Research Scholar, CSE Department, IKGPTU, Jalandhar 144603, India.
IT Department, Chandigarh Group of Colleges, Landran, Punjab 140307, India.
Sensors (Basel). 2021 Feb 24;21(5):1583. doi: 10.3390/s21051583.
Cloud computing offers the services to access, manipulate and configure data online over the web. The cloud term refers to an internet network which is remotely available and accessible at anytime from anywhere. Cloud computing is undoubtedly an innovation as the investment in the real and physical infrastructure is much greater than the cloud technology investment. The present work addresses the issue of power consumption done by cloud infrastructure. As there is a need for algorithms and techniques that can reduce energy consumption and schedule resource for the effectiveness of servers. Load balancing is also a significant part of cloud technology that enables the balanced distribution of load among multiple servers to fulfill users' growing demand. The present work used various optimization algorithms such as particle swarm optimization (PSO), cat swarm optimization (CSO), BAT, cuckoo search algorithm (CSA) optimization algorithm and the whale optimization algorithm (WOA) for balancing the load, energy efficiency, and better resource scheduling to make an efficient cloud environment. In the case of seven servers and eight server's settings, the results revealed that whale optimization algorithm outperformed other algorithms in terms of response time, energy consumption, execution time and throughput.
云计算提供了通过网络在线访问、操作和配置数据的服务。云这个术语指的是一个可以随时从任何地方远程访问的互联网网络。云计算无疑是一项创新，因为在实体和物理基础设施上的投资远远大于云计算技术的投资。本工作解决了云基础设施的功耗问题。因为需要算法和技术来降低能耗并为服务器的效率安排资源。负载均衡也是云计算的一个重要部分，它可以在多个服务器之间平衡分配负载，以满足用户不断增长的需求。本工作使用了各种优化算法，如粒子群优化（PSO）、猫群优化（CSO）、蝙蝠算法（BAT）、布谷鸟搜索算法（CSA）优化算法和鲸鱼优化算法（WOA），以实现负载平衡、提高能效和更好的资源调度，从而构建高效的云环境。在七个服务器和八个服务器的设置情况下，结果表明，在响应时间、能耗、执行时间和吞吐量方面，鲸鱼优化算法优于其他算法。
