Neighbour discovery and distributed spatio-temporal cluster detection in pocket switched networks

UoM administered thesis: Phd

  • Authors:
  • Matthew Orlinski


Pocket Switched Networks (PSNs) offer a means of infrastructureless inter-human communication by utilising Delay and Disruption Tolerant Networking (DTN) technology. However, creating PSNs involves solving challenges which were not encountered in the Deep Space Internet for which DTN technology was originally intended.End-to-end communication over multiple hops in PSNs is a product of short range opportunistic wireless communication between personal mobile wireless devices carried by humans. Opportunistic data delivery in PSNs is far less predictable than in the Deep Space Internet because human movement patterns are harder to predict than the orbital motion of satellites. Furthermore, PSNs require some scheme for efficient neighbour discovery in order to save energy and because mobile devices in PSNs may be unaware of when their next encounter will take place.This thesis offers novel solutions for neighbour discovery and opportunistic data delivery in PSNs that make practical use of dynamic inter-human encounter patterns.The first contribution is a novel neighbour discovery algorithm for PSNs called PISTONS which relies on a new inter-probe time calculation (IPC) and the bursty encounter patterns of humans to set the time between neighbour discovery scans. The IPC equations and PISTONS also give participants the ability to easily specify their required level of connectivity and energy saving with a single variable.This thesis also contains novel distributed spatio-temporal clustering and opportunistic data delivery algorithms for PSNs which can be used to deliver data over multiple hops. The spatio-temporal clustering algorimths are also used to analyse the social networks and transient groups which are formed when humans interact.


Original languageEnglish
Awarding Institution
  • Nicholas Filer (Supervisor)
Award date31 Dec 2013