19 Nov 2019

  • November 19, 2019
  • Amitraj
BCA 303: Cloud Computing 
         
                                                                     UNIT I 
Introduction Cloud Computing: Definition, Why Clouds, Vision, foundation / Evolution of cloud computing, Cloud and other computing paradigms(Distributed, Cluster, Grid), Essential Features, Characteristics, Advantages, Challenges, Ubiquitous Cloud and the Internet of Things, Ethical Issue in Cloud Computing, Evaluating the Cloud's Business, Current trends and Future of the cloud,  research issues in cloud environment.

                                                                  UNIT II 
Cloud Computing Architecture and infrastructure: Cloud Reference Model, Layer and Types of Clouds, Services models, deployment models, Data center Design and interconnection Network.

                                                                  UNIT III 
Virtualization:  Definition, Understanding and Benefits of Virtualization, Types of virtualizations (Compute, Network, Storage), Virtualization of Server, Desktop, Network, and data-centers. Types of Hypervisors: VMware, KVM, Xen. Virtual Clusters and Resources Management.

                                                                   UNIT IV 
Cloud Platforms in Industry: Major vendors and their offerings, Introduction to Microsoft Azure,
Amazon web services (EC2, S3, Etc.), Google AppEngine, Aneka: Cloud Application Platform Integration of Private and Public Clouds

Cloud applications: Protein structure prediction, Data Analysis, Satellite Image Processing, CRM and ERP, Social networking. Cloud Application- Scientific Application, Business Application.

                                                                   UNIT V 
Advance Topic in Cloud Computing:  Approaches of Migration into Cloud.  Federated Cloud/ InterCloud, Third Party Cloud Services, Service Level Agreement (SLA), Dynamic resource provisioning and management, Server consolidation and placement policies, Energy efficiency in data centers, Elastic Load Balancing and Auto Scaling.
Techniques for Big data processing (Google GFS, BigTable, and Map-Reduce Hadoop Distributed File System (HDFS), HIVE).



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