Neighbor Detection Based on Multiple Virtual Mobile Nodes
Details
Serval ID
serval:BIB_C5DAD1DA05EB
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Neighbor Detection Based on Multiple Virtual Mobile Nodes
Title of the conference
2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)
Publisher
IEEE
Address
Crete, Greece
ISBN
978-1-4673-8776-7
Publication state
Published
Issued date
02/2016
Series
Euromicro Conference on Parallel Distributed and Network-Based Processing
Pages
322-327
Language
english
Abstract
We introduce an algorithm that implements a time limited neighbor detector service in mobile ad hoc networks. The time-limited neighbor detector enables a mobile device to detect nearby devices in the past, present and up to some bounded time interval in the future. In particular, it can be used by a new trend of mobile applications known as proximity-based mobile applications. To implement the neighbor detector, our algorithm uses n = 2(k) virtual mobile nodes where k is a non-negative integer. A virtual mobile node is an abstraction that is akin to a mobile node that travels in the network in a predefined trajectory. In practice, it can be implemented by a set of mobile nodes based on a replicated state machine approach. Our algorithm implements the neighbor detector for nodes located in a circular region. We assume that each node can accurately predict its own locations up to some bounded time interval Delta(predict) in the future. The key idea of the algorithm is that the virtual mobile nodes regularly collect location predictions of nodes from different subregions, meet to share what they have collected with each other and then distribute the collected location predictions to nodes. Thus, each node can use the distributed location predictions for neighbor detection. We show that our algorithm is correct under certain conditions. Compared to a solution that works with a single virtual mobile node, our algorithm has a main advantage: as n grows, it remains correct with smaller values of Delta(predict). This feature makes the real world implementation of the neighbor detector more feasible. In fact, although there exist different approaches to predict the future locations of a node, usually predictions tend to become less accurate as Delta(predict) increases.
Keywords
Neighbor Detection, Virtual Mobile Node, MANET
Web of science
Create date
13/07/2017 15:37
Last modification date
20/08/2019 15:41