Title
Group Based Strategy to Accelerate Rendezvous in Cognitive Radio Networks
Abstract
In cognitive radio networks (CRNs), secondary users need to first discover neighbours and form communication links, referred to as the rendezvous process. Rendezvous between any two secondary users can only be achieved on the same channel. However, the nature of the CRN makes this a challenging problem. Specifically in CRN, not only the network is multi- channel, but the channels available at different nodes may be different. While most of the existing works study pair-wise rendezvous and design channel hopping sequence, in this paper, we focus on the performance improvement of the rendezvous process based on the existing channel hopping sequences with multiple users in CRN. We propose a new strategy, called Group Based Strategy (GBS) to achieve the acceleration, which is flexible to incorporate the existing sequence generation algorithms. Our basic idea is to group the encountered users and schedule rendezvous for them. With the purpose to increase rendezvous diversity, other users or groups can join the group if they get the group rendezvous information. Experiments are conducted to evaluate the proposed scheme. Overall, the performance can be improved by more than 50% under symmetric model or asymmetric model using our accelerating strategy.
Year
DOI
Venue
2018
10.1109/ICCCN.2018.8487320
2018 27th International Conference on Computer Communication and Networks (ICCCN)
Keywords
Field
DocType
communication links,Group Based Strategy,sequence generation algorithms,symmetric model,asymmetric model,performance improvement,secondary users,cognitive radio networks,accelerating strategy,group rendezvous information,rendezvous diversity,schedule rendezvous,multiple users,design channel hopping sequence,pair-wise rendezvous,CRN,rendezvous process
Synchronization,Computer science,Communication channel,Computer network,Schedule,Rendezvous,Acceleration,Message passing,Performance improvement,Cognitive radio,Distributed computing
Conference
ISSN
ISBN
Citations 
1095-2055
978-1-5386-5157-5
0
PageRank 
References 
Authors
0.34
10
5
Name
Order
Citations
PageRank
Ji Yi1309.26
Juncheng Jia200.68
Jin Wang332988.76
Jing-Ya Zhou46416.35
Shukui Zhang515019.81