Abstract
In the last few years, we have seen a significant increase both in the number and capabilities of mobile devices, as well as in the number of applications that need more and more computing and storage resources. Currently, in order to deal with this growing need for resources, applications make use of cloud services. This raises some problems, namely high latency, considerable use of energy and bandwidth, and the unavailability of connectivity infrastructures. Given this context, for some applications it makes sense to do part, or all, of the computations locally on the mobile devices themselves. In this paper we present Oregano, a framework for distributed computing on mobile devices, capable of processing batches or streams of data generated on mobile device networks, without requiring centralized services. Contrary to current state-of-the-art, where computations and data are sent to worker mobile devices, Oregano performs computations where the data is located, significantly reducing the amount of exchanged data.
This work was supported by FCT-MCTES via project DeDuCe (PTDC/CCI-COM/32166/2017) and NOVA LINCS (UID/CEC/04516/2019).
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References
Cisco: Cisco Annual Internet Report (2018–2023) (2018). https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html. Accessed June 2020
Fernando, N., Loke, S.W., Rahayu, W.: Computing with nearby mobile devices: a work sharing algorithm for mobile edge-clouds. IEEE Trans. Cloud Comput. 7(2), 329–343 (2019). https://doi.org/10.1109/TCC.2016.2560163
Georgakopoulos, D., Jayaraman, P.P., Fazia, M., Villari, M., Ranjan, R.: Internet of things and edge cloud computing roadmap for manufacturing. IEEE Cloud Comput. 3(4), 66–73 (2016). https://doi.org/10.1109/MCC.2016.91
Habak, K., Ammar, M.H., Harras, K.A., Zegura, E.W.: Femto clouds: leveraging mobile devices to provide cloud service at the edge. In: 8th IEEE International Conference on Cloud Computing. CLOUD, pp. 9–16 (2015). https://doi.org/10.1109/CLOUD.2015.12
Halpern, M., Zhu, Y., Reddi, V.J.: Mobile CPU’s rise to power: quantifying the impact of generational mobile CPU design trends on performance, energy, and user satisfaction. In: IEEE International Symposium on High Performance Computer Architecture. HPCA, pp. 64–76 (2016). https://doi.org/10.1109/HPCA.2016.7446054
Miluzzo, E., Cáceres, R., Chen, Y.F.: Vision: mClouds - computing on clouds of mobile devices. In: 3rd ACM Workshop on Mobile Cloud Computing and Services. MCS, pp. 9–14 (2012). https://doi.org/10.1145/2307849.2307854
Nishio, T., Shinkuma, R., Takahashi, T., Mandayam, N.B.: Service-oriented heterogeneous resource sharing for optimizing service latency in mobile cloud. In: 1st International Workshop on Mobile Cloud Computing & Networking. MobileCloud, pp. pp. 19–26. ACM (2013). https://doi.org/10.1145/2492348.2492354
Pal, S.: Extending mobile cloud platforms using opportunistic networks: survey, classification and open issues. J. Univ. Comput. Sci. 21(12), 1594–1634 (2015). https://doi.org/10.3217/jucs-021-12-1594
Remédios, D., Teófilo, A., Paulino, H., Lourenço, J.: Mobile device-to-device distributed computing using data sets. In: 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous, pp. pp. 297–298. ACM (2015). https://doi.org/10.4108/eai.22-7-2015.2260273
Satyanarayanan, M., Bahl, P., Cáceres, R., Davies, N.: The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 14–23 (2009). https://doi.org/10.1109/MPRV.2009.64
Shi, C., Lakafosis, V., Ammar, M.H., Zegura, E.W.: Serendipity: enabling remote computing among intermittently connected mobile devices. In: 13th ACM International Symposium on Mobile Ad Hoc Networking and Computing. MobiHoc, pp. pp. 145–154 (2012). https://doi.org/10.1145/2248371.2248394
Shi, W., Cao, J., Zhang, Q., Li, Y., Xu, L.: Edge computing: vision and challenges. IEEE Internet Things J. 3(5), 637–646 (2016). https://doi.org/10.1109/JIOT.2016.2579198
Silva, J.A., Paulino, H., Lourenço, J.M., Leitão, J., Preguiça, N.M.: Time-aware reactive storage in wireless edge environments. In: 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous, pp. 238–247. ACM (2019). https://doi.org/10.1145/3360774.3360828
Silva, J., Silva, D., Marques, E.R.B., Lopes, L., Silva, F.: P3-mobile: parallel computing for mobile edge-clouds. In: 4th Workshop on CrossCloud Infrastructures & Platforms. CrossCloud@EuroSys, pp. pp. 5:1–5:7. ACM (2017). https://doi.org/10.1145/3069383.3069388
Teófilo, A., Remédios, D., Lourenço, J.M., Paulino, H.: GOCRGO and GOGO: two minimal communication topologies for WiFi-direct multi-group networking. In: 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous, pp. 232–241. ACM (2017). https://doi.org/10.1145/3144457.3144481
Zaharia, M., et al.: Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing. In: 9th USENIX Symposium on Networked Systems Design and Implementation. NSDI, pp. 15–28 (2012). https://doi.org/10.5555/2228298.2228301
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Sanches, P., Silva, J.A., Teófilo, A., Paulino, H. (2020). Data-Centric Distributed Computing on Networks of Mobile Devices. In: Malawski, M., Rzadca, K. (eds) Euro-Par 2020: Parallel Processing. Euro-Par 2020. Lecture Notes in Computer Science(), vol 12247. Springer, Cham. https://doi.org/10.1007/978-3-030-57675-2_19
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