Work place: National University of Computer and Emerging Sciences, Islamabad, 44000, Pakistan
E-mail: Waseem.Shahzad@nu.edu.pk
Website:
Research Interests: Evolutionary Computation, Computer Architecture and Organization, Data Mining, Data Structures and Algorithms
Biography
Waseem Shahzad is currently working as an Associate Professor and Head of the department of Computer Science at National University of Computer and Emerging Sciences, Islamabad, Pakistan. His areas of interest are machine learning, data mining and knowledge discovery, data warehousing, big data, and evolutionary computing. He has several research publications in these areas.
By Kashif Munir Ehtesham Zahoor Waseem Shahzad Syed Junaid Hussain
DOI: https://doi.org/10.5815/ijcnis.2016.11.03, Pub. Date: 8 Nov. 2016
Massive increase in the mobile data traffic volume has recently resulted in a big interest towards the distributed mobility management solutions that aim to address the limitations and drawbacks of centralized mobility management. Location management is an important requirement in a distributed mobility management environment. To provide seamless Internet data services to a mobile node, the location of a mobile node is stored and periodically updated on a location server through a location update message that is sent by the mobile node. In this paper, we propose an intelligent approach of setting the period of sending location update messages on the basis of a mobile node’s patterns of data sessions and IP handovers. We use a machine learning approach on the location server. The results show that our approach significantly reduces the signaling load of the location management and the overall reduction is more than 50%.
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