-cloudlet-cloud acceleration architecture , 2012, 2012 IEEE Symposium on Computers and Communications (ISCC).

[18]  Rajiv Ranjan,et al.  Survey on social networking services , 2013 .

[19]  Riri Fitri Sari,et al.  Face Recognition for Social Media with Mobile Cloud Computing , 2013, CloudCom 2013.

[20]  Naphtali Rishe,et al.  Towards Safe Cities: A Mobile and Social Networking Approach , 2014, IEEE Transactions on Parallel and Distributed Systems.

[21]  Xingshe Zhou,et al.  Predicting the content dissemination trends by repost behavior modeling in mobile social networks , 2014, J. Netw. Comput. Appl..

[22]  Huadong Ma,et al.  Heterogeneous-belief based incentive schemes for crowd sensing in mobile social networks , 2014, J. Netw. Comput. Appl..

[23]  Marwa Ayad,et al.  Real-Time Mobile Cloud Computing: A Case Study in Face Recognition , 2014, 2014 28th International Conference on Advanced Information Networking and Applications Workshops.

[24]  Mazliza Othman,et al.  A Survey of Mobile Cloud Computing Application Models , 2014, IEEE Communications Surveys & Tutorials.

[25]  Junliang Chen,et al.  Recommending friends instantly in location-based mobile social networks , 2014 .

[26]  Yunheung Paek,et al.  Techniques to Minimize State Transfer Costs for Dynamic Execution Offloading in Mobile Cloud Computing , 2014, IEEE Transactions on Mobile Computing.

[27]  Lien-Wu Chen,et al.  Demo: An Augmented Reality Based Social Networking System for Mobile Users Using Smartphones , 2015, MobiHoc.

[28]  Tao Mei,et al.  Supporting Serendipitous Social Interaction Using Human Mobility Prediction , 2015, IEEE Transactions on Human-Machine Systems.

[29]  Rajkumar Buyya,et al.  Seamless application execution in mobile cloud computing: Motivation, taxonomy, and open challenges , 2015, J. Netw. Comput. Appl..

[30]  Chi-Fu Huang,et al.  Cyber-Physical Signage Interacting With Gesture-Based Human–Machine Interfaces Through Mobile Cloud Computing , 2016, IEEE Access.

[31]  Anang Hudaya Muhamad Amin,et al.  Decentralized face recognition scheme for distributed video surveillance in IoT-cloud infrastructure , 2016, 2016 IEEE Region 10 Symposium (TENSYMP).

[32]  Xingshe Zhou,et al.  MobiGroup: Enabling Lifecycle Support to Social Activity Organization and Suggestion With Mobile Crowd Sensing , 2016, IEEE Transactions on Human-Machine Systems.

[33]  B. Annappa,et al.  Twitter-user recommender system using tweets: A content-based approach , 2017, 2017 International Conference on Computational Intelligence in Data Science(ICCIDS).

[34]  Ming-Fong Tsai,et al.  Intelligent file transfer for smart handheld devices based on mobile cloud computing , 2017, Int. J. Commun. Syst..

[35]  Atay Ozgovde,et al.  Performance evaluation of single-tier and two-tier cloudlet assisted applications , 2017, 2017 IEEE International Conference on Communications Workshops (ICC Workshops).