The cloud computing is an emerging paradigm over the internet which provides applications and services based on the concept of abstraction and virtualization for a fraction of the cost. The number of cloud user increases day by day to utilize the available resources. Most of the cloud applications are run at remote nodes where many clients may request for the server at a time. This causes overloading in server which results in fault. Load balancing is the networking technique that distributes load to the nodes to optimize resource utilization, throughput, response time and overload. The need of load balancing increases with increase in the demand for computing resources. Faulttolerance is the ability of system to continue to work even in the presence of fault. This is a critical issue to be addressed to ensure reliability and availability in cloud computing. By effectively balancing the incoming load, fault tolerance can be achieved in cloud. This paper aims to compare the efficient load balancing algorithms that are fault tolerant.

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Cloud computing is a computing paradigm which provides a dynamic environment for end users to guarantee Quality of Service (QoS) on data towards confidentiality on the out sourced data. Confidentiality is about accessing a set of information from a cloud database with a high security leveL This research proposes a new cloud data security model, A Neural Data Security Model to ensure high confidentiality and security in cloud data storage environment for achieving data confidentiality in the cloud database platform. This cloud Neural Data Security Model comprises Dynamic Hashing Fragmented Component and Feedback Neural Data Security Component. The data security component deals with data encryption for sensitive data using the RSA algorithm to increase the confidentiality level. The fragmented sensitive data is stored in dynamic hashing. The Feedback Neural Data Security Component is used to encrypt and decrypt the sensitive data by using Feedback Neural Network. This Feedback Neural Network is deployed using the RSA security algorithm. This work is effici ent and effi!C tive for all kinds of queries requested by the user. The performance of this work is better than the conventional cloud data security models as it achieve a high data confidentiality leveL