Scalable Dew Computing
Source abstract
Abstract
Dew computing differs from the classical cloud and edge computing by bringing devices closer to the end-users and adding autonomous processing independent from the Internet, but it is still able to collaborate with other devices to exchange information on the Internet. The difference is expressed also on scalability, since edge and cloud providers can provide (almost endless) resources, and in the case of dew computing the scalability needs to be realized on the level of devices, instead of servers. In this paper, we introduce an approach to provide deviceless and thingless computing and ensure scalable dew computing. The deviceless approach allows functions to be executed on nearby devices found closer to the user, and the thingless approach goes even further, providing scalability on a low-level infrastructure that consists of multiple things, such as IoT devices. These approaches introduce the distribution of computing to other smart devices or things on a lower architectural level. Such an approach enhances the existing dew computing architectural model as a sophisticated platform for future generation IoT systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: IoT and Edge/Fog Computing · Mobile Crowdsensing and Crowdsourcing · IoT Networks and Protocols
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Computer Science and Engineering, Ss Cyril and Methodius University, 1000 Skopje, North Macedonia
Funding
European High-Performance Computing Joint Undertaking (JU) · European Union‘s Horizon 2020 research and innovation programme
References (50)
Show source-provided references
1. Above the clouds: A berkeley view of cloud computing
2. A view of cloud computing10.1145/1721654.1721672 ↗
3. That ‘internet of things’ thing
4. The internet of things: A survey10.1016/j.comnet.2010.05.010 ↗
5. Post-cloud computing paradigms: A survey and comparison10.23919/TST.2017.8195353 ↗
6. Pan, Y., Thulasiraman, P., and Wang, Y. (2018, January 29–30). Overview of Cloudlet, Fog Computing, Edge Computing, and Dew Computing. Proceedings of the 3rd International Workshop on Dew Computing, Toronto, ON, Canada.
7. The promise of edge computing10.1109/MC.2016.145 ↗
8. The case for VM-based cloudlets in mobile computing10.1109/MPRV.2009.82 ↗
9. Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012, January 17). Fog computing and its role in the Internet of things. Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, Helsinki, Finland.10.1145/2342509.2342513 ↗
10. Edge-centric computing: Vision and challenges10.1145/2831347.2831354 ↗
11. Patel, M., Naughton, B., Chan, C., Sprecher, N., Abeta, S., and Neal, A. (2014). Mobile-Edge Computing Introductory Technical White Paper, ETSI.
12. Cloud-dew architecture10.1504/IJCC.2015.071717 ↗
13. Edge computing: Vision and challenges10.1109/JIOT.2016.2579198 ↗
14. Scalable distributed computing hierarchy: Cloud, fog and dew computing
15. Implementation of a Horizontal Scalable Balancer for Dew Computing Services
16. Gusev, M. (2021, January 12–16). What makes Dew computing more than Edge computing for Internet of Things. Proceedings of the 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), Madrid, Spain.10.1109/COMPSAC51774.2021.00269 ↗
17. Jonas, E., Schleier-Smith, J., Sreekanti, V., Tsai, C.C., Khandelwal, A., Pu, Q., Shankar, V., Carreira, J., Krauth, K., and Yadwadkar, N. (2019). Cloud programming simplified: A berkeley view on serverless computing. arXiv.
18. Serverless is more: From paas to present cloud computing10.1109/MIC.2018.053681358 ↗
19. Gusev, M. (2018, January 29–30). Edge and Dew Computing for Streaming IoT. Proceedings of the 3rd International Workshop on Dew Computing, Toronto, ON, Canada.
20. Glikson, A., Nastic, S., and Dustdar, S. (2017, January 22–24). Deviceless edge computing: Extending serverless computing to the edge of the network. Proceedings of the 10th ACM International Systems and Storage Conference, Haifa, Israel.10.1145/3078468.3078497 ↗
21. Benomar, Z., Longo, F., Merlino, G., and Puliafito, A. (2021, January 6–10). Deviceless: A Serverless Approach for the Internet of Things. Proceedings of the 2021 ITU Kaleidoscope: Connecting Physical and Virtual Worlds (ITU K), Geneva, Switzerland.10.23919/ITUK53220.2021.9662096 ↗
22. Going Back to the Roots: The Evolution of Edge Computing, An IoT Perspective10.1109/MIC.2018.022021657 ↗
23. Counting time in drops: Views on the role and importance of smartwatches in dew computing10.1007/s11276-019-02046-y ↗
24. Minimizing dependency on internetwork: Is dew computing a solution?10.1002/ett.3496 ↗
25. Definition and Categorization of Dew Computing
26. An introduction to dew computing: Definition, concept and implications10.1109/ACCESS.2017.2775042 ↗
27. A deviceless edge computing approach for streaming IoT applications10.1109/MIC.2019.2892219 ↗
28. Seif, A.A., and El-Saber, N. (2017, January 12–13). Scalable distributed-computing iot applied architecture with semantic interoperable gateway. Proceedings of the 3rd Africa and Middle East Conference on Software Engineering, Cairo, Egypt.10.1145/3178298.3178306 ↗
29. Garrocho, C.T.B., da Cunha Cavalcanti, C.F.M., and Oliveira, R.A.R. (2020, January 24–27). Performance evaluation of industrial internet of things services in devices of cloud-fog-dew-things computing. Proceedings of the 2020 X Brazilian Symposium on Computing Systems Engineering (SBESC), Florianópolis, Brazil.10.1109/SBESC51047.2020.9277837 ↗
30. Gusev, M. (2021, January 12–16). Serverless and Deviceless Dew Computing: Founding an Infrastructureless Computing. Proceedings of the 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), Madrid, Spain.10.1109/COMPSAC51774.2021.00273 ↗
31. Kritikos, K., and Skrzypek, P. (2018, January 17–20). A review of serverless frameworks. Proceedings of the 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion), Zurich, Switzerland.10.1109/UCC-Companion.2018.00051 ↗
32. A Serverless Real-Time Data Analytics Platform for Edge Computing10.1109/MIC.2017.2911430 ↗
33. Wang, L., Li, M., Zhang, Y., Ristenpart, T., and Swift, M. (2018, January 11–13). Peeking behind the curtains of serverless platforms. Proceedings of the 2018 USENIX Annual Technical Conference (USENIX ATC 18), Boston, MA, USA.
