Computational grids are becoming increasingly vital in organizations with ever growing IT infrastructure and the need to increase the productivity of the computing infrastructure by ensuring optimal throughput for their computational jobs. Key to computational grids in the load balancer and job scheduler that is involved in decision making about when and which node to basically use to execute a job/task submitted to the grid. Most of the existing grids use a load function that evaluates the existing resources on the nodes, accesses the resource requirements of the task submitted and decide whether to withhold the job in the queue or schedule it on a node where the resources are available for the job. This decision making process becomes more challenging with jobs that are long duration, I/O intensive and resource requirements vary at different times during the task execution. Most current grid engines factor in the maximum requirement as stated at the time of job submission and are not good at analyzing the variation in resource requirements based on past history of the same job execution and use the information gathered in the decision making process. In this paper, we try to analyze how we can change the load balancing function to introduce more statistical analysis of history of past jobs in the scheduling decision process thereby ensuring we do not end up in trashing situations for I/O intensive jobs while at the same time utilize the available resources as efficiently as possible.

Requirement for power differs throughout the day, improving the average cost of power source. A timeof-use (TOU) expense has been suggested as a demand-side management (DSM) technique to influence customer requirements. In this paper, we explain a game-theoretic approach to improve TOU expenses strategies (GT-TOU). We recommend designs of expenses to power organizations coming up from customer demand fluctuations, and designs of customer fulfillment with the difference between the affordable demand and the actual intake.

The development in the modern technology paved a path in the utilization of surveillance cameras in streets, offices and other areas but this significantly leads a threat to the privacy of visitors, passengers or employees, leakage of information etc.. To overcome this threat, privacy and security needs to be incorporated in the practical surveillance system. It secures the video information which is resided in various video file types. In this process we used an efficient framework to preserve the privacy while distributing secret among ‘N’ number of parties. In this paper we analyzed various techniques of Chinese Remainder Theorem.

No abstract