Mobile web-based augmented reality (MWAR) provides users with quick richer information interaction forms due to its convenience and universality. However, the 3D model data service for MWAR is a type of centralized file-based data service, which cannot simultaneously meet diverse user and response delay requirements in large-scale and complex applications. This affects the application and promotion of large-scale and complex MWAR application. To this end, this paper proposes a collaborative model data computing service framework (CMCSF) for MWAR between Mobile Edge Servers (MES), Cloud Servers (CS), and mobile devices. The main contributions of this paper include: (1) The CMCSF converts the file-based 3D model data service in MWAR to a computing-based and interfaced data service to meet the diverse service requirements of users; (2) The CMCSF establishes a collaborative computing model data service between the MES and the CS, and it computes a control and deployment strategy for the collaborative computing model data service in order to reduce the response delay of 3D model data; and (3) The CMCSF optimizes the loading method of the WebGL engine (for example, three.js) and applies the asynchronous loading method of the JSON interface data on the http protocol for browsers to get persistent model data services. An experimental evaluation shows the CMCSF improves the response efficiency of the 3D model data file Significantly when compared with the original centralized file-based 3D model file service.
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Alhaija A, Mustikovela H, Karthik S, Lars M, Andreas G (2018) Augmented reality meets computer vision: Efficient data generation for urban driving scenes. Int J Comput Vis 126:961
Qiao X, Ren P, Nan G, Liu L, Dustdar S, Chen J (2019) Mobile web augmented reality in 5g and beyond:challenges, opportunities, and future directions. China Commun
Inmaculada CT, Sergio CY, Pablo CS, Marcos FM (2018) Casas Yrurzum Sergio, Fi-ar learning: a web-based platform for augmented reality educational content. Multimedia Tools Appl 78:6093–6118
Nguyen M, Lai MP, Le H, Yan WQ (2019) A web-based augmented reality plat-form using pictorial qr code for educational purposes and beyond. In: 25th ACM symposium on virtual reality software and technology
Tran TX, Hajisami A, Pandey P, Pompili D (2017) Collaborative mobile edge computing in 5g networks: new paradigms, scenarios, and challenges. IEEE Commun Mag 55(4):54–61
Rahimi MR, Jian R, Chi HL, Vasilakos AV, Venkatasubramanian N (2014) Mobile cloud computing: a survey, state of art and future directions. Mob Netw Appl 19(2):133–143
Huang Y, Qiao X, Ren P, Liu L, Chen J (2020) A lightweight collaborative deep neural network for the mobile web in edge cloud. IEEE Trans Mob Comput 99:1
Kumar K, Lu YH (2010) Cloud computing for mobile users: can offloading computation save energy? Computer 43(4):51–56
Barbera Marco V, Kosta S, Mei A, Stefa J (2013) To offload or not to offload? the bandwidth and energy costs of mobile cloud computing. In: INFOCOM, 2013 Proceedings IEEE
Aldmour R, Yousef S, Yaghi M, Tapaswi S, Pattanaik KK, Cole M (2017) New cloud offloading algorithm for better energy consumption and process time. Int J Syst Assur Eng Manag
Boukerche A, Pazzi R, Werner N (2006) Remote rendering and streaming of progressive panoramas for mobile devices. In: Proceedings of the 14th ACM International Conference on Multimedia, Santa Barbara, CA, USA, October 23–27, 2006
Maamar HR, Boukerche A, Petriu E (2010) Mosaic-a mobile peer-to-peer networks-based 3d streaming supplying partner protocol. In: 2010 IEEE/ACM 14th international symposium on distributed simulation and real time applications, pp 61–68. IEEE
Diepstraten J, Görke M, Ertl T (2012) Remote line rendering for mobile devices
Satyanarayanan M, Bahl P, Caceres R, Davies N (2009) The case for vm-based cloudlets in mobile computing. IEEE Perv Comput 8(4):14–23
