Ulster University Logo

Ulster Institutional Repository

Mobility and Delay in Greedy Geographic Routing

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

cadger, f, Curran, K, Santos, JA and Moffett, Sandra (2012) Mobility and Delay in Greedy Geographic Routing. The International Journal of Satellite Communications Policy and Management, 1 (2/3). pp. 106-119. [Journal article]

[img]PDF - Accepted Version
Indefinitely restricted to Repository staff only.

591Kb

URL: http://www.inderscience.com/dev/search/index.php?action=record&rec_id=49547

DOI: 10.1504/IJSCPM.2012.049547

Abstract

Opportunistic networking and geographic routing both represent fields of research in the area of Mobile Ad-Hoc Networking that seek to create dynamic, hop-by-hop, localised paths from source to destination thus enabling connectivity where no end-to-end path may be possible. Where they differ is in their approach to the problem of providing connectivity in a rapidly changing network; while geographic routing makes decisions based on physical locations, opportunistic networking seeks to take advantage of node mobility and select nodes that will physically carry the message closer to the destination and reduce the overall hop count. In spite of their differences, the similarity of the two approaches presents the opportunity of combining aspects from both paradigms to create hybrid protocols. Greedy geographic routing represents a simplistic form of geographic routing where routing decisions are made based purely on which neighbour is closest to the destination and represents a potentially useful base for developing hybrid opportunistic-geographic protocols due to its simplicity. This paper attempts to analyse the relationship between mobility and delay in greedy routing for use in designing future QoS-aware hybrid opportunistic-geographic protocols.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Business and Management Research Institute
Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:24255
Deposited By:Dr Kevin Curran
Deposited On:04 Dec 2012 13:27
Last Modified:04 Dec 2012 13:27

Repository Staff Only: item control page