Artificial Intelligence Based Congestion Control Mechanism Via Bayesian Networks Under Opportunistic

Ahthasham Sajid (), Muhammad Zaheer, Mehwish Baloch and Javeria Arshad
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Ahthasham Sajid: Department of Computer Science, FICT, BUITEMS, Quetta, Baluchistan, PAKISTAN
Muhammad Zaheer: Department of Environmental Management & Policy, FOE, BUITEMS, Quetta, Baluchistan, PAKISTAN
Mehwish Baloch: Department of Statistics, International Islamic University, Islamabad, PAKISTAN
Javeria Arshad: Department of Computer Science, Quaid-e-Azam University, Islamabad, PAKISTAN

Big Data In Agriculture (BDA), 2019, vol. 1, issue 1, 1-2

Abstract: Nodes in Mobile Opportunistic Network (MON) must cache packets to deal with the key challenging issue of intermittent connection. Management strategy of handling buffer therefore plays a vital impact on the performance of MON, and it attracts more attention recently. Intermittent connection and lengthy postpone are the key challenges in such networks for this reason the internet congestion control mechanisms aren’t suitable for DTNs. An inefficient buffer management strategy would badly affect the performance of such networks. In recent years, to handle congestion buffer manipulate strategies in MON are considered an active vicinity for research studies.

Keywords: DTN; ICN; MON (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnbda:v:1:y:2019:i:1:p:1-2

DOI: 10.26480/bda.01.2019.01.02

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