Survey on Crowd Sourced E-Health Networks

Survey on Crowd Sourced E-Health Networks

Authors

  • Aljawharah M. Almuhana 1College of Computer Science and Software Engineering, Hail University, UOH Hail, Kingdom of Saudi Arabia.
  • Kusum Yadav College of Computer Science and Software Engineering, Hail University, UOH Hail, Kingdom of Saudi Arabia.

Keywords:

Crowed, E-health, Networks, Buffer minimization

Abstract

By using the reliable data congestion which turns out to be very essential, particularly in enormous information timeline, in context of wide adaption of universal crowd sourced medical service’s members. Since the crowd-sourced e-health organizations have discontinuous the availability of its remote medicinal services. the information clog investigation is a major issue. The information blockage examination may be acknowledged by axing the quantity of sent duplicates, however, at times, it may not claim the changing system conditions well. Adjusting parcel-sending conditions progressively through identifying continuous system condition can be the good way to comprehend this issue. In view of this thought in this paper, an upgraded steering calculation called Lessened Variable Neighbourhood Seek Based Shower and Hold Up (RSW) is suggested. The current system situations will be assessed and quantized as a continuous limit to adjusts the edge for information clog control. Reproduction demonstrates that the proposed calculation expands information parcel conveyance likelihood, and advance the overhead proportion significantly, that may be doing 10 times lower than that of standard calculation.

References

Wang, K., Qi, X., Shu, L., Deng, D. J., & Rodrigues, J. J. (2016). Toward trustworthy crowdsourcing in the social internet of things. IEEE Wireless Communications, 23(5), 30-36. 2. Allahbakhsh, M., Benatallah, B., Ignjatovic, A., Motahari-Nezhad, H. R., Bertino, E., & Dustdar, S. (2013). Quality control in crowdsourcing systems: Issues and directions. IEEE Internet Computing, 17(2), 76-81. 3. Wang, K., Zhuo, L., Shao, Y., Yue, D., & Tsang, K. F. (2016). Toward distributed data processing on intelligent leak-points prediction in petrochemical industries. IEEE Transactions on Industrial Informatics, 12(6), 2091-2102. 4. Spyropoulos, T., Psounis, K., & Raghavendra, C. S. (2008). Efficient routing in intermittently connected mobile networks: The single-copy case, ACM. IEEE Transactions on Networking. 5. Feng, Z., & Chin, K. W. (2012). A unified study of epidemic routing protocols and their enhancements. In 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum (pp. 1484-1493). IEEE. 6. Spyropoulos, T., Psounis, K., & Raghavendra, C. S. (2005, August). Spray and wait: an efficient routing scheme for intermittently connected mobile networks. In Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking (pp. 252-259). 7. Hansen, P., Mladenović, N., & Pérez, J. A. M. (2008). Variable neighbourhood search: methods and applications. 4OR, 6(4), 319-360. 8. Wang, K., Shao, Y., Shu, L., Han, G., & Zhu, C. (2015). LDPA: A local data processing architecture in ambient assisted living communications. IEEE Communications Magazine, 53(1), 56-63. 9. Wang, K., Shao, Y., Shu, L., Zhu, C., & Zhang, Y. (2016). Mobile big data fault-tolerant processing for ehealth networks. IEEE Network, 30(1), 36-42. 10. Wang, K., Mi, J., Xu, C., Zhu, Q., Shu, L., & Deng, D. J. (2016). Real-time load reduction in multimedia big data for mobile Internet. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 12(5s), 1-20. 11. Hentschel, U., Schmidt, A., & Polze, A. (2011, March). Predictable communication for mobile systems. In 2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (pp. 24-28). IEEE. 12. Cherkaoui, E. H., & Agoulmine, N. (2014, October). Context-aware mobility management with WiFi/3G offloading for ehealth WBANs. In 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom) (pp. 472-476). IEEE. 13. Nelson, S. C., Bakht, M., & Kravets, R. (2009, April). Encounter-based routing in DTNs. In IEEE INFOCOM 2009 (pp. 846-854). IEEE.

WASSN 2018 10 of 10

Dang, H., & Wu, H. (2010). Clustering and cluster-based routing protocol for delay-tolerant mobile networks. IEEE Transactions on Wireless Communications, 9(6), 1874-1881. 15. Elwhishi, A., Ho, P. H., Naik, K., & Shihada, B. (2012). A novel message scheduling framework for delay tolerant networks routing. ieee transactions on parallel and distributed systems, 24(5), 871-880. 16. Wu, J., & Wang, Y. (2012, March). Social feature-based multi-path routing in delay tolerant networks. In 2012 Proceedings IEEE INFOCOM (pp. 1368-1376). IEEE. 17. Tournoux, P. U., Leguay, J., Benbadis, F., Whitbeck, J., Conan, V., & De Amorim, M. D. (2010). Density-aware routing in highly dynamic DTNs: The rollernet case. IEEE Transactions on Mobile Computing, 10(12), 1755-1768. 18. Wang, Y., Wu, J., & Yang, W. S. (2013). Cloud-based multicasting with feedback in mobile social networks. IEEE Transactions on Wireless Communications, 12(12), 6043-6053. 19. Patel, V. G., Oza, T. K., & Gohil, D. M. (2013). Vibrant energy aware spray and wait routing in delay tolerant network. Journal of Telematics and Informatics, 1(1), 43-47. 20. Jones, E. P., Li, L., Schmidtke, J. K., & Ward, P. A. (2007). Practical routing in delay-tolerant networks. IEEE Transactions on Mobile Computing, 6(8), 943-959. 21. Liu, J., Tang, M., & Yu, G. (2012, August). Adaptive spray and wait routing based on relay-probability of node in DTN. In 2012 International Conference on Computer Science and Service System (pp. 1138-1141). IEEE. 22. Spyropoulos, T., Psounis, K., & Raghavendra, C. S. (2007, March). Spray and focus: Efficient mobility-assisted routing for heterogeneous and correlated mobility. In Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07) (pp. 79-85). IEEE. 23. Medjiah, S., Taleb, T., & Ahmed, T. (2014). Sailing over data mules in delay-tolerant networks. IEEE Transactions on Wireless Communications, 13(1), 5-13. 24. Kishore, N., Jain, S., & Soares, V. N. (2013, July). An empirical review on the spray and wait based algorithms for controlled replication forwarding in delay tolerant networks. In 2013 Tenth International Conference on Wireless and Optical Communications Networks (WOCN) (pp. 1-5). IEEE. 25. Zheng, E., & Luo, Q. X. (2012). Spray and wait routing based on ACK-mechanism in disruption tolerant networks. Jisuanji Yingyong/ Journal of Computer Applications, 32(2), 367-369. 26. Guvenir, H. A., Acar, B., & Muderrisoglu, H. (1998). Arrhythmia data set in UCI machine learning repository. UC Irvine. 27. Shao, Y., Wang, K., Shu, L., Deng, S., & Deng, D. J. (2016). Heuristic optimization for reliable data congestion analytics in crowdsourced eHealth networks. IEEE Access, 4, 9174-9183

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Published

2021-09-19

How to Cite

Almuhana , A. ., & Yadav, K. . (2021). Survey on Crowd Sourced E-Health Networks: Survey on Crowd Sourced E-Health Networks. WAS Science Nature (WASSN) ISSN: 2766-7715, 1(1). Retrieved from https://worldascience.org/journals/index.php/wassn/article/view/28

Issue

Section

Computer Science & Mathematics