Dynamic load balancing for client server assignment in distributed system using genetical gorithm

Gopi, Arepalli Peda; Narayana, V. Lakshman; Kumar, Neeraj

doi:10.3166/isi.23.6.87-98

Cited by 13 publications

(9 citation statements)

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“…At the resonant frequency, f o =6.8 GHz, the simulated results of proposed antenna are S11=-29.9 dB, VSWR=1.06, gain=3.14 dBi, BW=3.13 to greater than 12 GHz. We obtained the wide bandwidth [15][16]when compared to former case due to stair case cut at left corner of the patch and we also achieved better return loss VSWR, gain.Omni-directional radiation patterns are obtained from this antenna. The proposed structure also exhibits UWB characterization.…”

Section: Simulation Resultsmentioning

confidence: 99%

Design of Ultra Wideband Patch Antenna

Katuru*,

Alapati

2020

IJITEE

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 Abstract: This paper presents an ultra wideband(UWB) antenna which is in rectangular shape is designed and analyzed by Microwave Studio Computer Simulation Technology(MS CST).The antenna uses FR-4 substrate. The rectangular patch which is excited by micro strip line is printed on the top of the substrate and a partial ground plane is printed on the other side. The basic structure of antenna produces ultra-wideband characteristics. But these characteristics can further be improved by cutting the lower left corner of the patch as stair case and observed the simulated results like return loss(S11), voltage standing wave ratio(VSWR), gain and bandwidth(BW).

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Section: Simulation Resultsmentioning

confidence: 99%

Design of Ultra Wideband Patch Antenna

Katuru*,

Alapati

2020

IJITEE

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“…c) The other solutions are based on trust-based mechanisms [22][23] [24], in which every vehicle is associated with a trust value and may vary depending on vehicle behavior [19] and there also exist a trusted third party (TTP) or mutual group trust management, which evaluates and isolates the attacker depending on its trust value [27]. These solutions may not work all the time as the attacker may act normal to improve its trust value and the TTP may compromise.…”

Section: Thre Are Different Types Of Communication Players Likementioning

confidence: 99%

Secure V2V Communication in IOV using IBE and PKI based Hybrid Approach

Kanumalli¹,

Ch²,

Murty³

2020

IJACSA

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We live in the world of "Internet of Everything", which lead to advent of different applications and Internet of vehicles (IOV) of one among them, which is a major step forward for the future of transportation system. Vehicle to vehicle (V2V) communication plays a major role in which a vehicle may send sensitive, non-sensitive messages and these messages are encrypted with public keys, which makes distribution of public keys is a major problem due to the vehicle need to be anonymous having pseudonyms which changes more frequently and makes it more complicated. Here we proposed a hybrid approach, which uses existing Public key certificate for authorization of the vehicle and Identity Based Encryption to generate public keys from the pseudonyms and use it in secure V2V communication without compromising anonymity of the vehicle.

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“…The Bayesian system is additionally seen as a procedure in medical expectation Particular it has been used for Brest malignancy guess and determination [20]. In future we mean to plan and actualize such framework for online applications [21].…”

Section: Literature Workmentioning

confidence: 99%

Machine Learning Methodology for Medical Data Analysis for Prediction of Risk

Sravanthi¹,

Harika²,

Archana³

et al. 2020

jcr

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Mining data is a nontrivial procedure of finding information from a large volume of data. Such information can be helpful in settling on significant choices. Medical data show special features including noise coming about because of human just as methodical blunders, missing qualities and even meager conditions. The nature of data has huge ramifications for the nature of the mining results. Medical data classification is important to perform preprocessing steps so as to expel or at least lighten a portion of the issues related with medical data. Clustering is a descriptive-based data mining task. The clustering algorithm is also called as unsupervised learning algorithm that learns the unlabeled dataset and groups or clusters the instances based on their similarity and builds the clustering model. Clustering is same as classification in which data is grouped, but in this, groups are not predefined. In clustering, clusters are not predefined. Classification of different types of clustering is as follows: Hierarchical clustering, Partition clustering, Categorical clustering, Density based clustering and Grid based clustering. The main intension of the research is to classify the medical data with high accuracy value. In order to achieve promising results, a novel data classification methods have been designed that utilize a Improved Cluster Optimal Classifier (ICOC). The proposed method is compared with traditional methods and the results show that the proposed method performance is better and accurate.

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Dynamic load balancing for client server assignment in distributed system using genetical gorithm

Cited by 13 publications

References 0 publications

Design of Ultra Wideband Patch Antenna

Design of Ultra Wideband Patch Antenna

Secure V2V Communication in IOV using IBE and PKI based Hybrid Approach

Machine Learning Methodology for Medical Data Analysis for Prediction of Risk

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