Task Scheduling and Resource Allocation of Cloud Computing

Based on QoS

Pan Bailin 1, a, Wang Yanping 2, b, Li Hanxi 3, c, Qian Jie 4, d

1, 2, 3, 4 Hangzhou Cigarette Factory of China Tobacco Zhejiang Industrial Co., LTD

a panbl@zjtobacco.com, b wangyp@zjtobacco.com，

c lihx@zjtobacco.com， d qianj@zjtobacco.com

Keywords: QoS; Task Scheduling; Resource Allocation; Cloud Computing

Abstract: With the enlargement of the scope of cloud computing application, the number of users

and types also increases accordingly, the special demand for cloud computing resources has also

improved. Cloud computing task scheduling and resource allocation are key technologies, mainly

responsible for assigning user jobs to the appropriate resources to perform. But the existing

scheduling algorithm is not fully consider the user demand for resources is different, and not well

provided for different users to meet the requirements of its resources. As the demand for quality of

service based on cloud computing and cloud computing original scheduling algorithm, the

computing power scheduling algorithm is proposed based on the QoS constraints to research the

cloud computing task scheduling and resource allocation problems, improving the overall efficiency

of cloud computing system.

Introduction

With the cloud proposed computing concept and its low cost and high efficiency of resource use in

terms of outstanding advantages, it is esteemed the major IT companies. The high reliability of

cloud computing need to perfect safety management mechanism and resource monitoring

mechanism; Cloud computing high scalability needed resource management system to support

various heterogeneous resources; The low cost of cloud computing services to resource

management system effectively organize a large number of low-cost PC, and efficient distribution

of resource scheduling strategy is needed to improve the use efficiency of system. So the resource

management to large extent determines the quality of service provided by the cloud computing

platform, is highly efficient and one of the key problems in stable operation of the relationship to

the cloud computing system [1].

The resources matching and task scheduling is one of the cloud computing resources

management basic core functions. Effective task resource scheduling algorithm can reduce the

number of cloud computing system task completion time, increase the efficiency of the use of

computing resources in the system, thus improve the performance of the system and the quality of

services is one of the most core function of this system. It is proposed in this paper, based on the

QoS constraints of computing power scheduling algorithm and the QoS parameters generated by the

vector of resource and task matching, this will be able to distinguish between user service quality

requirements, to provide users with in accordance with the requirements of resources.

Related key technology in cloud computing

The concept of cloud computing has no unified standard, define it as in the United States, "cloud

computing is an available and convenient pay trial mode, in this mode, through the network

on-demand access to structured computing resources Shared pool, quick access to the resources

required, and only need to do a small amount of management" [2].

Advanced Materials Research Vols. 915-916 (2014) pp 1382-1385Online available since 2014/Apr/09 at www.scientific.net© (2014) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMR.915-916.1382

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Cloud computing can provide flexible resources on demand, its form of expression is a series of

collection service. Combined with the application and research of the current cloud computing, the

architecture can be divided into core services, service management, and user access interface layer 3

[3], as shown in figure 1. Core service layer, the hardware infrastructure, software running

environment and application abstract into services, these services have strong reliability, high

availability, size retractable, meet diverse application requirements. Service management as the core

services provide support to further ensure the reliability, availability and security of the core

services. Users to access the interface layer achieve access to the cloud.

Service

management

Virtualization services

Network

resourcePhysical Device

Safety

management

Software as a service

Infrastructure as a service

Application service 1,2...n

Platform as a service

Data processing model

massive data storage

Core

Service

……

Figure 1.Architecture cloud computing

Task scheduling and resource allocation based on QoS

Scheduling model and matching task scheduling and resource allocation can be roughly divided into

batch mode and online mode.

Batch mode refers to the amount of resource requests together to become a task scheduling

cycle, then this will match a set task focused on resources. Scheduling goal is to find a scheduling

scheme, makes the system scheduling cycle of some aspect of the task or resources or some kind of

objective function to achieve expected values or optimal [4]. Group of task scheduling model and

applied to the pattern of the characteristics of the scheduling algorithm is as follows:

Scheduling algorithm based on prediction and empirical data, the valuation task execution time.

