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Home > Archives > Volume 20, No 11 (2022) > Article

DOI: 10.14704/NQ.2022.20.11.NQ66033

Pragmatic analysis of collision aware routing models for wireless networks from an empirical perspective

Ritesh Shrivastav, Dr.Swapanili Karmore


Collisions in wireless networks are a major reason for packet drops, data delays, reduced energy efficiency, and low throughput performance. To overcome this issue, various collision-aware models are proposed by researchers, which include robust clusterbased routing protocol (RCBRP), energyefficient optimal multipath routing protocol (EOMR), constrained application protocol with congestion control/advanced (CoCoA), etc. Each of these models also have machine learning optimized alternatives which assist in lowpower, and high throughput communication deployments. These models widely vary in terms of performance metrics like end-to-end delay, throughput, energy consumption, packet delivery ratio (PDR), etc. Moreover, they also have their own context-specific nuances, advantages, limitations, and future research scopes. Due to such a wide variation in performance, it becomes ambiguous for researchers to identify optimum collision aware routing models for their application-specific deployments. To reduce this ambiguity, a detailed discussion about these models along with their characteristics, applicability, and scalability performance is reviewed in this text. Based on this discussion, researchers & network designers will be able to identify optimum models for their network deployments, which will reduce cost of design & deployment for small to large scale wireless networks. This discussion is accompanied with a statistical evaluation of the reviewed models, which would further assist in identification of application-specific congestion control & mitigation strategies. This text also compares the reviewed models in terms of routing complexity, end-to-end delay, throughput, packet delivery ratio (PDR) performance, and other statistical metrics. Fusion methods for efficiently combining these models for reduced congestion are also discussed in this text. Based on this discussion & comparison of models, readers & network designers will be able to identify most optimum models for deploying high throughput, and low congestion wireless networks. After observing these metrics, this text proposes formulation of a novel model ranking score (MRS), which combines all the reviewed statistical performance metrics. Based on this this score, researchers will be able to identify congestion control models that are capable of finding an equilibrium between different performance metrics under various deployment scenarios.us use of keywords may increase the ease with which interested parties can locate our article.


Wireless, Congestion, Control, Network

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