Essential links


Laboratory of Computational Intelligence and Robotics



Head: Dr. Vali Derhami


Technician: Ms. Fahime Pakzaban

Address: Computer Eng. Dept., Yazd University, Yazd, Iran

Telephone: +98 (35) 31232365

Service-Oriented Enterprise Architecture (SOEA) Lab



Head: Dr. SeyedAkbar Mostafavi


Technicians: Farzaneh Nadi, Elham Barkhordari

Address: Ground floor, Faculty of Engineering (1), Yazd University


Introduction: SOEA lab was established in 2017. This lab focuses on design, development and deployment of integrated Information systems and enterprise architectures in the enterprises.

The main activities of SOEA lab include:

- Development of architecture reference models and frameworks

- Monitoring, assessment and certification

- Integration of information systems and development of service-oriented architecture

- Education, promotion of culture and preparation of organizations for implementation of architectural design

- Capacity building and institution building at universities and technical-research centers

- Providing the grounds for setting rules, directives and legal incentives for enterprise architecture

- Currently, 2 PhD. researchers, 2 PhD. students, 3 MSc. students and 2 staff workers collaborate on the research projects.

- The current active projects of the lab include service-oriented enterprise architecture in Yazd Municipality and comparative enterprise architecture in Yazd Regional Electricity Company.

Intelligent Connectivity Research laboratory




Head: Dr. Mojtaba Matinkhah


Introduction: How the Combination of 5G, AI, SDN and IoT is set to Change Everything

 - Research Topic 1: An Evolutionary Solution for Service Delay Minimization in Fog Computing

Fog computing is an emerging paradigm that extends resource computation to the edge of the networks where it avails services closely to end users with closer proximity to end-users. The advent of Fog Computing (FC) caused reduction in the services of Terminal nodes (TNs) which are the sensors and actuators of the Internet of Things (IoT) architecture. In this research, we propose a service delay minimization model in FC that will increase accessibility of resources to the Fog nodes to the Cloud datacenter. FC gives the idea as a very promising computing model for location, time, and delay sensitive applications supporting vertically-isolated, latency-sensitive applications by providing ubiquitous, scalable and distributed computing, storage, and network connectivity. The aforesaid characteristics make FC a really appropriate interface between the IoTs and Cloud. The Fog nodes (FNs) offer load balancing, optimization of network traffic, and content filtering as well as the main computation services which conventionally only belong to the Cloud servers. We introduce a new model for service minimizing delay in fog computing where simulated results depicted that the proposed approach intensively minimizes delay through determining the appropriate fog node for the user’s request execution.

- Research Topic 2: An Evolutionary Solution for Energy Efficiency in Fog Computing

The fog computing is a new paradigm that with cloud Computing development on the edge of the network, in addition to providing useful solutions to meet the IoT requirements, it will provide outstanding capabilities to develop and apply new technologies to the users. We take into consideration the efficiency of power efficiency according to the amount of energy consumption and response time in the processing of an incoming workload unit.

- Research Topic 3: A Fast Machine Learning for 5G Beam Selection In Unmanned Aerial Vehicle

The 5G setup plans to exploit the unoptimized mmWave bands (10-300 GHz). This unoptimized band is due to the loss of mmWave bands, like high path loss and penetration loss. Nonetheless, because of: (i) directional transmission paving way for beamforming to recompense for the high path loss, and (ii) higher placement density of base stations is the best alternative for short communication range in mmWave bands (100-150 m). The advances in technology and innovation of unmanned aerial vehicles (UAVs) necessitates many opportunities and uncertainties. UAVs are agile and can fly in and out of areas that are either dangerous for humans or have complex terrains making ground robots unsuitable. UAV is defined as an aerial vehicle that does not hold pilot on it, uses aerodynamic forces to provide vehicle lift, can fly autonomously or semi-autonomous, can be recoverable, and can carry a (non) or deadly payload. It is controlled either autonomously by onboard computers or by the remote control of a pilot on the ground through wireless communication links in our case 5G. Although the fast learning algorithm solved the problem of beam selection for 2-dimensional scenarios. We will modify it to face 3-dimensional scenarios for UAV. Therefore, we propose some modifications to the fast learning algorithm to address the problem of beam selection in 5G UAV. We model beam selection with environmental awareness in mmWave UAV to achieve close optimal performance on the average period through learning from the available situation.

- Research Topic 4: Reducing Jitter in Software Defined-Internet of Things using Reinforcement Learning

In this thesis, we use Software Defined network as backbone in internet of things. Massive number of heterogeneous smart objects and influx of data from different nodes generate unpredictable traffic in the IoT network. This can cause congestion and jitter in IoT. One of the reasons that causes congestion is incorrect routing in the IoT. Therefore, we consider an optimal routing algorithm. The use of a useful routing algorithm helps us to reduce congestion and jitter in the network. For an optimal routing, we can use Dijkstra algorithm however, Dijkstra algorithm while calculates a shortest path to the choose destination, it sends all traffics to the same destination from that calculated path. As a result, congestion and jitter will happen in the heterogeneous network continuously. In the heterogeneous network, we are not able to predict network traffic and on the other hand, we need to select an optimal path to the destination, thus we used reinforcement learning to select an optimal path in the network. In the network, traffic load is our dynamic parameter and learning agent will learn when traffic load become a little more in the selected shortest path, it will change optimal path to the destination and send traffic from another path until reduce congestion and jitter in the heterogeneous network. In this thesis, we want to improve quality of service in software defined-internet of things through reducing jitter in the heterogeneous IoT network, it will help us to achieve user satisfaction in the IoT network.

 - Research Topic 5: Improving the Resources Allocation on Fog Computing-Based Internet of Things Networks

Generation of large volumes of data by the Internet of Things, and the need for data processing in the internet cloud is emerging as a challenge. Current cloud models are not designed to process a large amount of data on a real-time basis. The conventional approach is to transfer all data from the edge of the network to the data centers for processing, which increases the delay time. In addition, the traffic associated with the equipment will be much greater than the bandwidth capacity available. Cloud computing enables data processing near to IoT equipment. This technology reduces the delay in responding to user requests by eliminating the way data is sent to the cloud. In order to achieve better performance in fog computing and to reduce the latency of real-time systems in the IoT, we need appropriate resource management. In addition, resource allocation between fog nodes is accompanied by challenges. In this thesis, we propose a method to improve resource allocation to fog nodes by using heuristic methods.

APA (CERT) Center



Head: Dr. Fazlollah Adibnia


Address: Yazd University, Yazd, Iran

Introduction: The Yazd University APA (CERT) Center was established in 2009 and provides the following services in the field of cyber security:

Holding workshops: network security, system security, secure programming and penetration testing.

Penetration testing: Application software and websites penetration testing, consulting to address relevant vulnerabilities, and providing a security certificate in accordance with the OWASP world standard. Network and system penetration testing.

Security Umbrella System: DNS is a vital network infrastructure for communicating to all users, applications and devices connected to the Internet. Although not actually designed for security, today we are facing a proliferation of DNS attacks on networks and disrupting critical systems. Provide security consultation. Consultation on setting up a CERT (Computer Emergency Response Team) Center (APA).Conducting scientific research on application and network security.