arXiv subjects

Amin Ebrahimzadeh

Publications and source records attributed to Amin Ebrahimzadeh.

3 recordsLinked to original sources

arXiv2026

Real-Time Adaptive Anomaly Detection in Industrial IoT Environments

To ensure reliability and service availability, next-generation networks are expected to rely on automated anomaly detection systems powered by advanced machine learning methods with the capability of handling multi-dimensional data. Such multi-dimensional, heterogeneous data occurs mostly in today's industrial Internet of Things (IIoT), where real-time detection of anomalies is critical to prevent impending failures and resolve them in a timely manner. However, existing anomaly detection methods often fall short of effectively coping with the complexity and dynamism of multi-dimensional data streams in IIoT. In this paper, we propose an adaptive method for detecting anomalies in IIoT streaming data utilizing a multi-source prediction model and concept drift adaptation. The proposed anomaly detection algorithm merges a prediction model into a novel drift adaptation method resulting in accurate and efficient anomaly detection that exhibits improved scalability. Our trace-driven evaluations indicate that the proposed method outperforms the state-of-the-art anomaly detection methods by achieving up to an 89.71% accuracy (in terms of Area under the Curve (AUC)) while meeting the given efficiency and scalability requirements.

cs.LG↗

arXiv2023

Deep Reinforcement Learning-based Content Migration for Edge Content Delivery Networks with Vehicular Nodes

With the explosive demands for data, content delivery networks are facing ever-increasing challenges to meet end-users quality-of-experience requirements, especially in terms of delay. Content can be migrated from surrogate servers to local caches closer to end-users to address delay challenges. Unfortunately, these local caches have limited capacities, and when they are fully occupied, it may sometimes be necessary to remove their lower-priority content to accommodate higher-priority content. At other times, it may be necessary to return previously removed content to local caches. Downloading this content from surrogate servers is costly from the perspective of network usage, and potentially detrimental to the end-user QoE in terms of delay. In this paper, we consider an edge content delivery network with vehicular nodes and propose a content migration strategy in which local caches offload their contents to neighboring edge caches whenever feasible, instead of removing their contents when they are fully occupied. This process ensures that more contents remain in the vicinity of end-users. However, selecting which contents to migrate and to which neighboring cache to migrate is a complicated problem. This paper proposes a deep reinforcement learning approach to minimize the cost. Our simulation scenarios realized up to a 70% reduction of content access delay cost compared to conventional strategies with and without content migration.

cs.NI↗

arXiv2019

Toward the Internet of No Things: The Role of O2O Communications and Extended Reality

Future fully interconnected virtual reality (VR) systems and the Tactile Internet diminish the boundary between virtual (online) and real (offline) worlds, while extending the digital and physical capabilities of humans via edge computing and teleoperated robots, respectively. In this paper, we focus on the Internet of No Things as an extension of immersive VR from virtual to real environments, where human-intended Internet services - either digital or physical - appear when needed and disappear when not needed. We first introduce the concept of integrated online-to-offline (O2O) communications, which treats online and offline channels as complementary to bridge the virtual and physical worlds and provide O2O multichannel experiences. We then elaborate on the emerging extended reality (XR), which brings the different forms of virtual/augmented/mixed reality together to realize the entire reality-virtuality continuum and, more importantly, supports human-machine interaction as envisioned by the Tactile Internet, while posing challenges to conventional handhelds, e.g., smartphones. Building on the so-called invisible-to-visible (I2V) technology concept, we present our extrasensory perception network (ESPN) and investigate how O2O communications and XR can be combined for the nonlocal extension of human "sixth-sense" experiences in space and time. We conclude by putting our ideas in perspective of the 6G vision.

cs.NI↗