Advances, Systems and Applications
Table 1 Summary of relevant techniques
From: Cost optimization in cloud environment based on task deadline
Reference | Technique | Performance Metrics | Simulation Tool | Main differences from proposed algorithm |
|---|---|---|---|---|
Tyagi et al. [12] | Throttled load balancing | RT & Cost | Cloud Analyst | Deadlines of the requests are not considered |
Ramasubbareddy et al. [13] | Load balancing | RT & Cost | Cloud Analyst | Deadlines of the requests are not considered |
Naha et al. [14] | Load Aware Over Cost Algorithm | RT Processing time Cost | Cloud Analyst | Unable to allocate resources dynamically |
Manasrah et al. [15] | Differential Evolution | Cost & overall RT | Cloud Analyst | High time complexity |
Kulkarni et al. [16] | Cost Aware Service Broker | Electricity cost | Cloud Analyst | QoS is not maintained in terms of RT |
Jain et al. [17] | Fuzzy rules algorithm | Energy consumption | Cloud Analyst | RT and Processing time are not optimized |
Rekha et al. [18] | Heuristic-based approach | RT and VM cost | Cloud Analyst | Outperfromed in selected scenarios |
Patel et al. [19] | VM to host Ratio | RT | Cloud Analyst | Algorithm only applicable within datacenters |
Tarawneh et al. [20] | Adaptive User-Oriented Fuzzy-Based | Cost and RT | Cloud Analyst | Deadlines of the requests are not considered |
Benlalia et al. [21] | Proximity-based routing | Cost and RT | Cloud Analyst | No simualtions / implementation results |
Chandan et al. [22] | Deadline Based | Task acceptance ratio | MATLAB | Ignore the switching cost of VM |
Junaid et al. [24] | Data File type formatting using Ant Colony | RT Migration time, Energy consumption | Cloudsim | Ignore cost optimization only categorize and process four types of data. |
Ghasemi et al. [25] | Machine Learning base VM replacement | Processor Memory Bandwidth | Cloudsim | Deadlines of the requests are not considered and deep Learning can be used to enhance results |
Junaid et al. [26] | Data File type formatting using Cat Swarm Optimization | RT Migration time Energy consumption | Cloudsim | Deadlines of the requests are not considered |
Maswood et al. [27] | Weighted Factors for Priority routing | Load Balancing Cost and Bandwidth | AMPL/CPLEX | Dependence on weighted factors and response time not optimized. |
Punit Gupta et al. [28] | ANN and Nature inspired algorithm | execution cost, average start time, and finish time | CloudSim | High time complexity, Not suitable for dynamic/runtime decision making |
Abbas Najafizadeh et al. [29] | Ant colony algorithm | execution time, service execution cost, deadline, and access level | MATLAB | High time complexity, Not suitable for dynamic/runtime decision making |
Bezdan et al. [30] | Swam intelligent based approach | Resource utilization, quality of service and makespan | CloudSim | High time complexity, Not suitable for dynamic/runtime decision making |