34. Hellerstein, J.M., Faleiro, J., Gonzalez, J.E., Schleier-Smith, J., Sreekanti, V., Tumanov, A., and Wu, C. (2018). Serverless computing: One step forward, two steps back. arXiv.
35. Baldini, I., Castro, P., Chang, K., Cheng, P., Fink, S., Ishakian, V., Mitchell, N., Muthusamy, V., Rabbah, R., and Slominski, A. (2017). Serverless computing: Current trends and open problems. Research Advances in Cloud Computing, Springer.10.1007/978-981-10-5026-8_1 ↗
36. Becker, S., Schmidt, F., and Kao, O. (2021, January 28–30). EdgePier: P2P-based Container Image Distribution in Edge Computing Environments. Proceedings of the 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC), Austin, TX, USA.10.1109/IPCCC51483.2021.9679447 ↗
37. Next generation technologies for smart healthcare: Challenges, vision, model, trends and future directions10.1002/itl2.145 ↗
38. Nastic, S., and Dustdar, S. (2018). Towards deviceless edge computing: Challenges, design aspects, and models for serverless paradigm at the edge. The Essence of Software Engineering, Springer.10.1007/978-3-319-73897-0_8 ↗
39. Low Latency Geo-distributed Data Analytics10.1145/2829988.2787505 ↗
40. Cardellini, V., Grassi, V., Lo Presti, F., and Nardelli, M. (2016, January 20–24). Optimal Operator Placement for Distributed Stream Processing Applications. Proceedings of the DEBS ’16 10th ACM International Conference on Distributed and Event-based Systems, Irvine, CA, USA.10.1145/2933267.2933312 ↗
41. Osmotic Flow: Osmotic Computing + IoT Workflow10.1109/MCC.2017.22 ↗
42. de Lara, E., Gomes, C.S., Langridge, S., Mortazavi, S.H., and Roodi, M. (2016, January 27–28). Poster Abstract: Hierarchical Serverless Computing for the Mobile Edge. Proceedings of the 2016 IEEE/ACM Symposium on Edge Computing (SEC), Washington, DC, USA.10.1109/SEC.2016.37 ↗
43. Gascon-Samson, J., Rafiuzzaman, M., and Pattabiraman, K. (2017, January 11). ThingsJS: Towards a Flexible and Self-adaptable Middleware for Dynamic and Heterogeneous IoT Environments. Proceedings of the M4IoT ’17 4th Workshop on Middleware and Applications for the Internet of Things, Las Vegas, NV, USA.10.1145/3152141.3152391 ↗
44. Workload and capacity optimization for cloud-edge computing systems with vertical and horizontal offloading10.1109/TNSM.2019.2937342 ↗
45. Latency-aware horizontal computation offloading for parallel processing in fog-enabled IoT10.1109/JSYST.2021.3085566 ↗
46. Flores, H., Su, X., Kostakos, V., Ding, A.Y., Nurmi, P., Tarkoma, S., Hui, P., and Li, Y. (2017, January 13–17). Large-scale offloading in the Internet of Things. Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, HI, USA.10.1109/PERCOMW.2017.7917610 ↗
47. Mostafa, M.A.A.A., and Khater, A.M. (2019, January 9–11). Horizontal offloading mechanism for IoT application in fog computing using microservices case study: Traffic management system. Proceedings of the 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), Amman, Jordan.10.1109/JEEIT.2019.8717462 ↗
48. Higuchi, T., Ucar, S., and Altintas, O. (2019, January 4–7). Offloading tasks to vehicular virtual edge servers. Proceedings of the 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW), Monterey, CA, USA.10.1109/MASSW.2019.00040 ↗
49. Analyzing vertical and horizontal offloading in federated cloud and edge computing systems10.1007/s11235-021-00864-0 ↗
50. The computer for the 21st century10.1038/scientificamerican0991-94 ↗