Cpu Usage Pattern Discovery Using Suffix Tree For Computational Resource Advisory System

Dalam alam pengkomputeraan grid, sumber pengkomputeraan yang boleh diguna sentiasa berubah dari masa ke masa. In grid computing environment, resource availability often changes from time to time

CPU Usage Pattern Discovery Using Suffix Tree For Computational Resource Advisory System [QA76.76.P426 I11 2006 f rb].

Dalam alam pengkomputeraan grid, sumber pengkomputeraan yang boleh diguna sentiasa berubah dari masa ke masa. Penjadual memerlukan aktiviti ramalan supaya ia dapat berfungsi dengan cekap. In grid computing environment, resource availability often changes from time to time. Thus, schedulers require resource prediction help to make effective scheduling decision

Automated Dynamic Service Placement And Replication Framework Using Team Formation Approach To Enhance Service Availability

Managing and administering services in the distributed environment are getting more complicated as the size of the distributed computing environment grows larger and becomes more dynamic. This thesis proposes an automated framework to manage services in a dynamic distributed environment where the resources available for these services would change from time to time. The aim of this research is to design an automated framework that would continuously search for resources with better performance and pool resources together to achieve better availability using a team formation approach

Clustering In Fingerprint Recognition System.

Clustering of fngerprints can help to reduce the complesity of the search process in a database

Storage Performance Evaluation for IoT Gateway Implementation Using Raspberry Pi 2

IoT gateway is a core module exists in many of the IoT architectures that plays a role to connect WSNs to the internet, or specifically to the Cloud. However, conventional internet gateway is not sufficient to be IoT gateway. One of the most critical issue faced by IoT gateway is unstable internet connection especially when using cellular network. This work proposes that IoT gateway should have temporary storage to mask network issue. The objective of this work is to find out the most efficient solution for IoT gateway with temporary storage based on the elements of hardware, scheduler and storage method including database versus flat file on Raspberry Pi and NAND flash. From our experimental results, we found that the most efficient solution for temporary storage in IoT Gateway is using 4-threaded flat file I/O with Deadline scheduler

A coherent authentication framework for mobile computing based on homomorphic signature and implicit authentication

Mobile cloud computing is an extension of cloud computing that allow the users to access the cloud service via their mobile devices. Although mobile cloud computing is convenient and easy to use, the security challenges are increasing significantly.One of the major issues is unauthorized access.Identity Management enables to tackle this issue by protecting the identity of users and controlling access to resources. Although there are several IDM frameworks in place, they are vulnerable to attacks like timing attacks in OAuth, malicious code attack in OpenID and huge amount of information leakage when user’s identity is compromised in Single Sign-On. Our proposed framework implicitly authenticates a user based on user’s typing behavior.The authentication information is encrypted into homomorphic signature before being sent to IDM server and tokens are used to authorize users to access the cloud resources.Advantages of our proposed framework are: user’s identity protection and prevention from unauthorized access

Predicting Shopper Volume Using ARIMA on Public Wi-Fi Signals

Shopping malls are being built at a rapid pace in many South East Asia countries and it has become competitive to attract and maintain shoppers.Being able to know the volume of shoppers and predicting the volume will greatly benefit mall management. In this paper, we present shopper volume monitoring using Wi-Fi signal detectors and use the data obtained from it to derive an Auto-Regressive Integrated Moving Average (ARIMA) model for shopper volume prediction