DOP-MS: A Microservice-based Data Offloading Service with Support for Data Anonymisation
Authors: 
Vitória R. N. Silvestre, Francisco A. A. Gomes, Adriano L. Cândido, Filipe Fernandes, Lincoln S. Rocha, Fernando A. M. TrintaAuthors Info & Claims
Pages 145 - 152
Abstract
Due to mobile devices' growing presence in our daily routine, mobile applications are becoming increasingly complex. They require more powerful processing capability and more extensive data storage, which characterizes a challenge when computational constraints of these devices are taken into account. Several software infrastructures proposed to help the development of mobile applications with data offloading features. However, they lack essential features for data offloading, such as configurable data synchronization policy models, privacy mechanisms for the offloaded data, and scalability and performance analyses. This work presents DOP, a solution to assist the development of mobile applications that use data migration, including contextual data, from mobile devices to a remote environment, based on a microservice architecture. The data offloading technique enables data migration into a remote environment, allowing (i) storage savings on the mobile device and (ii) sharing data among users. The experiments on DOP showed benefits in storage savings on mobile devices and new possibilities for inferring situations based on shared data from multiple users.
References
[1]
Adriano L. Cândido, Fernando A. M. Trinta, Lincoln S. Rocha, Paulo A. L. Rego, Nabor C. Mendonça, and Vinicius C. Garcia. 2019. A Microservice Based Architecture to Support Offloading in Mobile Cloud Computing. In Proceedings of the XIII Brazilian Symposium on Software Components, Architectures, and Reuse (Salvador, Brazil) (SBCARS '19). Association for Computing Machinery, New York, NY, USA, 93--102. https://doi.org/10.1145/3357141.3357148
[2]
Hoang T Dinh, Chonho Lee, Dusit Niyato, and Ping Wang. 2013. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless communications and mobile computing 13, 18 (2013), 1587--1611. https://doi.org/10.1002/wcm.1203
[3]
Gabriel B. dos Santos, Paulo A. L. Rego, and Fernando Trinta. 2017. Uma Proposta de Solução para Offloading de Métodos entre Dispositivos Móveis. In Anais Estendidos do XXIII Simpósio Brasileiro de Sistemas Multimídia e Web (Gramado). SBC, Porto Alegre, RS, Brasil, 76--81. https://sol.sbc.org.br/index.php/webmedia_estendido/article/view/4838
[4]
Xing Fan, Bronis R. de Supinski, Oliver Sinnen, and Nasser Giacaman (Eds.). 2019. OpenMP: Conquering the Full Hardware Spectrum - 15th International Workshop on OpenMP, IWOMP 2019, Auckland, New Zealand, September 11-13, 2019, Proceedings. Lecture Notes in Computer Science, Vol. 11718. Springer. https://doi.org/10.1007/978-3-030-28596-8
[5]
Niroshinie Fernando, Seng W. Loke, and Wenny Rahayu. 2013. Mobile Cloud Computing: A survey. Future Generation Computer Systems 29, 1 (Jan. 2013), 84--106. https://doi.org/10.1016/j.future.2012.05.023
[6]
Yohanes Yohanie Fridelin, Mochamad Rifki Ulil Albaab, Adnan Rachmat Anom Besari, Sritrusta Sukaridhoto, and Anang Tjahjono. 2018. Implementation of Microservice Architectures on SEMAR Extension for Air Quality Monitoring. In 2018 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC). 218--224. https://doi.org/10.1109/KCIC.2018.8628575
[7]
R.K. Ganti, Fan Ye, and Hui Lei. 2011. Mobile crowdsensing: current state and future challenges. Communications Magazine, IEEE 49, 11 (2011), 32--39. https://doi.org/10.1109/MCOM.2011.6069707
[8]
Francisco Gomes, Windson Viana, Lincoln Rocha, and Fernando Trinta. 2017. On the evaluation of a contextual sensitive data offloading service: the COP case. Journal of Information and Data Management 8, 3 (2017), 197--197.
[9]
Francisco A.A. Gomes, Windson Viana, Lincoln S. Rocha, and Fernando Trinta. 2016. A Contextual Data Offloading Service With Privacy Support. In Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web (Teresina, Piauí State, Brazil) (Webmedia '16). Association for Computing Machinery, New York, NY, USA, 23--30. https://doi.org/10.1145/2976796.2976860
[10]
Francisco A. A. Gomes, Paulo A. L. Rego, Lincoln Rocha, José N. de Souza, and Fernando Trinta. 2017. CAOS: A Context Acquisition and Offloading System. In 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), Vol. 1. IEEE, 957--966. https://doi.org/10.1109/COMPSAC.2017.80
[11]
Holger Knoche and Wilhelm Hasselbring. 2018. Using Microservices for Legacy Software Modernization. IEEE Software 35, 3 (2018), 44--49. https://doi.org/10.1109/MS.2018.2141035
[12]
James Lewis and Martin Fowler. 2014. Microservices. https://martinfowler.com/articles/microservices.html. (Acesso em: 14/08/2021).
