Learn More
Although cloud computing has rapidly emerged as a widely accepted computing paradigm, the research on cloud computing is still at an early stage. Cloud computing suffers from different challenging issues related to security, software frameworks, quality of service, standardization, and power consumption. Efficient energy management is one of the most(More)
Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized(More)
Rough set theory has been proven to be a successful computational intelligence tool. Rough entropy is a basic concept in rough set theory and it is usually used to measure the roughness of information set. Existing algorithms can only deal with small data set. Therefore, this paper proposes a method for parallel computation of entropy using MapReduce, which(More)
Cloud computing is a business oriented approach which involves collaboration of multiple computing technologies via internet. With the rapid increase in cloud usage, it becomes a challenge to deliver the services effectively and efficiently as per client's demand. In this concern Load Balancing has become one of the major key areas for research. There(More)
Virtualization-based server consolidation has been proven to be an ideal technique to solve the server sprawl problem by consolidating multiple virtualized servers onto a few physical servers leading to improved resource utilization and return on investment. In this paper, we solve this problem by using existing servers, which are heterogeneous and(More)
  • 1