Research Area

Internet of Things

The Internet of Things (IoT) refers to a network comprised of physical objects capable of gathering and sharing electronic information. The Internet of Things includes a wide variety of “smart” devices, from industrial machines that transmit data about the production process to sensors that track information about the human body. Often, these devices use internet protocol (IP), the same protocol that identifies computers over the world wide web and allows them to communicate with one another. The goal behind the internet of things is to have devices that self report in real time, improving efficiency and bringing important information to the surface more quickly than a system depending on human intervention.

Research Interests

  • Connectivity, Software

  • Security, Distributed systems

  • Cyber-physical systems, Pervasive computing

  • Embedded systems, Mobile computing

  • Artificial intelligence, Machine learning

Wireless Sensor Networks/Wireless Body Area Networks

The sensor nodes are deployed either inside the phenonenon or very close to it. They may self-organize into clusters or collabrate together to complete a task that is issued by the users. In addition, the positions of these nodes do not nedd to be predefined. As a result, the sensor nodes are fit for many applications, e.g., location tracking and chemical detection in areas not easily accessible. Since sensing applications generates a large quantitiy of data, these data many be fused or aggregated together to lower energy consumption. The sensor nodes use their processing abilities to locally carry out simple computations and transmit only the required and partially processed data. In uses with intelligence and a better understanding of the environments. In the future, the wireless sensor networks many be an integral part of our lives, more so than the present-day personal computers.

A Wireless Body Area Network (WBAN) connects independent nodes (e.g. sensors and actuators) that are situated in the clothes, on the body or under the skin of a person. The network typically expands over the whole human body and the nodes are connected through a wireless communication channel. According to the implementation, these nodes are placed in a star or multihop topology.A WBAN offers many promising new applications in the area of remote health monitoring, home/health care, medicine, multimedia, sports and many other, all of which make advantage of the unconstrained freedom of movement a WBAN offers. In the medical field, for example, a patient can be equipped with a wireless body area network consisting of sensors that constantly measure specific biological functions, such as temperature, blood pressure, heart rate, electrocardiogram (ECG), respiration, etc. The advantage is that the patient doesn’t have to stay in bed, but can move freely across the room and even leave the hospital for a while. This improves the quality of life for the patient and reduces hospital costs. In addition, data collected over a longer period and in the natural environment of the patient, offers more useful information, allowing for a more accurate and sometimes even faster diagnosis.

Research Interests

  • Real-time communications

  • Energy/Temperature aware routing

  • Mobility aware WBAN

  • Geographical routing

Software Defined Networks

Software-defined networking (SDN) is an approach to network management that enables dynamic, programmatically efficient network configuration in order to improve network performance and monitoring, making it more like cloud computing than traditional network management. SDN is meant to address the fact that the static architecture of traditional networks is decentralized and complex while current networks require more flexibility and easy troubleshooting. SDN attempts to centralize network intelligence in one network component by disassociating the forwarding process of network packets (data plane) from the routing process (control plane). The control plane consists of one or more controllers, which are considered the brain of the SDN network where the whole intelligence is incorporated. However, the intelligent centralization has its own drawbacks when it comes to security, scalability and elasticity and this is the main issue of SDN.

Research Interests

  • AI (Artificial Intelligence) -enabled SDN

  • SDN and Service Function Chaining (SFC)

  • VNF Orchestration, Network Slicing

  • SDN for Internet of Things (IoT)

  • Multi-domain Software Defined Networks, Hierarchical SDN Controllers

  • Quality of Service in Software Defined Networks

  • Energy efficiency in Software Defined Networks

  • Load balancing Software Defined Networks

  • Wireless Software Defined Networks, SDN in Wireless Networks

  • SDN in vehicular Ad Hoc Networks

  • SDN for 5G Mobile Networks

Fog/Edge Computing

Fog/Edge computing serves as a computing layer that sits between the edge devices and the cloud in the network topology. They have more compute capacity than the edge but much less so than cloud data centers. They typically have high uptime and always-on Internet connectivity. Applications that make use of the fog can avoid the network performance limitation of cloud computing while being less resource constrained than edge computing. As a result, they offer a useful balance of the current paradigms.

Research Interests

  • Real-time Communications, Resource Allocation

  • Quality of Service, Admission Control

  • Security, Applications

Mobile Ad Hoc Networks

In general, mobile ad hoc networks are formed dynamically by an autonomous system of mobile nodes that are connected via wireless links without using an existing network infrastructure or centralized administration. The nodes are free to move randomly and unpredictably. Such a networks may operate in a standalone fashion or may be connected to the larger Internet. Mobile ad hoc networks are infrastructure-less networks since they do not require any fixed infrastructure such as base station for their operation. In general, routes between nodes in ad hoc network may include multiple hops and , hence, it is appropriate to call such networks "Multiple wireless ad hoc networks".

Research Interests

  • Adaptive/Congnitive Protocols, Tactical Ad Hoc Networks

  • Vehiclular ad hoc networks, Drone ad hoc networks

  • Flying ad hoc networks, Modeling and simulation