Skip to main content

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