Context-Aware Wireless Power Transfer Scheduling for Vehicular Edge Computing

Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge Computing (MEC) to road scenarios. VEC and wireless power transfer (WPT) are regarded as promising technologies that have attracted significant attention in many areas. MEC/VEC can bring computation and data storage closer to where data is generated, enabling better data control, reduced costs, faster insights and actions, and continuous operation. Wireless Power Transfer (WPT) facilitates the development of ultra-low power communication technologies such as Internet of Everything (IoE) by providing a stable and reliable power source, enabling numerous novel applications and services. Therefore, WPT is expected to play a crucial role in powering and connecting a diverse range of devices and services in the 6G-enabled world. WPT technologies are vital in advancing the capabilities of 6G networks. By eliminating the need for cords and cables, WPT allows for more seamless and convenient charging of devices. This enhances the mobility of devices, which is crucial for the growth of IoE applications. WPT technologies offer improved energy efficiency, reducing waste generated by traditional charging methods. Implementing WPT in 6G networks increase the popularity of wearable technology, such as smartwatches, fitness trackers, and IoT devices, which require constant power. The integration of WPT with 6G networks provides a more convenient and efficient solution for charging these devices, ultimately leading to the growth of technology and the advancement of the IoE. WPT modes of operation include power-sharing and time switching concerning the WPT receiver structure.

Recently, some studies on wireless charging scheduling have been proposed, aiming at enhancing the performance of power-limited devices by optimizing charging scheduling schemes and load scheduling. However, these studies did not context-aware scheduling within a wide range of parameters.

Unlike most existing works, this project will strive to propose smart WPT scheduling that depends on context-aware multi-criteria decision-making in selecting a sensor for charging. Novel AI-driven scheduling algorithms will be developed for VEC. 

Academic qualifications

A first-class honours degree, or a distinction at master level, or equivalent achievements in Computer Science-related area with a good fundamental knowledge of computer science and communications.

English language requirement

If your first language is not English, comply with the University requirements for research degree programmes in terms of English language.

Application process

Prospective applicants are encouraged to contact the supervisor, Professor Ahmed Al-Dubai (a.al-dubai@napier.ac.uk) to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded). The outline may provide details about

• Background and motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Recent and complete curriculum vitae. The curriculum must include a declaration regarding the English language qualifications of the candidate.
• Supporting documents will have to be submitted by successful candidates.
• Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), on the form can be downloaded here.

Applications can be submitted here.

Download a copy of the project details here.