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Cloud resource provisioning: survey, status and future research directions

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Abstract

Cloud resource provisioning is a challenging job that may be compromised due to unavailability of the expected resources. Quality of Service (QoS) requirements of workloads derives the provisioning of appropriate resources to cloud workloads. Discovery of best workload–resource pair based on application requirements of cloud users is an optimization problem. Acceptable QoS cannot be provided to the cloud users until provisioning of resources is offered as a crucial ability. QoS parameters-based resource provisioning technique is therefore required for efficient provisioning of resources. This research depicts a broad methodical literature analysis of cloud resource provisioning in general and cloud resource identification in specific. The existing research is categorized generally into various groups in the area of cloud resource provisioning. In this paper, a methodical analysis of resource provisioning in cloud computing is presented, in which resource management, resource provisioning, resource provisioning evolution, different types of resource provisioning mechanisms and their comparisons, benefits and open issues are described. This research work also highlights the previous research, current status and future directions of resource provisioning and management in cloud computing.

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Acknowledgments

One of the authors, Sukhpal Singh, acknowledges the Department of Science and Technology (DST), Government of India, for awarding him the INSPIRE (Innovation in Science Pursuit for Inspired Research) Fellowship (Registration/IVR Number: 201400000761 [DST/INSPIRE/03/2014/000359]) to carry out this research work. We would like to thank all the anonymous reviewers for their valuable comments and suggestions for improving the paper. We would also like to thank Dr. Maninder Singh [EC-Council’s Certified Ethical Hacker (C-EH)] for his valuable suggestions.

Author information

Authors and Affiliations

  1. Computer Science and Engineering Department, Thapar University, Patiala, Punjab, 147004, India

    Sukhpal Singh & Inderveer Chana

Authors
  1. Sukhpal Singh
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  2. Inderveer Chana
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Corresponding author

Correspondence to Sukhpal Singh.

Appendices

Appendix 1: Data items extracted from all papers

Data item

Description

Bibliographic data

Author, year, title, source of research paper

Type of article

Conference, workshop, symposium, journal

Study context

What are the research focus and its aim?

Study plan

Classification of resources in cloud, resource provisioning evolution, RPMs etc.

What is the RPM?

It explicitly refers to the resource provisioning mechanism and their subtypes

How was comparison carried out?

Compare various traits objective function, provisioning criteria, operational environment etc.

Data collection

How the data of resource provisioning in cloud was collected?

Data analysis

How to analyzed data and extracted research challenges?

Simulation tool

It refers to tool used for validation

Research challenges

Open challenges in the area of cloud resource provisioning

Appendix 2: Journals/conferences reporting most resource provisioning mechanism related research

Publication source

J/C/S/W

#

N

International Conference on Service Sciences (ICSS)

C

3

1

Future Generation Computer Systems

J

28

13

Concurrency and Computation: Practice and Experience

J

8

3

IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)

S

7

2

ACM Computing Surveys

J

5

3

IEEE Symposium on Computers and Communications (ISCC)

S

3

1

Proceedings of IEEE INFOCOM

C

8

1

IEEE Computer Software and Applications Conference Workshops (COMPSACW)

W

3

1

IEEE/ACM International Conference on Grid Computing (GRID)

C

6

2

IEEE International Conference on Cloud Computing (CLOUD)

C

19

6

Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems

C

2

1

ACM SIGOPS Operating Systems Review

J

3

1

Journal of Supercomputing

J

8

1

ACM International Symposium on High Performance Distributed Computing

S

4

1

IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

C

17

2

Journal of Grid Computing

J

3

3

Journal of Parallel and Distributed Computing

J

4

1

International Conference on Distributed Computing Systems (ICDCS)

C

6

2

International Conference on Cloud and Service Computing (CSC)

C

2

1

IEEE Transactions on Parallel and Distributed Systems

J

5

3

Computers & Electrical Engineering

J

2

1

Parallel Computing

J

2

1

Journal of Intelligent and Fuzzy Systems

J

1

1

Knowledge and Information Systems

J

5

3

  1. J, journal; C, conference; W, workshop; S, symposium; N, number of studies reporting resource provisioning mechanism as prime study; #, total number of articles investigated

Appendix 3: Acronyms

QoS

Quality of Service

SLA

Service Level Agreement

RPM

Resource Provisioning Mechanism

RPA

Resource Provisioning Agent

WA

Workload Analyzer

RIC

Resource Information Center

CPU

Central Processing Unit

FoS

Focus of Study

VM

Virtual Machine

WRM

Workload Resource Manager

SLO

Service Level Objective

EC2

Elastic Compute Cloud

DMM

Dirichlet Multinomial Model

RP

Resource Provisioning

DLT

Divisible Load Theory

QuiD

Quick image Display

FFD

First Fit Decreasing

DAG

Directed Acyclic Graph

SHC

Stochastic Hill Climbing

NSGA-II

Non-dominated Sorting Genetic Algorithm II

SPEA2

Strength Pareto Evolutionary Algorithm 2

DLE

Data Link Escape

WRR

Weighted Round Robin

DVFS

Dynamic Voltage Frequency Scaling

FIFO

First In First Out

CMNS

Cloud Message Notify Service

SERA

Semantically Enhanced Resource Allocation

GA

Genetic Algorithm

BG

Box/Gray box

offline-BP

offline-Bin Packing

DVM-Pro

Digital Variable Multi System

ABC

Artificial Bee Colony

DPM-RA

Data Protection Manager-RA

RUBiS

Rice University Bidding System

MHOD

Markov Host Overload Detection

TPC-W

Transactional Web Benchmark

RPS

Resource Provisioning Strategy

PCP

Partial Critical Paths

IC-PCP

IaaS Cloud Partial Critical Paths

IC-PCPD2

IaaS Cloud Partial Critical Paths with Deadline Distribution

IDEA

Improved Differential Evolution Algorithm

PSO

Particle Swarm Optimization

HBB-LB

Honey Bee Behavior inspired Load Balancing

ACO

Ant Colony Optimization

FlexPRICE

Flexible Provisioning of Resources In a Cloud Environment

MDBP

Multi-Dimensional Bin-Packing

BRS

Best Resource Selection

FCFS

First-Come-First-Service

NDF

Nearest Deadline First

SJF

Shortest Job First

SEC

Semi-Elastic Cluster

AR

Advance Reservation

CA-PROVISION

Combinatorial Auction-PROVISION

OCRP

Optimal Cloud Resource Provisioning

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Singh, S., Chana, I. Cloud resource provisioning: survey, status and future research directions. Knowl Inf Syst 49, 1005–1069 (2016). https://doi.org/10.1007/s10115-016-0922-3

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