A Survey on Improved Mobile Crowdsensing with Integration of Emerging Technologies

Authors

  • Bakul Panchal  Assistant Professor, Department of Computer Engineering L. D. College of Engineering, Ahmedabad, Gujarat, India

Keywords:

Customer’s impatience, Queue, System's performance

Abstract

This paper is to present the Queueing theory as an analytical tool for various real time situations. First, we discuss different types of queues with the concepts vacation, Customer’s impatience, server failure etc. Second, we look into different practical applications. It provides fundamental concepts of queueing models and their role in system’s performance. As we seek to design more and more sophisticated processing systems, Statistical performance evaluation has got lot of significance. The capability to forecast a projected system's per¬formance before one builds it is an extremely cost effective design instrument. In line to this, queueing theory is a tool for analysis of practical problems and has potential applications. Queueing models have wide range of applications in computer communication systems, manufacturing/production systems and inventory systems. There are many extensive works have been done in the Queueing theory over the past five decades. The motivation of this talk is to provide adequate information to analysts, industry people and others who are interested in using queuing theory to model congestion problems and want to locate the details of relevant models.

References

  1. Raghu K. Ganti, Fan Ye, and Hui Lei IBM T. J. Watson Research Center, Hawthorne, NY rganti, fanye, [email protected], “Mobile Crowdsensing: Current State and Future Challenges” .
  2. https://www.businesstoday.in/magazine/cover-story/story/wearable-tech-google-glass-jawbone-up-fitbit-flex-137630-2014-09-01
  3. Khalid Abualsaud, Tarek M. Elfouly, Tamer Khattab, Elias Yaacoub, Loay Sabry Ismail, Mohamed Hossam Ahmed, and Mohsen Guizani, “A Survey on Mobile Crowd-Sensing and Its Applications in the IoT Era” .
  4. IEEE Research Paper by Yohan Chon, Nicholas D. Lane, Fan Li, Hojung Cha, Feng Zhao, “Automatically Characterizing Places with Opportunistic CrowdSensing using Smartphones”.
  5. https://otonomo.io/blog/5-innovative-on-demand-car-services/
  6. Sciencedirect Research Paper by Alaa Tharwat, Hani Mahdi, Mohamed Elhosenyc, Aboul Ella Hassaniend, Recognizing human activity in mobile crowdsensing environment using optimized k-NN algorithms
  7. Privacy-preserving task allocation for edge computing-based mobile crowdsensing https://homomorphicencryption.org
  8. A Blockchain-based privacy preserving mechanism for mobile crowdsensing Hilmand Khan*, Hajra Khan, Ayesha Shauqat, Sibgha Tahir, Sarmad Hanif and Hafi z Hamza

Downloads

Published

2017-08-30

Issue

Section

Research Articles

How to Cite

[1]
Bakul Panchal, " A Survey on Improved Mobile Crowdsensing with Integration of Emerging Technologies, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.973-975, July-August-2017.