All Outputs (6)

Joint communication, computation, and control for computational task offloading in vehicle-assisted multi-access edge computing (2022)
Journal Article
Dang, T. N., Manzoor, A., Tun, Y. K., Kazmi, S. M. A., Haw, R., Hong, S. H., …Hong, C. S. (2022). Joint communication, computation, and control for computational task offloading in vehicle-assisted multi-access edge computing. IEEE Access, 10, 122513-122529. https://doi.org/10.1109/ACCESS.2022.3220251

Future generation of Electric Vehicles (EVs) equipped with modern technologies will impose a significant burden on computation and communication to the network due to the vast extension of onboard infotainment services. To overcome this challenge, mu... Read More about Joint communication, computation, and control for computational task offloading in vehicle-assisted multi-access edge computing.

Multiple adversarial domains adaptation approach for mitigating adversarial attacks effects (2022)
Journal Article
Rasheed, B., Khan, A., Ahmad, M., Mazzara, M., & Kazmi, S. M. (2022). Multiple adversarial domains adaptation approach for mitigating adversarial attacks effects. International Transactions on Electrical Energy Systems, 2022, 1-11. https://doi.org/10.1155/2022/2890761

Although neural networks are near achieving performance similar to humans in many tasks, they are susceptible to adversarial attacks in the form of a small, intentionally designed perturbation, which could lead to misclassifications. The best defense... Read More about Multiple adversarial domains adaptation approach for mitigating adversarial attacks effects.

PbCP: A profit-based cache placement scheme for next-generation IoT-based ICN networks (2022)
Journal Article
Serhane, O., Yahyaoui, K., Nour, B., Hussain, R., Kazmi, A., & Moungla, H. (2022). PbCP: A profit-based cache placement scheme for next-generation IoT-based ICN networks. Computer Communications, 194, 311-320. https://doi.org/10.1016/j.comcom.2022.07.044

The large number of connected devices generating a massive amount of data in the emerging technologies such as the Internet of Things (IoT), will surpass the capabilities of the current Internet infrastructure. Therefore, it is essential to design a... Read More about PbCP: A profit-based cache placement scheme for next-generation IoT-based ICN networks.

Computing on wheels: A deep reinforcement learning-based approach (2022)
Journal Article
Kazmi, S. M. A., Ho, T. M., Nguyen, T. T., Fahim, M., Khan, A., Piran, M. J., & Baye, G. (2022). Computing on wheels: A deep reinforcement learning-based approach. IEEE Transactions on Intelligent Transportation Systems, 23(11), 22535-22548. https://doi.org/10.1109/TITS.2022.3165662

Future generation vehicles equipped with modern technologies will impose unprecedented computational demand due to the wide adoption of compute-intensive services with stringent latency requirements. The computational capacity of the next generation... Read More about Computing on wheels: A deep reinforcement learning-based approach.

ApplianceNet: A neural network based framework to recognize daily life activities and behavior in smart home using smart plugs (2022)
Journal Article
Fahim, M., Kazmi, S. M. A., & Khattak, A. M. (2022). ApplianceNet: A neural network based framework to recognize daily life activities and behavior in smart home using smart plugs. Neural Computing and Applications, 34(15), 12749-12763. https://doi.org/10.1007/s00521-022-07144-1

A smart plug can transform the typical electrical appliance into a smart multi-functional device, which can communicate over the Internet. It has the ability to report the energy consumption pattern of the attached appliance which offer the further a... Read More about ApplianceNet: A neural network based framework to recognize daily life activities and behavior in smart home using smart plugs.

Online service provisioning in NFV-enabled networks using deep reinforcement learning (2022)
Journal Article
Nouruzi, A., Zakeri, A., Javan, M. R., Mokari, N., Hussain, R., & Kazmi, S. M. A. (2022). Online service provisioning in NFV-enabled networks using deep reinforcement learning. IEEE Transactions on Network and Service Management, 19(3), 3276-3289. https://doi.org/10.1109/TNSM.2022.3159670

In this paper, we study a Deep Reinforcement Learning (DRL) based framework for an online end-user service provisioning in a Network Function Virtualization (NFV)-enabled network. We formulate an optimization problem aiming to minimize the cost of ne... Read More about Online service provisioning in NFV-enabled networks using deep reinforcement learning.