arXiv subjects

Seyhan Ucar

Publications and source records attributed to Seyhan Ucar.

6 recordsLinked to original sources

arXiv2026

The Search for Relevance: A Context-Aware Paradigm Shift in Semantic and Task-Oriented V2X Communications

The design of communication systems has traditionally prioritized the reliable and timely delivery of data. However, the scalability challenges faced by the evolution towards a data-driven hyper-connected society and economy demand new communication paradigms that carefully curate the content being transmitted. This paper proposes a joint semantic and task-oriented communication paradigm where connected devices transmit only the information necessary to convey the desired meaning that is relevant to the intended receivers, based on their context. We qualitatively and quantitatively analyze the potential benefits of the proposed semantic and task-oriented communication paradigm in the Vehicle-to-Everything (V2X) domain. The V2X domain offers a unique environment for the development and deployment of semantic and task-oriented V2X communications, as it is rich in contextual information and Connected and Autonomous Vehicles (CAVs) are native semantic devices. The qualitative analysis focuses on a cooperative perception use case and shows how semantic and task-oriented V2X communications can reduce the amount of information transmitted by each vehicle without compromising the situational awareness of its intended receivers. The quantitative analysis numerically demonstrates that semantic and task-oriented V2X communications can achieve a two-fold improvement in communication efficiency which can significantly benefit the scalability of future V2X networks.

cs.NI↗

arXiv2026

Semantic and Task-Oriented V2X Communications: Pushing the Limits of V2X Networks Scalability

Scalable Vehicle-to-Everything (V2X) networks are key to support the large-scale deployment of connected and automated mobility. However, the scalability of V2X networks is currently challenged by the limitations of existing V2X communication paradigms, which prioritize the reliable and timely delivery of the transmitted information over a careful message content selection - an approach that can potentially lead to the transmission of unnecessary information and an inefficient usage of communication resources. Semantic and task-oriented V2X communications have recently been proposed to address these scalability challenges by focusing on the content of the transmitted messages, particularly on its relevance to the intended receivers. In this paper, we numerically demonstrate that semantic and task-oriented V2X communications can substantially improve the scalability of V2X networks, increasing by up to a 4.1x factor the number of supported vehicles under high-density conditions. In addition, we show that semantic and task-oriented V2X communications can also decrease the inter-reception time between consecutive messages by up to 67% and lead to a twofold increase in the probability of successfully delivering all required relevant information to the intended receivers.

cs.NI↗

arXiv2026

HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learning

This study presents a hierarchical, network-level traffic flow control framework for mixed traffic consisting of Human-driven Vehicles (HVs), Connected and Automated Vehicles (CAVs). The framework jointly optimizes vehicle-level eco-driving behaviors and intersection-level traffic signal control to enhance overall network efficiency and decrease energy consumption. A decentralized Multi-Agent Reinforcement Learning (MARL) approach by Value Decomposition Network (VDN) manages cycle-based traffic signal control (TSC) at intersections, while an innovative Signal Phase and Timing (SPaT) prediction method integrates a Machine Learning-based Trajectory Planning Algorithm (MLTPA) to guide CAVs in executing Eco-Approach and Departure (EAD) maneuvers. The framework is evaluated across varying CAV proportions and powertrain types to assess its effects on mobility and energy performance. Experimental results conducted in a 4*4 real-world network demonstrate that the MARL-based TSC method outperforms the baseline model (i.e., Webster method) in speed, fuel consumption, and idling time. In addition, with MLTPA, HONEST-CAV benefits the traffic system further in energy consumption and idling time. With a 60% CAV proportion, vehicle average speed, fuel consumption, and idling time can be improved/saved by 7.67%, 10.23%, and 45.83% compared with the baseline. Furthermore, discussions on CAV proportions and powertrain types are conducted to quantify the performance of the proposed method with the impact of automation and electrification.

cs.LG↗

arXiv2021

DHT-based Communications Survey: Architectures and Use Cases

Several distributed system paradigms utilize Distributed Hash Tables (DHTs) to realize structured peer-to-peer (P2P) overlays. DHT structures arise as the most commonly used organizations for peers that can efficiently perform crucial services such as data storage, replication, query resolution, and load balancing. With the advances in various distributed system technologies, novel and efficient solutions based on DHTs emerge and play critical roles in system design. DHT-based methods and communications have been proposed to address challenges such as scalability, availability, reliability and performance, by considering unique characteristics of these technologies. In this article, we propose a classification of the state-of-the-art DHT-based methods focusing on their system architecture, communication, routing and technological aspects across various system domains. To the best of our knowledge, there is no comprehensive survey on DHT-based applications from system architecture and communication perspectives that spans various domains of recent distributed system technologies. We investigate the recently emerged DHT-based solutions in the seven key domains of edge and fog computing, cloud computing, blockchain, the Internet of Things (IoT), Online Social Networks (OSNs), Mobile Ad Hoc Networks (MANETs), and Vehicular Ad Hoc Networks (VANETs). In contrast to the existing surveys, our study goes beyond the commonly known DHT methods such as storage, routing, and lookup, and identifies diverse DHT-based solutions including but not limited to aggregation, task scheduling, resource management and discovery, clustering and group management, federation, data dependency management, and data transmission. Furthermore, we identify open problems and discuss future research guidelines for each domain.

cs.DC↗

arXiv2020

Hybrid Vehicular and Cloud Distributed Computing: A Case for Cooperative Perception

In this work, we propose the use of hybrid offloading of computing tasks simultaneously to edge servers (vertical offloading) via LTE communication and to nearby cars (horizontal offloading) via V2V communication, in order to increase the rate at which tasks are processed compared to local processing. Our main contribution is an optimized resource assignment and scheduling framework for hybrid offloading of computing tasks. The framework optimally utilizes the computational resources in the edge and in the micro cloud, while taking into account communication constraints and task requirements. While cooperative perception is the primary use case of our framework, the framework is applicable to other cooperative vehicular applications with high computing demand and significant transmission overhead. The framework is tested in a simulated environment built on top of car traces and communication rates exported from the Veins vehicular networking simulator. We observe a significant increase in the processing rate of cooperative perception sensor frames when hybrid offloading with optimized resource assignment is adopted. Furthermore, the processing rate increases with V2V connectivity as more computing tasks can be offloaded horizontally.

cs.DC↗

arXiv2016

Multi-Hop Cluster based IEEE 802.11p and LTE Hybrid Architecture for VANET Safety Message Dissemination

This paper proposes a hybrid architecture, namely VMaSC-LTE, combining IEEE 802.11p based multi-hop clustering and the fourth generation cellular system, Long Term Evolution (LTE), with the goal of achieving high data packet delivery ratio and low delay while keeping the usage of the cellular architecture at the minimum level. In VMaSC-LTE, vehicles are clustered based on a novel approach named VMaSC: Vehicular Multi-hop algorithm for Stable Clustering. From the clustered topology, elected cluster heads operate as dual-interface nodes with the functionality of IEEE 802.11p and LTE interface to link VANET to LTE network. Using various key metrics of interest including data packet delivery ratio, delay, control overhead and clustering stability, we demonstrate superior performance of the proposed architecture compared to both previously proposed hybrid architectures and alternative routing mechanisms including flooding and cluster based routing via extensive simulations in ns-3 with the vehicle mobility input from the Simulation of Urban Mobility (SUMO). The proposed architecture also allows achieving higher required reliability of the application quantified by the data packet delivery ratio at the cost of higher LTE usage determined by the number of cluster heads in the network.

cs.NI↗