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| S. no. | Author and year | Methodology | Parameters | Limitations | Tool |
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| 1 | Sreenivasulu and Paramasivam (2021) [13] | Hybrid optimization algorithm (BAT and BAR), hierarchy process model, and MOML preemption policy | Turnaround time, response time, memory utilization, bandwidth utilization, and resource utilization | (i) The author does not consider energy consumption and is required to prove the efficiency of the proposed algorithm with real-time workflows | CloudSim |
|
| 2 | Dubey and Sharma 2021) [14] | Hybrid AC-PSO algorithm and task scheduling | Makespan rate, cost, and resource utilization rate | (i) The author does not define the fitness function for energy | CloudSim |
| (ii) The work does not consider the parameters of energy consumption, throughput, and schedule length |
| (iii) Need to improve the time complexity |
|
| 3 | Dubey and Sharma (2021) [15] | Hybrid CR-PSO algorithm | Makespan rate, cost, execution time, and energy consumption | (i) Author required plan scheduling for dependent tasks and needed to verify the effectiveness of proposed work on parameters such as energy consumption, load balancing, task rejection ratio, and turnaround time | CloudSim |
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| 4 | Prem Jacob and Pradeep (2019) [20] | CPSO | Deadline, makespan time, and cost | (i) Required to consider various other QoS service parameters and energy consumption | CloudSim |
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| 5 | Khan and Santhosh (2021) [24] | PSGWO | Makespan time and execution time | (i) Required to apply this technique for various applications | NetBeans |
| Waiting time, energy efficiency, and resource utilization |
|
| 6 | Kumar and Sharma (2018) [25] | PSO-COGENT | Execution time, execution cost, makespan time, energy consumption, throughput, and task rejection ratio | (i) Required to consider various SLA and QoS parameters for verifying the algorithm’s effectiveness | CloudSim |
| (ii) need to test for various workflows in the cloud |
|
| 7 | Velliangiri et al. (2021) [26] | HESGA | Makespan time, cost, and response time | (i) Required to apply this approach with other applications such as agriculture and so on | CloudSim |
| (ii) Need to consider various parameters such as energy consumption, load balancing, QoS, and so on |
|
| 8 | Gokuldhev and Singaravel (2020) [27] | LPMSA | Makespan time and energy consumption | (i) The proposed technique is required to test with real-time application and needs to consider various parameters and is still required to enhance the algorithm | CloudSim with Java |
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| 9 | Gokuldhev and Singaravel (2020) [28] | LPGWO | Makespan time and energy consumption | (i) This work needs scheduling in low and high machine heterogeneity was enhanced and consider various QoS metrics is required | CloudSim with Java |
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| 10 | Dubey et al. (2018) [29] | HEFT | Makespan time and load balancing | (i) The proposed method is required to consider various QoS parameters and need test its effectiveness | CloudSim |
| 11 | Ragmani et al. (2020) [33] | FACO (ACO and fuzzy logic) | Total processing time, response time, cost, and load balancing index | The proposed approach needs to be evaluated within a real and multicloud computing architecture and required considering various parameters such as energy consumption | CloudSim |
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| 12 | Bhasker and Murali (2022) | The proposed method (HES-ACO) | Total execution time, execution cost, makespan time, energy consumption, throughput, task rejection ratio, resource utilization, and deadline constraint | The proposed approach extends this work further to consider security issues while users access the cloud’s information | CloudSim |
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