Ascent EM for Efficient Curve-Clustering in Large Online Auction Databases

2004 ◽  
Author(s):  
Wolfgang Jank
Keyword(s):  
Online Auction ◽  
Curve Clustering

Resource Allocation in Cloud using Multi Bidding Model with User Centric Behavior Analysis

2020 ◽  
Vol 13 (5) ◽  
pp. 1008-1019
Author(s):  
N. Vijayaraj ◽  
T. Senthil Murugan
Keyword(s):  
Resource Allocation ◽  
Behavior Analysis ◽  
User Behavior ◽  
Low Cost ◽  
Cloud Services ◽  
Online Auction ◽  
Analysis Model ◽  
Efficient Resource ◽  
User Centric ◽  
Cloud Resources

Background: Number of resource allocation and bidding schemes had been enormously arrived for on demand supply scheme of cloud services. But accessing and presenting the Cloud services depending on the reputation would not produce fair result in cloud computing. Since the cloud users not only looking for the efficient services but in major they look towards the cost. So here there is a way of introducing the bidding option system that includes efficient user centric behavior analysis model to render the cloud services and resource allocation with low cost. Objective: The allocation of resources is not flexible and dynamic for the users in the recent days. This gave me the key idea and generated as a problem statement for my proposed work. Methods: An online auction framework that ensures multi bidding mechanism which utilizes user centric behavioral analysis to produce the efficient and reliable usage of cloud resources according to the user choice. Results: we implement Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis. Thus the algorithm is implemented and system is designed in such a way to provide better allocation of cloud resources which ensures bidding and user behavior. Conclusion: Thus the algorithm Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis is implemented & system is designed in such a way to provide better allocation of cloud resources which ensures bidding, user behavior. The user bid data is trained accordingly such that to produce efficient resource utilization. Further the work can be taken towards data analytics and prediction of user behavior while allocating the cloud resources.

Determinants of Nonpaying Bid Behavior in Online Auction Platforms

2021 ◽  
pp. 1-28
Author(s):  
ChienHsing Wu ◽  
Shu-Chen Kao ◽  
ChengHsun Ho
Keyword(s):  
Online Auction

An online auction mechanism for time-varying multidimensional resource allocation in clouds

2020 ◽  
Vol 111 ◽  
pp. 27-38 ◽  
Author(s):  
Jixian Zhang ◽  
Xutao Yang ◽  
Ning Xie ◽  
Xuejie Zhang ◽  
Athanasios V. Vasilakos ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Online Auction ◽  
Time Varying ◽  
Auction Mechanism

Robust Curve Clustering Based on a Multivariate $t$-Distribution Model

2010 ◽  
Vol 21 (12) ◽  
pp. 1976-1984 ◽  
Author(s):  
Zhi Min Wang ◽  
Qing Song ◽  
Yeng Chai Soh ◽  
Kang Sim
Keyword(s):  
Distribution Model ◽  
Multivariate T Distribution ◽  
Curve Clustering ◽  
T Distribution ◽  
Multivariate T

scholarly journals Efficient Secure Multiparty Computation Protocol for Sequencing Problem over Insecure Channel

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Yi Sun ◽  
Qiaoyan Wen ◽  
Yudong Zhang ◽  
Hua Zhang ◽  
Zhengping Jin
Keyword(s):  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Secure Multiparty Computation ◽  
Online Auction ◽  
Multiparty Computation ◽  
Sequencing Problem ◽  
The Core ◽  
Secure Protocol ◽  
Core Issue

As a powerful tool in solving privacy preserving cooperative problems, secure multiparty computation is more and more popular in electronic bidding, anonymous voting, and online auction. Privacy preserving sequencing problem which is an essential link is regarded as the core issue in these applications. However, due to the difficulties of solving multiparty privacy preserving sequencing problem, related secure protocol is extremely rare. In order to break this deadlock, this paper first presents an efficient secure multiparty computation protocol for the general privacy-preserving sequencing problem based on symmetric homomorphic encryption. The result is of value not only in theory, but also in practice.

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