The performance of service in cloud environment is a dominant factor which impacts the performance of the entire cloud system. However, the most organizations maintain their own private clouds to maintain their data and enable the access for the users of their own organization. There exist several load balancing and security protocols to access the services and maintain their data in the cloud environment but suffer to achieve higher performance. To handle this issue, Load Balancing, Security, and Data Deduplication (LBSDD) algorithm is presented. Initially, the request received from various users and various locations. Next, request and server related features are extracted. Then, select the best features from the extracted features using HGOA algorithm. After that the LBSDD factors are evaluated for the cloud performance. In evaluation user request is balanced by using Dropbox-NGINX tool with selected features. Next, the user may upload the files to the cloud server, so for providing security is an important factor here the security is maintained by using DKME4C algorithm. Then, the third factor is Data Deduplication evaluated using hashed indexes, tables, here the hash code is generated using the SHA-512 algorithm in this proposed method Data Deduplication is named as E-HIT. The proposed LBSDD algorithm achieves higher performance in server efficiency than other methods.

云环境中服务的性能是影响整个云系统性能的主要因素。但是，大多数组织都维护自己的私有云以维护其数据并为自己组织的用户提供访问权限。存在几种负载平衡和安全协议来访问服务并在云环境中维护其数据，但是要获得更高的性能是很困难的。为了解决此问题，提出了负载平衡，安全性和重复数据删除（LBSDD）算法。最初，从各个用户和各个位置接收到该请求。接下来，提取与请求和服务器相关的功能。然后，使用HGOA算法从提取的特征中选择最佳特征。之后，针对云性能评估LBSDD因子。在评估中，可以通过使用具有所选功能的Dropbox-NGINX工具来平衡用户请求。接下来，用户可以将文件上传到云服务器，因此，为了提供安全性是重要的因素，此处使用DKME4C算法维护安全性。然后，第三个因素是使用哈希索引，表评估的重复数据删除，此处使用SHA-512算法生成哈希码，该数据删除方法称为E-HIT。所提出的LBSDD算法在服务器效率方面比其他方法具有更高的性能。第三个因素是使用哈希索引，表评估的重复数据删除，此处的哈希码是使用SHA-512算法生成的，在此建议的方法中，重复数据删除称为E-HIT。所提出的LBSDD算法在服务器效率上比其他方法具有更高的性能。第三个因素是使用哈希索引，表评估的重复数据删除，此处的哈希码是使用SHA-512算法生成的，在此建议的方法中，重复数据删除称为E-HIT。所提出的LBSDD算法在服务器效率方面比其他方法具有更高的性能。