scholarly journals M21TCP: Overcoming TCP incast congestion in data centres

2015 ◽  
Author(s):  
Akintomide Adesanmi ◽  
Lotfi Mhamdi
Keyword(s):  
Data Centres

scholarly journals A Load Balancing Algorithm for the Data Centres to Optimize Cloud Computing Applications

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Dalia Abdulkareem Shafiq ◽  
NZ Jhanjhi ◽  
Azween Abdullah ◽  
Mohammed A AlZain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Load Balancing Algorithm ◽  
Data Centres

scholarly journals Secure Framework Enhancing AES Algorithm in Cloud Computing

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ijaz Ahmad Awan ◽  
Muhammad Shiraz ◽  
Muhammad Usman Hashmi ◽  
Qaisar Shaheen ◽  
Rizwan Akhtar ◽  
...  
Keyword(s):  
Data Privacy ◽  
Security Threats ◽  
Privacy And Security ◽  
Plain Text ◽  
Aes Algorithm ◽  
Confidential Data ◽  
Network Usage ◽  
Data Centres ◽  
Demand Service ◽  
Remote Data

The tremendous growth of computational clouds has attracted and enabled intensive computation on resource-constrained client devices. Predominantly, smart mobiles are enabled to deploy data and computational intensive applications by leveraging on the demand service model of remote data centres. However, outsourcing personal and confidential data to the remote data servers is challenging for the reason of new issues involved in data privacy and security. Therefore, the traditional advanced encryption standard (AES) algorithm needs to be enhanced in order to cope with the emerging security threats in the cloud environment. This research presents a framework with key features including enhanced security and owner’s data privacy. It modifies the 128 AES algorithm to increase the speed of the encryption process, 1000 blocks per second, by the double round key feature. However, traditionally, there is a single round key with 800 blocks per second. The proposed algorithm involves less power consumption, better load balancing, and enhanced trust and resource management on the network. The proposed framework includes deployment of AES with 16, 32, 64, and 128 plain text bytes. Simulation results are visualized in a way that depicts suitability of the algorithm while achieving particular quality attributes. Results show that the proposed framework minimizes energy consumption by 14.43%, network usage by 11.53%, and delay by 15.67%. Hence, the proposed framework enhances security, minimizes resource utilization, and reduces delay while deploying services of computational clouds.

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