Allocating resource dynamically in cloud computing
Praveen Kumar, Priyavrat Singh Yadav, Kashish Bhutani, Nagma Arora, Deepanshu Jain, Bhawesh Dabas · 2017
In Cloud Computing, properly utilizing resource allocation dynamically is one of the most important factors for optimization. While utilizing, the main focus is on to use maximum resources which are highly scalable so that the process is completed in a speedy manner. In today's world exploring various algorithm and developing our own more efficient algorithm is desired for the advancement of technology. Similarly, this paper focuses on analyzing two similar algorithms and thereafter proposing a new composite algorithm which focuses on maximizing the throughput of the cloud provider. This proposed algorithm is derived from teaching learning based optimization algorithm (TLBO) and grey wolves optimization algorithm (GW). This algorithm works more efficient in utilizing each of these algorithms. Moreover, it balances time and cost and also tries to avoid local optimization trap which ultimately makes the waiting time minimum. In order to justify its effectiveness we have conducted few experiments and then compared them.