Difference between revisions of "Tutorial:Must read"
From MobiNetS
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===SDN/NFV related=== | ===SDN/NFV related=== | ||
* Tran, T.X., Hajisami, A., Pandey, P. and Pompili, D., 2017. [https://arxiv.org/pdf/1612.03184 Collaborative mobile edge computing in 5G networks: New paradigms, scenarios, and challenges]. IEEE Communications Magazine, 55(4), pp.54-61. | |||
* Xu, J., Chen, L. and Zhou, P., 2018, April. [https://arxiv.org/pdf/1801.05868 Joint service caching and task offloading for mobile edge computing in dense networks]. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications (pp. 207-215). IEEE. | |||
* Cziva, R. and Pezaros, D.P., 2017. [http://eprints.gla.ac.uk/138001/7/138001.pdf Container network functions: bringing NFV to the network edge]. IEEE Communications Magazine, 55(6), pp.24-31. | |||
* | |||
===Other interesting topics=== | ===Other interesting topics=== | ||
Revision as of 11:23, 9 October 2019
This page shows the must-read papers for different topics.
Low-power wireless
LoRa
- Liando, J.C., Gamage, A., Tengourtius, A.W. and Li, M., 2019. Known and unknown facts of LoRa: Experiences from a large-scale measurement study. ACM Transactions on Sensor Networks (TOSN), 15(2), p.16.
- Georgiou, O., & Raza, U. (2017). Low power wide area network analysis: Can LoRa scale?. IEEE Wireless Communications Letters, 6(2), 162-165.
- Sundaram, J.P.S., Du, W. and Zhao, Z., 2019. A Survey on LoRa Networking: Research Problems, Current Solutions and Open Issues. IEEE COMST, 2019.
Ad hoc protocols
- Akkaya, K. and Younis, M., 2005. A survey on routing protocols for wireless sensor networks. Ad hoc networks, 3(3), pp.325-349.
- Hagedorn, A., Starobinski, D. and Trachtenberg, A., 2008, April. Rateless deluge: Over-the-air programming of wireless sensor networks using random linear codes. In IPSN 2008 (pp. 457-466). IEEE.
- Ferrari, F., Zimmerling, M., Thiele, L. and Saukh, O., 2011, April. Efficient network flooding and time synchronization with glossy. In Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (pp. 73-84). IEEE.
- Guo, S., Kim, S.M., Zhu, T., Gu, Y. and He, T., 2011, October. Correlated flooding in low-duty-cycle wireless sensor networks. In 2011 19th IEEE International Conference on Network Protocols (pp. 383-392). IEEE.
- Biswas, S. and Morris, R., 2004. Opportunistic routing in multi-hop wireless networks. ACM SIGCOMM Computer Communication Review, 34(1), pp.69-74.
Other interesting topics
- Gao, Y., Dong, W., Chen, C., Bu, J., Guan, G., Zhang, X. and Liu, X., 2013, October. Pathfinder: Robust path reconstruction in large scale sensor networks with lossy links. In 2013 21st IEEE International Conference on Network Protocols (ICNP) (pp. 1-10). IEEE.
- Kim, S.M. and He, T., 2015, September. Freebee: Cross-technology communication via free side-channel. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking (pp. 317-330). ACM.
- Liang, C.J.M., Chen, K., Priyantha, N.B., Liu, J. and Zhao, F., 2014, November. Rushnet: practical traffic prioritization for saturated wireless sensor networks. In Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems (pp. 105-118). ACM.
Edge computing
- Shi, W. and Dustdar, S., 2016. The promise of edge computing. Computer, 49(5), pp.78-81.
Offloading
- Chen, X., Jiao, L., Li, W. and Fu, X., 2015. Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Transactions on Networking, 24(5), pp.2795-2808.
- Mach, P. and Becvar, Z., 2017. Mobile edge computing: A survey on architecture and computation offloading. IEEE Communications Surveys & Tutorials, 19(3), pp.1628-1656.
- Mao, Y., Zhang, J. and Letaief, K.B., 2016. Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE Journal on Selected Areas in Communications, 34(12), pp.3590-3605.
Wireless distributed learning
- Konečný, J., McMahan, H.B., Yu, F.X., Richtárik, P., Suresh, A.T. and Bacon, D., 2016. Federated learning: Strategies for improving communication efficiency. arXiv preprint arXiv:1610.05492.
- Bonawitz, K., Eichner, H., Grieskamp, W., Huba, D., Ingerman, A., Ivanov, V., Kiddon, C., Konecny, J., Mazzocchi, S., McMahan, H.B. and Van Overveldt, T., 2019. Towards federated learning at scale: System design. arXiv preprint arXiv:1902.01046.
- Wang, X., Han, Y., Wang, C., Zhao, Q., Chen, X. and Chen, M., 2019. In-edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning. IEEE Network.
- Tran, T.X., Hajisami, A., Pandey, P. and Pompili, D., 2017. Collaborative mobile edge computing in 5G networks: New paradigms, scenarios, and challenges. IEEE Communications Magazine, 55(4), pp.54-61.
- Xu, J., Chen, L. and Zhou, P., 2018, April. Joint service caching and task offloading for mobile edge computing in dense networks. In IEEE INFOCOM 2018-IEEE Conference on Computer Communications (pp. 207-215). IEEE.
- Cziva, R. and Pezaros, D.P., 2017. Container network functions: bringing NFV to the network edge. IEEE Communications Magazine, 55(6), pp.24-31.