Patel M, Naughton B, Chan C, Sprecher N, Abeta S, Neal A et al (2014) Mobile-edge computing introductory technical white paper. White paper, mobile-edge computing (MEC) industry initiative, pp 1089–7801
Liang T, Yong L Wei G (2016) A hierarchical edge cloud architecture for mobile computing. In IEEE INFOCOM 2016—IEEE Conference on Computer Communications
Li X, Wang X, Li K, Zhu H, Leung VCM (2017) Collaborative multi-tier caching in heterogeneous networks: Modeling, analysis, and design. IEEE Trans Wireless Commun 99:1
Min C, Hao Yixue H, Long HK, Vincent L (2017) Green and mobility-aware caching in 5g networks. IEEE Trans Wireless Commun 16:1
Shi W, Jie C (2016) Edge computing: vision and challenges. IEEE Int Things J 3(5):637–646
Chen M, Yixue H, Meikang Q, Jeungeun S, Di W, Iztok H (2016) Mobility-aware caching and computation offloading in 5g ultra-dense cellular networks. Sensors 16(7):974
Masip-Bruin X, Marín-Tordera E, Tashakor G, Jukan A, Ren G-J (2016) Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems. IEEE Wireless Commun 23(5):120–128
Verbelen T, Simoens P, De Turck F, Dhoedt B (2013) Leveraging cloudlets for immersive collaborative applications. IEEE Perv Comput 12(4):30–38
Al-Shuwaili A, Simeone O, Bagheri A, Gesualdo S (2016) Joint uplink/downlink optimization for backhaul-limited mobile cloud computing with user scheduling. IEEE Trans Sign Inform Process Over Netw 3:1467
Sardellitti S, Scutari G, Barbarossa S (2015) Joint optimization of radio and computational resources for multicell mobile-edge computing. IEEE Trans Sign Inform Process Over Netw 1(2):89–103
Bohez S, Turck Joeri De, Verbelen T, Simoens P, Dhoedt B (2013) Mobile, collaborative augmented reality using cloudlets. In 2013 International conference on MOBILe Wireless MiddleWARE, operating systems, and applications, IEEE, pp 45–54
Kumar A, Mantri A, Dutta R (2020) Development of an augmented reality-based scaffold to improve the learning experience of engineering students in embedded system course. Comput Appl Eng Educ 3:1–14
Huang Y, Qiao X, Tang J, Ren P, Chen J (2020) Deepadapter: a collaborative deep learning framework for the mobile web using context-aware network pruning. In IEEE INFOCOM 2020—IEEE conference on computer communications
Ren P, Qiao X, Huang Y, Liu L, Dustdar S, Chen J (2020) Edge-assisted distributed dnn collaborative computing approach for mobile web augmented reality in 5g networks. IEEE Netw 34(2):254–261
Niroshinie F, Seng W, Loke W, (2013) Mobile cloud computing: a survey. Fut Gener Comput Syst
Ahmed E, Ahmed A, Yaqoob I, Shuja J, Gani A, Imran M, Shoaib M (2017) Bringing computation closer toward the user network: Is edge computing the solution? IEEE Commun Mag 55(11):138–144
Shannon EC (2001) A mathematical theory of communication. Bell Syst Techn J 27(4):623–656
Ren J, Guanding Yu, He Y, Li GY (2019) Collaborative cloud and edge computing for latency minimization. IEEE Trans Vehicular Technol 68(5):5031–5044
Ying He F, Yu R, Zhao N, Leung VCM, Yin H (2017) Software-defined networks with mobile edge computing and caching for smart cities: A big data deep reinforcement learning approach. IEEE Commun Mag 55(12):31–37
Yoo SK, Lee KS, Bae SH, Kim N H (2004) Polygon reduction algorithm for three-dimensional surface visualization. Transactions- Korean Institute of Electrical Engineers
This work is supported by the Basic Public Welfare Projects in Zhejiang Province, China, under Grant LGG19F020002; Key Lab of Film and TV Media Technology of Zhejiang Province, No.2020E10015.
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Li, L., Lu, Q., Xu, Y. et al. CMCSF: a collaborative service framework for mobile web augmented reality base on mobile edge computing. Computing (2021). https://doi.org/10.1007/s00607-021-00952-8
- Mobile web augmented reality
- Mobile edge computing
- Model data computing service
- Collaborative computing
Mathematics Subject Classification