Turning Android Smartphones into Dew Devices to Mitigate Offloading Limitations in Unstable Networks

• Filipe de Matos UFC
• Paulo A. L. Rego UFC
• Fernando Trinta UFC

DOI: https://doi.org/10.5753/semish.2025.8805

Abstract

Offloading helps overcome mobile devices’ computational and energy limits, but its performance depends on an efficient server language and a stable network, which are not always guaranteed. Dew Computing converts client devices into Dew devices, enabling local execution of server processes and prioritizing internal interactions. This work defines the Duplication Management Service (SGD), which transforms Android smartphones into Dew devices and evaluates its impact. Tests with real devices showed that Dew enables tasks previously infeasible, reduces network traffic by up to 2.5x, and computes tasks up to 2.9x faster in high competition scenarios despite consuming up to 19.4x more energy. It is a promising option for unstable networks or low bandwidth.

References

Araújo, M., Maia, M. E. F., Rego, P. A. L., and De Souza, J. N. (2020). Performance analysis of computational offloading on embedded platforms using the gRPC framework. In 8th International Workshop on ADVANCEs in ICT Infrastructures and Services (ADVANCE 2020), pages 1–8.

Bera, S., Dey, T., Mukherjee, A., and Buyya, R. (2023). E-cropreco: a dew-edge-based multi-parametric crop recommendation framework for internet of agricultural things. The Journal of Supercomputing, 79:11965–11999.

Bugden, W. and Alahmar, A. (2022). The safety and performance of prominent programming languages. International Journal of Software Engineering and Knowledge Engineering, 32:713–744.

Cunha, S. a., Silva, L., Saraiva, J. a., and Fernandes, J. a. P. (2024). Trading runtime for energy efficiency: Leveraging power caps to save energy across programming languages. In Proceedings of the 17th ACM SIGPLAN International Conference on Software Language Engineering, SLE ’24, page 130–142, New York, USA. ACM.

De, D. (2016). Mobile Cloud Computing: Architectures, Algorithms and Applications. CRC Press.

de Matos, F., Oliveira, W., Castor, F., Rego, P., and Trinta, F. (2022). Multi-language offloading service: An android service aimed at mitigating the network consumption during computation offloading. In Proceedings of the Brazilian Symposium on Multimedia and the Web, page 329–338, New York, US. ACM.

de Matos., F., Rego., P., and Trinta., F. (2021). An empirical study about the adoption of multi-language technique in computation offloading in a mobile cloud computing scenario. In Proceedings of the 11th International Conference on Cloud Computing and Services Science - CLOSER,, pages 207–214. INSTICC, SciTePress.

De Matos, F., Rego, P. A. L., and Trinta, F. (2023). Evaluating offloading scalability using a multi-language approach on cellular networks. In 2023 IEEE 20th Consumer Communications & Networking Conference, pages 125–130, Piscataway, US. IEEE.

Garrocho, C. T. B. and Oliveira, R. A. R. (2020). Counting time in drops: views on the role and importance of smartwatches in dew computing. Wireless Networks, 26:3139–3157.

Georgiou, S., Kechagia, M., Louridas, P., and Spinellis, D. (2018). What are your programming language’s energy-delay implications? In 2018 IEEE/ACM 15th International Conference on Mining Software Repositories, pages 303–313, New York, US. ACM.

Georgiou, S. and Spinellis, D. (2019). Energy-delay investigation of remote inter-process communication technologies. Journal of Systems and Software, 162:1–14.

Gushev, M. (2020). Dew computing architecture for cyber-physical systems and iot. Internet of Things, 11:1–9.

Oliveira, W., Moraes, B., Castor, F., and Fernandes, J. P. (2023). Ebserver: Automating resource-usage data collection of android applications. In 2023 IEEE/ACM 10th International Conference on Mobile Software Engineering and Systems, pages 55–59, Piscataway, US. Institute of Electrical and Electronics Engineers.

Pedhadiya, M. K., Jha, R. K., and Bhatt, H. G. (2019). Device to device communication: A survey. Journal of Network and Computer Applications, 129:71–89.

Pereira, R., Couto, M., Ribeiro, F., Rua, R., Cunha, J., Fernandes, J. P., and Saraiva, J. (2021). Ranking programming languages by energy efficiency. Science of Computer Programming, 205:1–30.

Ray, P. P. (2019). Minimizing dependency on internetwork: Is dew computing a solution? Transactions on Emerging Telecommunications Technologies, 30:1–13.

Rego, P. A., Costa, P. B., Coutinho, E. F., Rocha, L. S., Trinta, F. A., and Souza, J. N. d. (2017). Performing computation offloading on multiple platforms. Computer Communications, 105(C):1–13.

Robaina, G. and Fiorese, A. (2023). Gaming on the edge: Uma arquitetura de computação na borda para jogos em dispositivos móveis. In Anais do XLI Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 574–587, Porto Alegre, RS, Brasil. SBC.

Shakarami, A., Shahidinejad, A., and Ghobaei-Arani, M. (2020). A review on the computation offloading approaches in mobile edge computing: A game-theoretic perspective. Software: Practice and Experience, 50:1719–1759.

Singh, P., Gaba, G. S., Kaur, A., Hedabou, M., and Gurtov, A. (2023). Dew-cloud-based hierarchical federated learning for intrusion detection in iomt. IEEE Journal of Biomedical and Health Informatics, 27:722–731.

Wang, Y. (2015). Cloud-dew architecture. International Journal of Cloud Computing, 4:199–210.

Yannibelli, V., Hirsch, M., Toloza, J., Majchrzak, T. A., Zunino, A., and Mateos, C. (2023). Speeding up smartphone-based dew computing: In vivo experiments setup via an evolutionary algorithm. Sensors, 23:1–22.