Modeling and evaluation of multi-hop wireless networks using SRNs

Entezari Maleki, R ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1109/TNSE.2020.3048096
  3. Publisher: IEEE Computer Society , 2021
  4. Abstract:
  5. As multi-hop wireless networks are attracting more attention, the need to evaluate their performance becomes essential. In order to evaluate the performance metrics of multi-hop wireless networks, including sending and receiving rates of a node as well as the collision probability, a model based on Stochastic Reward Nets (SRNs) is proposed. The proposed SRN models a typical node in such networks, considered as a general template to be applied to any wireless node. The SRN model of a single node is designed to take transmission effects of all neighboring nodes into account, while ignoring the ones whose transmission has no effect on the node under-study. Applying the proposed SRN to each node in a multi-hop wireless network, we can model any arbitrary topology and evaluate the mean queue size, collision probability, sending and receiving rates of the nodes. Common issues related to Medium Access Control (MAC) and physical layer of wireless networks, e.g. hidden and exposed node problems, collision, transmission, interference and carrier sense ranges, are considered in the proposed SRN model. The results obtained by the proposed model, in two different scenarios, are validated with the results obtained from the discrete-event simulation conducted in ns-2 simulator to show the applicability and accuracy of the proposed SRN model. © 2013 IEEE
  6. Keywords:
  7. Medium access control ; Network layers ; Stochastic models ; Stochastic systems ; Topology ; Transport properties ; Wireless networks ; Arbitrary topology ; Collision probability ; Hidden and exposed nodes ; Model-based OPC ; Multihop wireless network ; Neighboring nodes ; Performance metrics ; Stochastic reward nets ; Discrete event simulation
  8. Source: IEEE Transactions on Network Science and Engineering ; Volume 8, Issue 1 , 2021 , Pages 662-679 ; 23274697 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9310345