Comparative Analysis of Load Balancing Algorithms for Cloud Computing in IoT

Background: Cloud computing is a widely adopted computing paradigm and its importance has increased multi-folds in the recent past due to the inception of Internet of Things (IoT). Objectives: Efficient load balancing techniques are required to optimize the use of the cloud resources although load balancing in cloud is known to be a NP-hard problem. Methods: This work focuses on multiple load balancing algorithms whose performance has been analysed and compared under varying load conditions. Results: Comparative analysis of 5 algorithms is given, among which max-min algorithm is found to be the best performing algorithm with approximately 28% better job finish time and 23% higher throughput than the worst performing algorithm (FCFS). Conclusion: Simulations have been performed in CloudSim under varying input loads and the performance has been analysed under multiple scenarios. All the simulations have pointed towards the superiority of Max-min algorithm over other algorithms. This work will prompt the researchers to further investigate into load balancing algorithms so that better results are achieved.