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Table 2 Comparative analysis of cloud availability and reliability solutions

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