Topology control based on the group mobility model for mobile wireless mesh backbone networks

Author(s):  
Ting lei Huang ◽  
Zi Zhang
2021 ◽  
Author(s):  
Yusi Chen ◽  
Ying Lu ◽  
Jin Liu ◽  
Qi Guo ◽  
Nierui Fan ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-16
Author(s):  
Pragasen Mudali ◽  
Matthew Olusegun Adigun

Topology Control has been shown to provide several benefits to wireless ad hoc and mesh networks. However these benefits have largely been demonstrated using simulation-based evaluations. In this paper, we demonstrate the negative impact that the PlainTC Topology Control prototype has on topology stability. This instability is found to be caused by the large number of transceiver power adjustments undertaken by the prototype. A context-based solution is offered to reduce the number of transceiver power adjustments undertaken without sacrificing the cumulative transceiver power savings and spatial reuse advantages gained from employing Topology Control in an infrastructure wireless mesh network. We propose the context-based PlainTC+ prototype and show that incorporating context information in the transceiver power adjustment process significantly reduces topology instability. In addition, improvements to network performance arising from the improved topology stability are also observed. Future plans to add real-time context-awareness to PlainTC+ will have the scheme being prototyped in a software-defined wireless mesh network test-bed being planned.


Author(s):  
Alexander P Pelov ◽  
Thomas Noel

This paper presents the generic layered architecture for mobility models (LEMMA), which can be used to construct a wide variety of mobility models, including the majority of models used in wireless network simulations. The fundamental components of the architecture are described and analyzed, in addition to its benefits. One of the core principles stipulates that each mobility model is divided in five distinct layers that communicate via interfaces. This allows their easy replacement and recombination, which we support by reviewing 19 layers that can form 480 different mobility models. Some of the advanced features provided by the architecture are also discussed, such as layer aggregation, and creation of hybrid and group mobility models. Finally, some of the numerous existing studies of the different layers are presented.


Sign in / Sign up

Export Citation Format

Share Document