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The problem of scheduling under resource constraints is widely applicable. One prominent example is power management, in which we have a limited continuous supply of power but must schedule a number of power-consuming tasks. Such problems…
Representing the movements of objects (trips) over a network in a compact way while retaining the capability of exploiting such data effectively is an important challenge of real applications. We present a new Compact Trip Representation…
Real-time end-to-end task scheduling in networked control systems (NCSs) requires the joint consideration of both network and computing resources to guarantee the desired quality of service (QoS). This paper introduces a new model for…
Our society has never been more dependent on computer networks. Effective utilization of networks requires a detailed understanding of the normal background behaviors of network traffic. Large-scale measurements of networks are…
In this paper, we design an exclusive Metaverse network traffic classifier, named Discern-XR, to help Internet service providers (ISP) and router manufacturers enhance the quality of Metaverse services. Leveraging segmented learning, the…
Applying of network slicing in vehicular networks becomes a promising paradigm to support emerging Vehicle-to-Vehicle (V2V) applications with diverse quality of service (QoS) requirements. However, achieving effective network slicing in…
Traffic routing is vital for the proper functioning of the Internet. As users and network traffic increase, researchers try to develop adaptive and intelligent routing algorithms that can fulfill various QoS requirements. Reinforcement…
Segment routing (SR) combines the advantages of source routing supported by centralized software-defined networking (SDN) paradigm and hop-by-hop routing applied in distributed IP network infrastructure. However, because of the computation…
Edge and mobile platforms for augmented and virtual reality, collectively referred to as extended reality (XR) must deliver deterministic ultra-low-latency performance under stringent power and area constraints. However, the diversity of XR…
We consider the problem of enhancing the delivery of real-time traffic in wireless networks using bandwidth sharing between operators. A key characteristic of real-time traffic is that a packet has to be delivered within a delay deadline…
The complexity of emerging sixth-generation (6G) wireless networks has sparked an upsurge in adopting artificial intelligence (AI) to underpin the challenges in network management and resource allocation under strict service level…
In this thesis work, a QoS model for real-time interactive traffic on a real network with constrained bandwidth and real-time traffic has been proposed. The model supports tight guarantees of QoS to real-time interactive traffic without…
Deep learning-based network traffic classification (NTC) techniques, including conventional and class-of-service (CoS) classifiers, are a popular tool that aids in the quality of service (QoS) and radio resource management for the Internet…
Time-Sensitive Networking (TSN) is an enhancement of Ethernet which provides various mechanisms for real-time communication. Time-triggered (TT) traffic represents periodic data streams with strict real-time requirements. Amongst others,…
Recent developments and widespread in wireless sensor network have led to many routing protocols, many of these protocols consider the efficiency of energy as the ultimate factor to maximize the WSN lifetime. The quality of Service (QoS)…
Fractal behavior and long-range dependence have been observed in tele-traffic measurement and characterization. In this paper we show results of application of the fractal analysis to internet traffic via various methods. Our result…
The paper focuses on improving the spectrum sharing using NSU, FLS and Traffic Pattern Prediction and also made comparison that traffic pattern prediction provides a better way of improving the spectrum utilization and avoids the spectrum…
Extended Reality (XR) provides a more intuitive interaction method for teleoperating robots compared to traditional 2D controls. Recent studies have laid the groundwork for usable teleoperation with XR, but it fails in tasks requiring rapid…
We present a transfer learning analysis on a sporting environment of the expanded 3D (X3D) neural networks. Inspired by action quality assessment methods in the literature, our method uses an action recognition network to estimate athletes'…
Traffic classification has various applications in today's Internet, from resource allocation, billing and QoS purposes in ISPs to firewall and malware detection in clients. Classical machine learning algorithms and deep learning models…