Because of the complexity of the cloud computing environment and execution of the

complexity of the task resources, but some factors affect the accuracy of the valuation will be

enormous impact on the algorithm performance.

Through the information feedback and the algorithm of iterative search the global optimal

solution. In the heavy load of cloud computing application environment, the need to scheduled

tasks often many, but also has a high response time for scheduling, applications will be limited.

Online mode is refers to the resource request, not every resource request to their resource

matching. This type of scheduling algorithm often use some simple data structure and algorithm

theory, generally without iteration, so the response speed, suitable for the actual current used in

Advanced Materials Research Vols. 915-916 1383

cloud computing systems. Graphs in the Hadoop system task scheduling model is a kind of typical

online resource scheduling algorithm. Graphs scheduling was divided into two stages, first is job

scheduling stage, followed by the resource matching phase.

Qos is quality Of Service. Computing power scheduling algorithm based on QoS constraints

need to meet the needs of users, with the descriptions in the Worker nodes QoS parameter design,

task and resource matching method, and then design a perfect improved algorithm. Based on the

computing power scheduling algorithm on the basis of introducing the QoS constraints. The core

idea is according to user operation demand of service quality for the user to provide the most

appropriate resources in the cluster [5]. Considering the load of the system problems at the same

time, try to reduce the amount of calculation when choosing tasks allocated, to reduce the load of

the Master. Will be two levels of scheduling between the queue and queue to queue, between the

queue and queue in tertiary scheduling. Among them, the child queues for bias are classified

according to task QoS requirements after dividing the queue. Child queues choice according to the

request allocation of tasks between QoS preference classification of idle resources, thus reducing

subsequent calculations the calculation capacity of the matching degree of each task in the queue.

According to the above description, we can get the computing power scheduling algorithm based on

QoS constraints of a scheduler process as shown in figure 2.

Start

Submit task, load information

Load resources and request to perform task

Choose rank

Eempty filed?

Choose children rank

Eempty filed?

Choose appropriate tasks assigned to the worker

End

Resources

reclassified

Y

N

NY

Figure 2. Execution flow of task scheduling and resource allocation based on QoS

Management system design of task scheduling and resource allocation of cloud computing

Task scheduling and resource allocation integration and management system has the function of the

main interface, needing to design and implementation of some data structures. Resources

organization plan calls for system data structure has two entities, resource management node

resource entities. Which resources entities has geographical information, hardware information,

such as static properties. Monitoring algorithms require resources entities have the dynamic

information such as utilization rate, availability, attributes. A computing resources may be installed

on multiple software, can provide various application service, a kind of software can be installed on

multiple resources, so has the application service software entities, entities and computing resources

and software applications services entity relationship is many-to-many relationships. To achieve the

1384 Advanced Engineering Research

above functions, this paper puts forward as shown in figure 3 cloud computing task scheduling and

resource allocation management system design.

Computing resources

information

Software service

information

Management node

information

Registration and

cancellation module

Resource monitoring

module

Computing resources layer

Task scheduling and

resource allocation module

Information collection

Dstribution and

release module

Monitoring scheduling module

Task

management

layer

Resource management

Figure 3. Management system of task scheduling and resource allocation of cloud computing

Conclusion

In this paper, it analyzes the cloud computing task scheduling and resource allocation management

system that should have the main function based on the cloud computing architecture. On the basis

of in-depth analysis of the resource scheduling, it put forward the resource scheduling algorithm

based on QoS, supporting QoS constraints resources task. At the same time, this paper analyzes the

batch mode and online mode of two kinds of resource scheduling model design thought, puts

forward the task under the guidance of QoS load balancing resource scheduling algorithm, and

further analyzes the cloud computing platform and the research status of resource management

system, and cloud computing resource management subsystem was designed and implemented.

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[3] Y. Fang, and F. Wang, Ge J. Web Information Systems and Mining (Springer Berlin Heidelberg,

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[5] M.D. Dikaiakos, D. Katsaros, and P. Mehra: Internet Computing, Vol. 13(2009) No.5, p. 10

Advanced Materials Research Vols. 915-916 1385

Advanced Engineering Research 10.4028/www.scientific.net/AMR.915-916 Task Scheduling and Resource Allocation of Cloud Computing Based on QoS 10.4028/www.scientific.net/AMR.915-916.1382