Retraction Note to: A reliable multi-hop opportunistic routing scheme with bandwidth guarantee for multimedia wireless mesh networks

Harikishore, S.; Sumalatha, V.

doi:10.1007/s12652-022-03944-4

Cited by 1 publication

(2 citation statements)

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“…The threshold value is set to 0.5 value. The BDM assumption applies to passive unreliable, active unreliable, and reliable sensor nodes specified in ( 6)- (8). Here, ni indicates a sensor node, UN represents the total unreliable sensor node, P indicates the possibility of reliable and unreliable sensor nodes, and RN indicates the reliable sensor node.…”

Section: Bdmmentioning

confidence: 99%

“…Conventional security solutions may suffer from opponent attacks in composite multimedia transmission scenarios because of the rising count of multimedia sensors and the broad range of applications [5]. Security approaches are executed to conquer the conflict between costs and security [6]; as a result, failure to defend legitimate transmissions [7], [8]. Hence, this paper concentrates on unreliable node detection and improves IoT network security.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian decision model based reliable route formation in internet of things

Kumar,

Mishra,

Reddy

et al. 2024

IJEECS

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Security provisioning has become an important issue in wireless multimedia networks because of their crucial task of supporting several services. This paper presents Bayesian decision model based reliable route formation in internet of things (BDMI). The main objective of the BDMI approach is to distinguish unreliable sensor nodes and transmit the data efficiently. Active and passive attack recognition methods identify unreliable node sensor nodes. Remaining energy, node degree, and packet transmission rate parameters to observe their node possibilities for recognizing the passive unreliable nodes. In active recognition, the base station (BS) confirms every sensor node identity, remaining energy, supportive node rate, node location, and link efficiency parameters to detect active unreliable sensor nodes. The Bayesian decision model (BDM) efficiently isolates an unreliable sensor node in the multimedia network. Simulation outcomes illustrate that the BDMI approach can efficiently enhance unreliable node detection and minimize the packet loss ratio in the network.

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Section: Bdmmentioning

confidence: 99%