collaborators

5 papers

cs.NI2025

On-Dyn-CDA: A Real-Time Cost-Driven Task Offloading Algorithm for Vehicular Networks with Reduced Latency and Task Loss

Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek +2

Real-time task processing is a critical challenge in vehicular networks, where achieving low latency and minimizing dropped task ratio depend on efficient task execution. Our prima…

cs.NI2025

Meeting Deadlines in Motion: Deep RL for Real-Time Task Offloading in Vehicular Edge Networks

Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek +2

Vehicular Mobile Edge Computing (VEC) drives the future by enabling low-latency, high-efficiency data processing at the very edge of vehicular networks. This drives innovation in k…

cs.NI2025

A Reliable and Efficient 5G Vehicular MEC: Guaranteed Task Completion with Minimal Latency

Mahsa Paknejad, Parisa Fard Moshiri, Murat Simsek +2

This paper explores the advancement of Vehicular Edge Computing (VEC) as a tailored application of Mobile Edge Computing (MEC) for the automotive industry, addressing the rising de…

cs.NI2025

Partitioned Task Offloading for Low-Latency and Reliable Task Completion in 5G MEC

Parisa Fard Moshiri, Murat Simsek, Burak Kantarci

The demand for MEC has increased with the rise of data-intensive applications and 5G networks, while conventional cloud models struggle to satisfy low-latency requirements. While t…

cs.NI2025

Joint Optimization of Completion Ratio and Latency of Offloaded Tasks with Multiple Priority Levels in 5G Edge

Parisa Fard Moshiri, Murat Simsek, Burak Kantarci

Multi-Access Edge Computing (MEC) is widely recognized as an essential enabler for applications that necessitate minimal latency. However, the dropped task ratio metric has not bee…