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| Authors [ref] | Title/year | Methods | Findings/remarks |
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| Ragmani et al. [8] | An improved hybrid fuzzy-ant colony algorithm applied to load balancing in cloud computing environment/2019 | Fuzzy logic module to calculate pheromone values for any colony optimization | Hybrid load-balancing algorithm
Empirical results proved appropriate for handling complex networks |
|
| Akawee et al. [9] | Using resource allocation for seamless service provisioning in cloud computing/2022 | Survey of recourses allocation | Highlights the importance of resource allocation and its relationship with load balancing, and discusses the limitations of resource allocation in cloud computing |
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| Sethi et al. [10] | Efficient load balancing in cloud computing using fuzzy logic/2012 | Fuzzy logic and round-robin scheduling | Hybrid method
Fuzzy logic is used to identify the virtual machine with the minimum load. Round-robin scheduling for virtual machine assignment for requests |
|
| Hwang and Wood [11] | Adaptive dynamic priority scheduling for virtual desktop infrastructures/2012 | Soft real-time scheduler | The effect of a smaller scheduling time quantum in a virtual desktop infrastructure (VDI) setting was calculated and proved that the order of average overhead time per scheduler call remained unchanged |
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| Begam et al. [12] | Load balancing in DCN servers through SDN machine learning algorithm/2022 | Multiple regression | Server selection is based on a prediction of the response time of the server as a function of current load, response time, bandwidth, and server utilization |
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| Ouhame and Hadi [14] | Enhancement in resource allocation system for cloud environment using modified grey wolf technique/2020 | Grey wolf optimization algorithm | Metrics studied are throughput, energy consumption, and average network execution time in VM for cloud computing |
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| Miriam et al. [16] | An efficient job scheduling in isometric HPCLOUD using ZBLA optimization/2015 | Honey bee behavior | The virtual machine workload was calculated by the HBB algorithm and classified as overloaded, balanced, and light-weighed. The task with high priority was removed from overloaded VMs and assigned to lightweight VMs. These tasks were playing the role of scout bees in the next step |
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| Jena and Mohanty [19] | GA-based customer-conscious resource allocation and task scheduling in multicloud computing/2018 | Genetic algorithm and shortest task first scheduling | Hybrid load-balancing algorithm
Two-phase approach |
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| Hafiz [20] | Efficient load balancing algorithm in cloud computing/2015 | Randomization and greedy algorithm | Hybrid load-balancing algorithm
A load-balancing algorithm for heterogeneous cloud computing environments that improves the efficiency |
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