A Reference-Based Multiobjective Bacteria Foraging Optimization Technique for QoS Multicast Routing

Sahoo, Sarmila; Nayak, Sasmita; Kabat, Manas Ranjan

doi:10.1007/s13369-018-3090-9

Cited by 8 publications

(2 citation statements)

References 17 publications

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“…Hence, this work implements a chaotic IM search technique to improve the performance of the traditional cuckoo search (TCS) method. The efficacy of the proposed chaotic cuckoo search (CCS) is further confirmed with other techniques, such as particle swarm optimization (PSO) [ 47 ], bacterial foraging optimization (BFO) [ 48 ], bat algorithm (BA) [ 41 ], and TCS [ 41 ].…”

Section: Computer-based Diagnosis Methodsmentioning

confidence: 93%

Extraction and Evaluation of Corpus Callosum from 2D Brain MRI Slice: A Study with Cuckoo Search Algorithm

Manic

Biju

Patel

et al. 2021

Computational and Mathematical Methods in Medicine

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The work proposes a computer-based diagnosis method (CBDM) to delineate and assess the corpus callosum (CC) segment from the 2-dimensional (2D) brain magnetic resonance images (MRI). The proposed CBDM consists of two parts: (1) preprocessing and (2) postprocessing sections. The preprocessing tools have a multithreshold technique with the chaotic cuckoo search (CCS) algorithm and a preferred threshold procedure. The postprocessing employs a delineation process for extracting the CC section. The proposed CBDM finally extracts the vital CC parameters, such as total brain area (TBA) and CC area (CCA) to classify the considered 2D MRI slices into the control and autism spectrum disorder (ASD) groups. This attempt considers the benchmark brain MRI database which includes ABIDE and MIDAS for the experimental investigation. The results obtained with ABIDE dataset are further confirmed against the fuzzy C -means driven level set (FCM + LS) and multiphase level set (MLS) technique and the proposed CBDM with Shannon entropy along with active contour (SE + AC) presented improved result in comparison to the existing methodologies. Further, the performance of CBDM is confirmed on MIDAS and clinical dataset. The experimental outcomes approve that the proposed CBDM extracts the CC section from the 2D MR brain images that have higher accuracy compared to alternative techniques.

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Section: Computer-based Diagnosis Methodsmentioning

confidence: 93%

Extraction and Evaluation of Corpus Callosum from 2D Brain MRI Slice: A Study with Cuckoo Search Algorithm

Manic

Biju

Patel

et al. 2021

Computational and Mathematical Methods in Medicine

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“…Multi-cast routing was proposed in [7] which mimicked multi-objective bacteria for their multi-casts. The scheme called RBMOBFO was based on referential user preferences.…”

Section: Related Workmentioning

confidence: 99%

An Energy Efficient Qos Routing Protocol Based On Red Deer Algorithm In MANET

Arivarasan¹

2021

TURCOMAT

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MANETs (Mobile ad hoc networks) are overloaded with their heavy usage choking traffic. Recent studies have been attempting to find feasibility of routes in these networks. Most proposed schemes have failed to consider the network traffic or MANET requirements. MANET routing done by RPs (Routing Protocols) would perform better when they adhere to QoS (Quality of Service) or application requirements. As a result, RPs must satisfy numerous QoS metrics at a time where soft computing algorithm based RPs are a solution to QoS routing problems. Evolutionary algorithm based routing do not achieve enough energy efficiency which is a major drawback. To overcome this drawback, this work, proposes Red Deer algorithm (RDA) based energy efficient QoS routing for MANETs called (RDA-EQRP). The proposed RDA based routing algorithm discovers the shortest path from a source to a destination which can consumes less energy while supporting the metrics such of reliability, bandwidth, SRC (Static Resource Capacity), Quality and delay. Simulation results show that proposed rotting scheme RDA-EQRP consumes lesser energy in MANET routing.

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