[13]
Silvia Mirri, Catia Prandi, Paola Salomoni, Franco Callegati, Andrea Melis, and Marco Prandini. 2016. A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios. Mobile Information Systems 2016 (01 2016), 1--14. https://doi.org/10.1155/2016/2821680
[14]
Z. Sanaei, S. Abolfazli, A. Gani, and R. Buyya. 2014. Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges. IEEE Communications Surveys Tutorials 16, 1 (First 2014), 369--392. https://doi.org/10.1109/SURV.2013.050113.00090
[15]
Santonu Sarkar, Gloria Vashi, and P.P. Abdulla. 2018. Towards Transforming an Industrial Automation System from Monolithic to Microservices. In 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Vol. 1. IEEE, 1256--1259. https://doi.org/10.1109/ETFA.2018.8502567
[16]
Mahadev Satyanarayanan, P. Bahl, R Caceres, and N. Davies. 2009. The Case for VM-Based Cloudlets in Mobile Computing. Pervasive Computing, IEEE 8, 4 (Oct 2009), 14--23. https://doi.org/10.1109/MPRV.2009.82
[17]
Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar, and Rajkumar Buyya. 2013. A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing. IEEE Communications Surveys Tutorials 15, 3 (2013), 1294--1313. https://doi.org/10.1109/SURV.2012.111412.00045
[18]
Cícero A. Silva, Gibeon S. Aquino, Sávio R. M. Melo, and Dannylo J. B. Egídio. 2019. A Fog Computing-Based Architecture for Medical Records Management. Wireless Communications and Mobile Computing 2019 (27 Feb 2019), 1968960. https://doi.org/10.1155/2019/1968960
[19]
Lukas Sommer and Andreas Koch. 2020. OpenMP Device Offloading for Embedded Heterogeneous Platforms - Work-in-Progress. In 20th International Conference on Embedded Software, EMSOFT 2020, Singapore, September 20-25, 2020, Tulika Mitra and Andreas Gerstlauer (Eds.). IEEE, 4--6. https://doi.org/10.1109/EMSOFT51651.2020.9244045
[20]
Gustavo Sousa. 2016. Software Product Lines for Multi-Cloud Microservices Configuration. In Journées Cloud GdR RSD. Nice, France. https://hal.inria.fr/hal-01355864
[21]
Johannes Thönes. 2015. Microservices. IEEE software 32, 1 (2015), 116--116. https://doi.org/10.1109/MS.2015.11
[22]
Eran Toch. 2014. Crowdsourcing Privacy Preferences in Context-aware Applications. Personal Ubiquitous Comput. 18, 1 (Jan. 2014), 129--141. https://doi.org/10.1007/s00779-012-0632-0
[23]
Feng Xia, Fangwei Ding, Jie Li, Xiangjie Kong, Laurence Yang, and Jianhua Ma. 2014. Phone2Cloud: Exploiting computation offloading for energy saving on smartphones in mobile cloud computing. Information Systems Frontiers 16, 1 (03 2014), 95--111. https://doi.org/10.1007/s10796-013-9458-1
[24]
Man-Ching Yuen, Irwin King, and Kwong-Sak Leung. 2011. A Survey of Crowd-sourcing Systems. In 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing. IEEE, 766--773. https://doi.org/10.1109/PASSAT/SocialCom.2011.203
Index Terms
- DOP-MS: A Microservice-based Data Offloading Service with Support for Data Anonymisation
Recommendations
A Microservice Based Architecture to Support Offloading in Mobile Cloud Computing
SBCARS '19: Proceedings of the XIII Brazilian Symposium on Software Components, Architectures, and ReuseMobile devices are increasingly present in people's daily lives. However, despite the substantial improvement of new generations of smartphones, the amount of information and the complexity of the procedures delegated to these devices still imposes ...
Optimal mobile device selection for mobile cloud service providing
With the rapid growth of the mobile devices and the emergence of cloud computing, mobile cloud computing has gained widespread interest. In mobile cloud computing, a large-scale collection of mobile devices cooperate with each other to provide a cloud ...
POEM: On Establishing a Personal On-Demand Execution Environment for Mobile Cloud Applications
MS '15: Proceedings of the 2015 IEEE International Conference on Mobile ServicesA distributed mobile cloud service model called "POEM" is presented to manage the mobile cloud resource and compose mobile cloud applications. POEM provides the following salient features: (a) it considers resource management not only between mobile ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
November 2021
271 pages
ISBN:9781450386098
DOI:10.1145/3470482
- General Chairs:
- Adriano César Machado Pereira,
- Leonardo Chaves Dutra da Rocha
Copyright © 2021 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
In-Cooperation
- SBC: Brazilian Computer Society
- CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
- CAPES: Brazilian Higher Education Funding Council
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 November 2021
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior).
Conference
WebMedia '21: Brazilian Symposium on Multimedia and the Web
November 5 - 12, 2021
Minas Gerais, Belo Horizonte, Brazil
Acceptance Rates
WebMedia '21 Paper Acceptance Rate 24 of 75 submissions, 32%;
Overall Acceptance Rate 270 of 873 submissions, 31%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 46Total Downloads
- Downloads (Last 12 months)3
- Downloads (Last 6 weeks)0
Reflects downloads up to 09 Nov 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in