An energy-optimization-based method of task scheduling for a cloud video surveillance center

Summary Today, cloud computing has developed as one of the important emergent technologies in communication and Internet. It offers on demand, pay per use access to infrastructure, platforms, and applications. Due to the increase in its popularity, the huge number of requests need to be handled in an efficient manner. Task scheduling as one of the challenges in the cloud computing supports the requests for assigning a particular resource so as to perform effectively. In the resource management, task scheduling is performed where there is the dependency between tasks. Many approaches and case studies have been developed for the scheduling of these tasks. Up to now, a systematic literature review (SLR) has not been presented to discover and evaluate the task scheduling approaches in the cloud computing environment. To overcome, this paper presents an SLR‐based analysis on the task scheduling approaches that classify into (a) single cloud environments that evaluate cost‐aware, energy‐aware, multi‐objective, and QoS‐aware approaches in task scheduling; (b) multicloud environment that evaluates cost‐aware, multi‐objective, and QoS‐aware task scheduling; and (c) mobile cloud environment that is energy‐aware and QoS‐aware task scheduling. The analytical discussions are provided to show the advantages and limitations of the existing approaches.

show abstract

“…Xiong, et al 33 An energy-efficient tasks scheduling mechanism for video monitoring center in the cloud.…”

Section: Reference Main Context Advantage Limitationmentioning

confidence: 99%

Task scheduling mechanisms in cloud computing: A systematic review

Motlagh

Movaghar

Rahmani

2019

Int J Communication

View full text Add to dashboard Cite

show abstract

“…The problem of scheduling, outside manufacturing, occurs also in many other industries, such as information technology [7], transportation ([8], medicine [9], scheduling classes (as well as project management) [10].…”

Section: Introductionmentioning

confidence: 99%

The concept of algorithm supporting the process of scheduling production tasks

2018

View full text Add to dashboard Cite

The purpose of the work was to develop a concept of an algorithm which supports the process of scheduling production tasks. The designed algorithm performs a task queue creation process in six steps: selecting a schedule type, declaring a queue length, selecting orders for queue development, loading data, automatic job analysis, and queue and Gantt chart generation, taking a decision on the acceptance of the designed production program. The designed system will use single-attribute priority rules (defined by experts) and multi-attribute rules that can be created by combining single-attribute rules. The concept of an algorithm that supports the process of scheduling production tasks, developed and tested by conducting simulations, can be the basis for developing a computer application supporting decision-making process in a manufacturing or service company.

show abstract

“…Cloud computing is defined by the US National Institute of Standards and Technology (NIST) as a computing model that provides easy access to a shared pool of resources such as computing facilities, storage devices, and software applications through Internet anywhere and anytime [1,2]. Advancement of cloud computing has been promoting the development of video surveillance and has formed a totally new cloud computing service model called video surveillance as a service [3]. According to the statistics by IMS Research, the demand for video surveillance service based on cloud computing is growing at an annual rate of 20% to 30% [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…Because of high reliability and availability, cloud video surveillance (CVS) services can help solve the problems encountered with traditional video surveillance technologies including high maintenance costs of communication and storage devices and low level of data security. For example, in [3], the architecture of typical CVS for commercial service based on virtual machine technology is designed to provide users with a kind of "plug and play" monitoring service with less cost and better convenience, and a task-oriented scheduling method is also proposed subsequently to reduce the energy consumption of the CVS. In [6], a model of video surveillance system based on the network coding distributed file system was established to save storage space.…”

Section: Introductionmentioning

confidence: 99%

“…Our goal in this paper is to develop an energy saving storage method based on an improved SLA for CVS systems. Unlike the task-oriented scheduling method presented in another paper of ours [3], the method presented in this paper focuses on storage node scheduling for energy saving. In practice, both of our methods can be applied to the same data center.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Low Energy Consumption Storage Method for Cloud Video Surveillance Data Based on SLA Classification

Xiong

et al. 2016

Mobile Information Systems

Self Cite

View full text Add to dashboard Cite

With the continuous expansion of the amount of data with time in mobile video applications such as cloud video surveillance (CVS), the increasing energy consumption in video data centers has drawn widespread attention for the past several years. Addressing the issue of reducing energy consumption, we propose a low energy consumption storage method specially designed for CVS systems based onthe service level agreement (SLA) classification. A novel SLA with an extra parameter of access time period is proposed and then utilized as a criterion for dividing virtual machines (VMs) and data storage nodes into different classifications. Tasks can be scheduled in real time for running on the homologous VMs and data storage nodes according to their access time periods. Any nodes whose access time periods do not encompass the current time will be placed into the energy saving state while others are in normal state with the capability of undertaking tasks. As a result, overall electric energy consumption in data centers is reduced while the SLA is fulfilled. To evaluate the performance, we compare the method with two related approaches using the Hadoop Distributed File System (HDFS). The results show the superiority and effectiveness of our method.

show abstract

An energy-optimization-based method of task scheduling for a cloud video surveillance center

Cited by 19 publications

References 26 publications

Task scheduling mechanisms in cloud computing: A systematic review

Task scheduling mechanisms in cloud computing: A systematic review

The concept of algorithm supporting the process of scheduling production tasks

A Low Energy Consumption Storage Method for Cloud Video Surveillance Data Based on SLA Classification

Contact Info

Product

Resources

About