A Critical Review on Load Balancing, Task And Resource Scheduling In A Cloud Environment: The Best UK Dissertation Research Topics From Existing Recent Research Gaps In Computer Science Engineering Domain
                     OCT 8, 2019
Research Paper
CRITICAL REVIEW
LOAD BALANCING, 
TASK  AND 
RESOURCE
SCHEDULING IN CLOUD  
ENVIRONMENT
The Best UK Dissertation Research Topics from Existing Recent 
 Research Gaps in Computer CSrcitiiceanl Rcev iEewn Igni nCleoeudr iCnogm Dpuotinmg,a Eingineering & Technology
Tags: Tutors India Computer Science Dissertation Topics Topics in Computer Science Computer Science dissertation help
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Reviewed the literature article by considering load  
balancing, task and resource scheduling method for 
 efficient cloud service provisioning.
There is a possibility to minimize the total cost of  
computation by new scheduling method on the basis of 
SHORT NOTES  bio-inspired heuristics.
Single objective- and multi-objective-based task  
scheduling method for making multidimensional task and 
 resource scheduling model.
Tested the suggested system performance using 
 CloudSim simulator toolkit.
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LOAD BALANCING,  
TASK AND RESOURCE  
SCHEDULING IN  
CLOUD 
ENVIRONMENT
- RESEARCH PAPER
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01
Priya et al. (2018) presented a load balancing (LB) and resource scheduling (RS)   
approach for efficient cloud service provisioning. The simulated results shown that  
attained better performance with respect to high resource scheduling efficiency,  
average success rate and reduced the response time. Future Research Scope for PhD  
Scholars based on Priya et al: But the primary criteria called, scheduling of task not  
addressed. Also, need to consider LB and RS of intermediate data toward enhancing  
the system performance by considering privacy-preserving as a metric together with  
other metrics like average response time and success ration.
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02
Nasr et al. (2018) suggested an Online Potential Finish Time (OPFT) task scheduling method for  
enhancing the scheduling performance and resolve the QoS issues. The performance of OPFT  
method is assessed via CloudSim, and the simulated results indicate that this method better  
efficient. Future Research Scope for PhD Scholars based on Nasr et al: However, the scheduling  
performance is poor; hence there is a need to improving the scheduling efficiency. Also, integrity  
of virtual machine and overhead, multidimensional resource scheduling was not addressed.
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03
Adhikari et al. (2019) suggested a load balancing resource clustering method approach toward  
attaining optimal resource clustering and their cluster centers for faster convergence via meta-  
heuristic Bat-algorithm. Future Research Scope for PhD Scholars based on Ashikari et al: The  
suggested method has been evaluated by considering synthetic datasets, as a resulted shown
superiority than the traditional approach. But, the of  VM and overhead
integrity  unaddressed. Also, needs to validate its remain  the multidimensional
performance for  scheduling process. resource
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04
Adhikari et al. (2019) proposed a chaotic symbiotic organisms search (CMSOS) method for  
resolving multi-objective large scale task scheduling optimization issues on cloud computing  
environment. The suggested model performance has been evaluated using synthesized  
workloads, and standard workload traces for huge instances. The simulated results of CMSOS  
shown better optimal trade-offs. Future Research Scope for PhD Scholars based on Adhikari et  
al: However, the resource management, integrity of VM remains unaddressed. Also, needs to  
handle QoS requirements like security and reliability for very large workload instances.
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05
Chaudhary and Kumar (2019) presented a Hybrid Genetic-Gravitational Search Algorithm (HG-GSA)  based 
load scheduling technique for minimizing the computation cost. The simulated results have shown  that 
they minimized the computation cost which significantly improved the system performance than the  
traditional method. But the suggested method is not suitable for multidimensional resource scheduling  
strategies. Future Research Scope for PhD Scholars from Chaudhary: The task scheduling and resource  
management remain unaddressed. Also, there is possibility to minimize the total cost of computation by  
new scheduling method on the basis of bio-inspired heuristics.
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06
Arunarani et al. (2019) reviewed the available task scheduling methods and related metrics which is  
appropriate for a cloud platform. At the end of research they have recommended enhancing  the  
effectiveness of scheduling by combining virtual machine consolidation and task scheduling strategies.  
Also, will consider the different input parameters. Future Research Scope for PhD Scholars based on  
Arunarani et al: Then, there should be a need for single objective- and multi-objective-based task scheduling  
for enhancing the system performance by hybrid combination of earlier algorithms. But the major concern  
like integrity of virtual machine and overhead, load balancing, resource management remains unaddressed.
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COMPARISON TABLE
S.No. WORK BY METHOD IMPLEMENTATION TOOL FINDINGS & CONCLUSION LIMITATION / FUTURE SCOPE
High resource scheduling Scheduling of task not addressed.  
LB CloudSim  
1) Priya et al.(2018)  efficiency. Needs to validate the performance of 
and RS method simulator toolkit Reduced the system  success ration.
response time.
OPFT task  CloudSim  Task Completion Time has Scheduling performance is poor.  
2) Nasr et al. (2018) scheduling method simulator toolkit  been minimized Multidimensional resource scheduling was 
 not addressed.
Multidimensional resource scheduling
Load balancing  
CloudSim  Attained less execution cost, was not addressed.
3) Adhikari et al. (2019) resource clustering 
simulator toolkit  makespan within the given  Needs to scrutinize the trade-off among 
 method constraints  different nature-inspired algorithms 
with  task deployment policies.
Better optimal trade-offs
amongst financial cost  Resource management, integrity 
CloudSim  
4) Adhikari et al. (2019) CMSOS method (cost) and execution time. 
of VM  remains unaddressed.
simulator toolkit
 There is no To validate the performance for large 
computational  overhead.  workload instances.
HG-GS based  
5) Chaudhary and CloudSim  load scheduling Minimized the computation cost
Task scheduling and resource management 
 Kumar simulator toolkit  remain unaddressed
 technique
(2019)
Suggested to enhance the
Reviewed the task  
system performance by single  To enhance of scheduling performance by 
6) Arunarani et al. (2019) scheduling methods NA and multi-objective-based task  combining VM consolidation and task  
 and related metrics
 scheduling scheduling strategies
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RECOMMENDATIONS
To scrutinize the trade-off among different nature-inspired algorithms with task  
deployment policies for various types of service level agreements (SLA) with their  
penalties and load balancing policies.
To minimize the total cost of computation by a new scheduling method on the basis  
of bio-inspired heuristics. Also will enhance the system performance by hybrid  
combination of single objective- and multi-objective-based task scheduling method.
To enhancing the cloud system performance for the multidimensional dataset by  
considering integrity of virtual machine, overhead and multidimensional resource  
scheduling strategies.
To handle various QoS requirements like security and reliability for very large  
workload instances.
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