2019
DOI: 10.1109/access.2019.2927076
|View full text |Cite
|
Sign up to set email alerts
|

A Comprehensive Survey of Load Balancing Strategies Using Hadoop Queue Scheduling and Virtual Machine Migration

Abstract: The recent growth in the demand for scalable applications from the consumers of the services has motivated the application development community to build and deploy the applications on cloud in the form of services. The deployed applications have significant dependency on the infrastructure available with the application providers. Bounded by the limitations of available resource pools on-premises, many application development companies have migrated the applications to third party cloud environments called da… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4

Citation Types

0
25
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
7
2

Relationship

0
9

Authors

Journals

citations
Cited by 38 publications
(25 citation statements)
references
References 57 publications
0
25
0
Order By: Relevance
“…All approaches provide the benefits of shorter response time. Nevertheless, the resource duplication cost must also be taken into account as an extra cost (Niladri Sekhar Dey et al 2019). In general, cloud data center networks are based on huge layered switches with a vast volume of data between thousands of servers has to be transmitted.…”
Section: Introductionmentioning
confidence: 99%
“…All approaches provide the benefits of shorter response time. Nevertheless, the resource duplication cost must also be taken into account as an extra cost (Niladri Sekhar Dey et al 2019). In general, cloud data center networks are based on huge layered switches with a vast volume of data between thousands of servers has to be transmitted.…”
Section: Introductionmentioning
confidence: 99%
“…In distributed systems, applications requiring large volumes of data are studied under "data-intensive computing", in which most of the processing time is dedicated to reading/writing or manipulating the data. With the surge in the amount and pace with which the data are generated, the focus of distributed systems such as cloud computing has shifted from compute-intensive to data-intensive domain [13]. The data to be processed in distributed systems can be broadly classified into three categories: structured, semistructured, and unstructured.…”
Section: Introductionmentioning
confidence: 99%
“…Hadoop utilizes a special and reliable shared storage system, called Hadoop Distributed File System (HDFS), to manage data access in a distributed approach. The HDFS makes ease to access to a data block for a MapReduce job to run the corresponding big data application in parallel [7]- [9]. It can provide a stable and reliable interface to the application, and build a distributed system with high reliability and scalability.…”
Section: Introductionmentioning
confidence: 99%
“…Buyya et al [17] proposed a scheduling algorithm to reduce the response time of the cloud resource with minimum cost. Several scheduling schemes were proposed to balance the workload based on the amount of available resources [9], [18]- [21]. All these schemes are non-preemptive and do not consider priority based on the deadlines of the submitted jobs.…”
Section: Introductionmentioning
confidence: 99%