Jenkins' Deliberations on Communal Conflict with the Leaders of Punjab: 1946-47 (Part-I)

Bhim Sen Sacher informed Jenkins about the destruction caused by arson in Lahore. Akbari Mandi, Chune Mandi, Chauhatta Basti, Bhagat Singh Basti, Kucha Kagzian and Pipal Vehra had been burnt down. The fire brigade could not cope with those vast and dispersed areas. If someone tried to extinguish the fire he was shot at by the police. Bhim Sen Sachar suggested that the only way to save Lahore was to impose martial law in the city. He hoped that the Governor would take that step immediately.64 Jenkins thanked Lala Bhim Sen Sachar and Gokul for their letters informing him about Lahore. Jenkins explained that fire brigade had done a good job in spite of constraints and difficulties. He believed that all communities had access to incendiary materials, and could use it without detection by traversing joined roof-tops. Throwing fire-balls from one house to another was wreaking devastation. Checking trouble of that kind was not an easy job, but searches were carried out and culprits were arrested.6

Cloud Evolution Management Using Intelligent Cloud Ecosystem Ice

This research is primarily focused on cloud computing and the spread of this technology with an enormous speed, which is sufficient to explain the need and desirability of this technology, on the other hand, same distinction is also the main challenge i.e. unplanned growth of cloud computing and relevant technologies. In past we have seen the same issues with world wide web, in which we have expanded to such levels that a proper governance and maintenance became near to impossible. Rapidly expanding cloud technology with conventional and emerging services is a source of generating huge volumes of data that requires to be addressed for analytics and simply for suitable storage structure. Big data and IoT are two emerging challenges linked to cloud computing and these two areas are research focus of many scientists. In this research we have proposed an Intelligent Cloud Ecosystem (ICE) which is a blend of cloud technology along with artificial intelligence and cognitive science. We believe that an autonomous and self-evolving intelligent environment is the solution to emerging problems related to cloud technologies. To address the issues of Big data and IoT, our proposed model ICE is having the ability to analyze the heterogeneity and homogeneity knowledge structures wherein, machine learning and artificial neural networks have been proposed for semantic, property and feature analysis. Validation of the proposed model ICE is being done through algorithm development as well as by simulating the model in MATLAB. Results have shown the positive inclination towards ecosystem relevance with overall performance and interoperability i.e. these two parameters play a significant role in the sustenance of the intelligent ecosystem, while third parameter is dynamic which may change as per the requirement e.g. reliability, security, cost etc. This research concludes that cloud technology will work better in a comprehensive cloud ecosystem with better management and service parameters for users as well as for cloud service providers, also the issues of Big data and IoT are more manageable and observable in a cloud ecosystem.