Using hybrid protocols for fast and reliable peer-to-peer communication

Peer-to-peer communication:

In this project, you will lay the theoretical foundations that will form the basis of the next generation of peer-to-peer communication protocols.

These days, our society contains a multitude of electronic devices that communicate with each other. Some of this communication is hierarchical, where one server communicates with many clients. In other cases, the communication is among equals, in a peer-to-peer network.

A famous example of peer-to-peer communication would, of course, be file sharing using the BitTorrent protocol. But peer-to-peer communication is useful in many other settings as well. Think, for example, of a group of autonomous vehicles that transmit traffic conditions to each other. Or consider a distributed database that is stored on multiple servers, where a change to one of the copies needs to be transmitted to the others.

Hybrid protocols:

Because there is a lot of peer-to-peer communication going on, we would like that communication to be fast and reliable. In order to simultaneously achieve speed and reliability, you will create hybrid protocols. These protocols combine symbolic methods (i.e., traditional math/logic/programming where each participant in the protocol receives precise instructions) and implicit methods (i.e., machine learning).

The symbolic approach provides a lot of control over what the participants can do. When using symbolic protocols it is therefore (relatively) easy to guarantee that all participants will receive all information they need, and to prove an upper bound on how long that will take. As a result, symbolic protocols tend to be very reliable.

The implicit approach uses machine learning to optimize the communication process, in ways that a human programmer would not be able to. As a result, implicit protocols tend to be very efficient. A hybrid protocol will combine the reliability of symbolic protocols with the speed of symbolic ones.

In this project, you will create hybrid protocols and rigorously test their reliability and speed.

Applicant qualities:

Applicants should be familiar with at least one, and preferably more, of the following topics:

 -Distributed systems

 -Logic

 -Machine learning

Programming experience is not strictly necessary, but would be beneficial.

Start Date: 1st October 2023

This PhD project is funded by The Faculty of Science & Engineering at The University of Liverpool and will start on 1st October 2023.

Successful candidates who meet the University of Liverpool eligibility criteria will be awarded a Faculty of Science & Engineering studentship for 3.5 years, covering UK tuition fees and an annual tax-free stipend (e.g. £17,688 p.a. for 2022-23).

Faculty of Science & Engineering students benefit from bespoke graduate training and £5,000 for training, travel and conferences.

The Faculty of Science & Engineering is committed to equality, diversity, widening participation and inclusion. Academic qualifications are considered alongside non-academic experience. Our recruitment process considers potential with the same weighting as past experience. Students must complete a personal statement profoma and ensure this is included in their online application.

How to Apply:

All applicants must complete the personal statement proforma. This is instead of a normal personal/supporting statement/cover letter. The proforma is designed to standardise this part of the application to minimise the difference between those who are given support and those who are not. The proforma can be found here: https://tinyurl.com/ym2ycne4. More information on the application process can be found here: https://tinyurl.com/mwn5952t. When applying online, students should ensure they include the department name in the ‘Programme Applied For’ section of the online form, as well as the Faculty of Science & Engineering as the ‘studentship type’ in the finance section.