From: Reliability and high availability in cloud computing environments: a reference roadmap
Papers’ reference | Main idea | Advantages | Challenges | Evaluation metrics |
---|---|---|---|---|
[46] | Investigating the repair policy and system parameters on cloud availability | Repair policy effectiveness is evaluated Using differential analysis for analyzing parameter sensitivity | Types of Failures are not considered Limitation on number of physical machines The lack of different types repair facilities in evaluation | MTTR Steady state availability MTTM Pool size |
[47] | Storage services availability evaluation using hierarchical models | Adoption of availability importance index Critical components availability identification | Study case study and assessments are limited to the Eucalyptus platform | MTTF MTTR File Size MaxClients InService Throughput |
[32] | Using VM replicas in cloud datacenter to provide high availability | Resource optimization while assuring availability | VM and application scheduling is not considered in the proposed method Evaluation on a small cloud infrastructure | Latency OMG DDS QoS Standard Deviation |
[48] | Applying non-sequential Monte Carlo Simulation to reliability evaluation | A new cloud computing test-bed were developed A new algorithm for expansion planning were presented | This approach cannot be used for modeling other reliability features such as live VM migration | Number of failures Number of VM allocations |
[49] | Using a combination of a stochastic Petri net model and a proposed cloud scoring system | Considering both cloud consumers and cloud providers in the proposed method Proposing a cloud scoring system | The proposed cloud scoring system overhead and cost is not considered The user requirements are limited to only cost and energy in this study | OPEX option Carbon footprint option Overload factor Deployment Distances Relative average utilization |
[50] | Comparing two fault tolerance techniques according to the cloud consumers’ and providers’ requirements | Considering both cloud consumers’ and cloud providers’ requirements | Failure prediction mechanism is required | MTBF Electricity Bill Failure prediction accuracy Energy consumption Task completion rate |
[51] | Amending the current cloud simulators to support HA features | Considering green computing | Limited availability evaluation metrics | Request per second Average service time Power consumption |