Internet acts as the best medium for proliferation and diffusion of fake news. Information quality on the internet is a very important issue, but web-scale data hinders the expert’s ability to correct much of the inaccurate content or fake content present over these platforms. Thus, a new system of safeguard is needed. Traditional Fake news detection systems are based on content-based features (i.e. analyzing the content of the news) of the news whereas most recent models focus on the social features of news (i.e. how the news is diffused in the network). This paper aims to build a novel machine learning model based on Natural Language Processing (NLP) techniques for the detection of ‘fake news’ by using both content-based features and social features of news. The proposed model has shown remarkable results and has achieved an average accuracy of 90.62% with F1 Score of 90.33% on a standard dataset.

Virtualization is widely adopted by the data centers, in order to fulfill the high demand for resources and for their proper utilization. For system management in these virtualized data centers virtual machine live migration acts as a key method. It provides significant benefit of load-balancing without service disruption. Along with the various benefits virtual machine live migration also imposes performance overhead in terms of computation, space and bandwidth used. This paper analyzes the widely used precopy method for virtual machine live migration and proposes the two fold optimization of precopy method for virtual machine live migration. In the first phase, the proposed two fold precopy method reduces the amount of data sent in first iteration of precopy method. Second phase restricts sending of similar data iteratively in each subsequent iterations of precopy method by identifying frequently updated pages and keeps it till the last stop and copy iteration. In this way it reduces total migration time and total amount of data transferred. The proposed two fold precopy method is compared with precopy method and simulation results show the performance improvement of a virtual machine live migration in terms of total migration time and total amount of data transferred.