Research Interests

Network Science for Communications

Cloud Computing

Smart Grid, Smart Grid Communications

Network Resource Management

Traffic Engineering

Network Planning

Autonomic Networking

Optimization Theory and Applications

Mathematical Theory of Networks

Graph Theory and Network Analysis

Control Techniques for Data Networks

Network Algorithms

Green Communications

Wireless and Vehicular Networks

Next Generation Data Centers

VoIP

Bioinformatics
Thesis Summary
In my PhD thesis, I built a conceptual architecture for selfmanaging systems,
with special emphasis on core networks where robustness to environmental changes
are viewed as critical. The main objective of my thesis was to find a
theoretical framework to build, control, and maintain robust communication
networks. Motivated by ideas from Evolutionary Science, I tried to find a
survival value for communication networks to quantify their sensitivity to the
environmental changes (changes in topology, traffic, QoS parameters, and
community of interest). I used randomwalk betweenness (a metric from graph
theory) of a link per unit of link weight to capture the effect of topology,
load, and community of interest. I proved that this quantity is independent of
the link location (therefore, it is a global measure on the graph), and it is a
strictly convex function of link weights. I named this global value and used it
as the survival value of a network. In order to have a robust network, we need
to minimize Network Criticality.
As a part of my thesis, I developed a conceptual architecture for
selforganizing management systems, AutoNet, to control the allocation of
resources to the customers in order to maximize the robustness. The main idea
was to consider a management system as an evolutionary process that evolves
based on survivability and performance requirements. For my purposes, the
evolution should be in the direction of decreasing Network Criticality, which in
turn increases the network robustness. AutoNet consists of two autonomic loops,
the slow loop to control the longterm evolution of robustness throughout the
whole network, and the fast loop to account for shortterm performance and
robustness issues. AutoNet assigns separate Virtual Networks (VN) to different
customers based on their specific Service Level Agreements (SLA), and the
autonomic control loop tries to keep the customers' resources at the required
level without service interruption. I used Network Criticality as the main
control parameter and proposed appropriate algorithms for slow and fast loops of
AutoNet, to guide the network evolution in real time. For the fast loop, I
developed some flow assignment algorithms to engineer the traffic according to
the customer demands, and for the slow loop, I used SemiDefinite Programming (SDP)
approach to solve the convex optimization problem for Network Criticality in
order to do network (re)planning which is the main job of the slow loop.
Teaching Experience
Instructor
1. University of Ontario Institute of Technology (UOIT), Oshawa, Canada, Winter 2011, Course: "Modern Control Systems (ENGR 3100U)".
2. University of Ontario Institute of Technology (UOIT), Oshawa, Canada, Fall 2010, Course: "Digital Communications (ENGR 4130U)".
3.Azad University of Tehran, Department of Computer Science (CS), Tehran, Iran, 19961999.
4. Azad University of Saveh, Department of Electrical \& Computer
Engineering (ECE), Tehran, Iran, 19982001.