Reliability and energy efficient workflow scheduling in cloud environment

Garg, Ritu; Mittal, Mamta; Sơn, Lê Hoàng

doi:10.1007/s10586-019-02911-7

Cited by 86 publications

(32 citation statements)

References 37 publications

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“…Cao et al [17] proposed a soft error-aware VM selection and the task scheduling approach to minimize the execution cost of cloud workflows under makespan, reliability, and memory constraints while considering soft errors in cloud data centers. Garg et al [18] proposed a new scheduling algorithm called the reliability and energy-efficient workflow scheduling algorithm, which jointly optimized lifetime reliability of application and energy consumption and guaranteed the userspecified QoS constraint. Nik et al [19] proposed a scheduling approach, which included four algorithms for minimizing the workflow execution cost while also meeting the user-specified deadline and reliability.…”

Section: Related Workmentioning

confidence: 99%

A Novel Coevolutionary Approach to Reliability Guaranteed Multi-Workflow Scheduling upon Edge Computing Infrastructures

Wang

Zheng

Chen

et al. 2020

Security and Communication Networks

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Recently, mobile edge computing (MEC) is widely believed to be a promising and powerful paradigm for bringing enterprise applications closer to data sources such as IoT devices or local edge servers. It is capable of energizing novel mobile applications, especially the ultra-latency-sensitive ones, by providing powerful local computing capabilities and lower end-to-end delays. Nevertheless, various challenges, especially the reliability-guaranteed scheduling of multitask business processes in terms of, e.g., workflows, upon distributed edge resources and servers, are yet to be carefully addressed. In this paper, we propose a novel edge-environment-based multi-workflow scheduling method, which incorporates a reliability estimation model for edge-workflows and a coevolutionary algorithm for yielding scheduling decisions. The proposed approach aims at maximizing the reliability, in terms of success rates, of services deployed upon edge infrastructures while minimizing service invocation cost for users. We conduct simulative experimental case studies based on multiple well-known scientific workflow templates and a well-known dataset of edge resource locations as well. Simulative results clearly suggest that our proposed approach outperforms traditional ones in terms of workflow success rate and monetary cost.

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Section: Related Workmentioning

confidence: 99%

A Novel Coevolutionary Approach to Reliability Guaranteed Multi-Workflow Scheduling upon Edge Computing Infrastructures

Wang

Zheng

Chen

et al. 2020

Security and Communication Networks

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“…Further studies will create an adapted and responsive web application with the help of MQTT and machine learning methods [51][52][53][54][55][56][57][58][59][60][61] to allow users to interact by topics against smart wireless robots with minimal efforts.…”

Section: Adapting a Lower Response Time Consumesmentioning

confidence: 99%

Internet of Green Things with autonomous wireless wheel robots against green houses and farms

Ram

Ravimaran²,

Krishnan

et al. 2020

International Journal of Distributed Sensor Networks

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Nowadays, smart farming involves the integration of advanced technologies that incorporate low-cost robots to meet the required knowledge and maintain the health of plants in farming. Technologies like precision agriculture are also used to optimize resources based on the field condition. Internet of Green Things is also one of the technologies to integrate and share the information between people and healthy farm things. Internet of Green Things gives the information like soil moisture, temperature, humidity, and nutrient level by means of respective sensors. Monitoring and information gathering in green houses with the help of robots is a tedious and expensive process. In this connection, information is shared among low-cost robots encouraging data availability of the current state of a plant with other robots. This will emphasize the monitoring of green houses in a well-organized way. In this article, a Flask-based framework through Raspberry Pi is proposed for interoperability among the low-cost ESP8266 robots. Data gathering is performed by smart robots that are accessible through Message Queuing Telemetry Transport subscribes by means of Representational State Transfer Application Programming Interface. A cloud-like database server is provided to stock up the data. The integration of robotics with Internet of Green Things gains more advantage in gathering about spatial information data that are connected with the irrigation. Visualization techniques and perspectives based on Internet of Green Things for precision agriculture in the field of farming are highlighted.

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“…Similarly, the blocking ratio should be the lower the better to minimize the impact caused by bandwidth consumption of backbone network. Figure 8 shows that the CPU resource consumption is directly proportional to the number of VDCs and similarly, the energy consumption (Ec) is equivalent to the multiplication of CPU resource consumption (Rc) and time (T ) in Formula (24).…”

Section: B Relatonship Between Performance Energy and Costmentioning

confidence: 99%

Toward SLAs Guaranteed Scalable VDC Provisioning in Cloud Data Centers

Sun

Zhu

et al. 2019

IEEE Access

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Cloud computing has been a cost-efficient paradigm for deploying various applications in datacenters in recent years. Therefore, efficient provisioning for virtual data center (VDC) requests from different service providers (SPs) over physical data centers plays a vital role in improving the quality of service (QoS) and reducing the operational cost of SPs. Therefore, a significant attention has been paid for the VDC provisioning problem. However, few approaches have been proposed for the problem of reliable VDC embedding across multiple data centers, as most of them only consider the problem of VDC mapping within a single data center. In this paper, we study the problem of QoS-aware VDC provisioning across multiple data centers, such that the total bandwidth consumption in the inter-data center backbone network is minimized while satisfying the reliability requirement of each VDC request. We formulate this problem as a mathematical optimization problem by using integer linear programming (ILP) and propose an efficient heuristic algorithm called reliable VDC embedding (RVDCE) algorithm to solve this NP-hard problem. The simulation results show that the proposed algorithm performs better in terms of blocking ratio, CPU resource consumption, and bandwidth consumption of backbone network than the existing solution. In addition, this paper has also incorporated integrated security to minimize security vulnerabilities seen in other similar approaches. Apart from demonstrating how to resolve security challenges in our VDC proposal, cost calculations have been implemented to demonstrate the robustness, resiliency, validity, and effectiveness of the VDC provisioning solution for cloud computing.

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Reliability and energy efficient workflow scheduling in cloud environment

Cited by 86 publications

References 37 publications

A Novel Coevolutionary Approach to Reliability Guaranteed Multi-Workflow Scheduling upon Edge Computing Infrastructures

A Novel Coevolutionary Approach to Reliability Guaranteed Multi-Workflow Scheduling upon Edge Computing Infrastructures

Internet of Green Things with autonomous wireless wheel robots against green houses and farms

Toward SLAs Guaranteed Scalable VDC Provisioning in Cloud Data Centers

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