The application of Ants' society algorithm for Management of resources in continuous bilateral auction

Background: The main purpose of this paper is to improve the efficiency of grid computing by means of Ants' society algorithm. Application of this algorithm in various problem led to an improvement in efficiency and reduction in processing time. This enables us to use this algorithm in grid computing. Economic solutions in the field of management of heterogeneous resources for grid computing showed significant performance. The main idea was economic solutions for product exchange in market. This paper aims to introduce a new method for bilateral auction scenario by means of genetic algorithm (GA). In this method, by making resources intelligent, we move the packages of call for proposal so that it can reduce response time as well as being able to supply resources with lower prices. For simplicity in controlling packages, we used the network structure in implementation. Applied structure includes routers and communication of users and auctioners and auctioners and resources owners. The method was implemented using GridSim simulator. This is an open source software written in Java programming language. Results reveal that the method of bilateral auction using GA reduces sale stages and consequently leads to faster responding to requests and also resources are supplied with a lower cost

Colour Fusion in Face Authentication System Based on Visible and Near Infrared Images

In this paper, face authentication using images taken in visible and near-infrared spectra (NIR) is studied. Visible images are in RGB colour space and near-infrared images are in gray levels colour space. First, the performance of system in each of the primary colour spaces of visible and near-infrared spectrum is evaluated that the verification process is based on the Normalised Correlation measure within the LDA feature space. In order to utilize the information of colour images, the scores associated to an adaptively selected subset of the colour based classifiers are then fused in the decision level. The selection process is based on a sequential search technique called the "plus L and take away R" algorithm. The sum rule and svm rule is used for fusing the related scores. Our extensive experimental studies using the HFB face database demonstrate that using the proposed method, the performance of the system considerably improves as compared to the individual Visible-based or NIR-based face verification systems