Hussein Zangoti

Ph.D. Candidate

Lecture Information:
  • October 27, 2022
  • 2:00 PM
  • Zoom

Speaker Bio

Hussein Zangoti is a Ph.D. candidate at the Knight Foundation School of Computing and Information Sciences (KFSCIS), Florida International University (FIU), under the supervision of Professor Niki Pissinou. Hussein received his B.Sc. in Computer Science from Jazan University, a public research university based in Saudi Arabia, and his M.Sc. in Computer Science from Monmouth University. Since 2010, Hussein is a lecturer on leave and worked as a head in the Computer and Network Engineering Department at Jazan University, one of the largest public, nonprofit institutions of higher education in the Kingdom of Saudi Arabia.

Hussein is funded through Jazan University, Saudi Arabia. During his doctoral studies, Hussein served as a graduate research mentor for the NSF-sponsored Research Experience for Undergraduates (REU) and Research Experience for Teachers (RET) programs for three consecutive years and a reviewer for peer-reviewed conferences in the area of computer and networking. Hussein’s research publications and interests include IoT, blockchain, networking, and security.

This lecture will be held on Zoom.

Meeting ID: 982 4010 4563
Passcode: 1L2XLN


The age of combining sensing, processing and communication in moving, resource-constrained physical devices that connect and exchange data with other devices and systems other wireless communications networks, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Internet of Thing (mIoT) applications. As IoT becomes more ubiquitous, safeguarding transactions becomes a critical piece of information and an important factor for commercial success. Although it has been shown that blockchain can secure IoT, research and development in this area are still in progress. For example, current blockchain models for mobile IoT assume there are fixed, powerful edge devices capable of providing global communication to all the nodes in the network. However, due to the mobile nature of IoT or network partitioning problems, nodes can move out of a cell area and split into smaller independent peer-to-peer subnetworks. Existing blockchain structures either do not support the network partitioning problem or have limitations. This research stems from the recognition that the wide applicability of mobile IoT will remain elusive unless new techniques are introduced to efficiently represent moving objects by organizing and partitioning the data points based on specific conditions of moving through time and space of resource-constrained devices.

The research is one of the first steps that aims to address the challenges of blockchain-based applications in resource constrained, self-organized and self-configured mobile IoT devices facing split and merge problems due to frequent node mobility and network partitioning. Our objective is to design and develop (1) a multidimensional, graph-based blockchain structure that utilizes k-dimensional spatiotemporal space to scan only a few blocks for any blockchain operations; (2) a method for the blockchain to continue to provide its service when the network of mIoT miners is partitioned or if the network merges again with data that remain available and consistent; and (3) a blockchain-based deep learning for higher speed and delivery of data in mIoT. The class of application environments for which our research and approach are suitable and useful includes time and space dependent applications or systems that require some form of action, such as cyber defence, defence logistics support and the networking of the defense Internet of Military Things, tactical-level data management, event sharing or other lightweight dynamically data driven applications.