In data centers, the energy-efficient scheduling of virtual machines (VMs) is critical to the full utilization of physical machines (PMs). Considering the sheer amount of data in cloud environment, this paper puts forward a novel energy-efficient scheduling method for VM consolidation and migration in cloud data centers. The proposed method optimizes the energy consumption at cloud data centers through three algorithms: the first algorithm describes the general migration of VMs among PMs; the second algorithm defines the migration of VMs among PMs; the third algorithm explains how the migration takes place. The effectiveness of our method was demonstrated on CloudSim with 5 PMs and 30 VMs, under the constraints of arrival time and deadline. The results show that our method can balance the load of input jobs and schedule the VMs properly, thus reducing the carbon emissions at the cloud data center.
Cloud has been emerging, popular and very demanding technology now a day. Cloud has got wide popularity with its sophisticated features such as internet access, more storage, easy setup, automatic updates, low cost and resource provisioning based on "pay as you go" policy. In spite of advantages, security is considered to be more important and drew the attention of many researchers. The data storage is becoming an indispensable measurement in cloud and most of the times cloud does not guarantee that information/data that has been stored is secured from illegitimate access. Many researchers are working to ensure information security in cloud but unfortunately they do not provide adequate security. This paper is aiming to propose an efficient algorithm with obfuscation and cryptography for unstructured data. The algorithm works to preserve confidentiality of data stored in cloud at two levels. At the fist level the algorithm obfuscate the document by replacing the key words (obfuscation), and at the second level obfuscated document is encrypted using traditional RSA algorithm for better security. Experimental results shows that the proposed algorithm yields good results.
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