User Utility Oriented Queuing Model for Resource Allocation in Cloud Environment

Zhang, Zhe; Liu, Ying

doi:10.1155/2015/246420

Cited by 6 publications

(1 citation statement)

References 21 publications

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“…This reduces: the overall energy consumption for the benefit of cloud service provider, and the overall execution cost and entire time of execution for the clients' satisfaction. Benefits of ant colony algorithm includes [28] In [29], the authors Zhang and Li proposed a user utility oriented queuing model to handle task scheduling in cloud environment. These authors modelled task scheduling as an M/M/1 queuing system, classified the utility into time utility and cost utility, and built a linear programming model to maximize total utility for time utility and cost utility.…”

Section: Resource Management and Challenges 4) Resource Management Momentioning

confidence: 99%

Cloud Service Level Agreements and Resource Management

Odun-Ayo¹,

Udemezue²,

Kilanko³

2019

Adv. sci. technol. eng. syst. j.

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Cloud computing is a technical "as-a-service" usage model utilizing virtualization. Virtual machines are the core of cloud computing that runs as independent machine grouped into different networks within the hypervisor. Practically done by deployment of clouds computing hosts enterprise servers in virtual machines on an array of high-end servers. Managing cloud resources has to do with controlling and limiting access to the pool of available resources. This brings about the conception of an agreement between the resource services cloud providers and the customers otherwise known as Service Level Agreement, in other to restrict access to provisioned resources. Resource provisioning is a flexible on-demand pay-as-you-go package that is negotiated; and signed based on SLAs between customers and cloud providers. SLAs enable cloud providers to evade costly SLA consequences payable when there are violations, optimizing the performance of customers' applications and professionally manage resources to reduce cost. These documents are the agreements called Service Level Agreements (SLAs). SLAs outline the expectations which are: terms, conditions, and services of the clients from their service providers regarding availability, redundancy, uptime, cost, and penalties in cases of violations. These ensure clients' confidence in the services offered. Managing resource is an ongoing major issue in cloud computing. Considering the limitation of resources, it poses a challenge for cloud service providers to make provision for all resources as needed. This paper seeks a solution to problems that relates to the present trends and developments of what cloud Service Level Agreements are and it ensures so by reviewing current literature. Thus, this research is a study of cloud Service Level Agreements, cloud resource management and their challenges. This paper has made provision to act as guidance for future research and it is anticipated to be beneficiary to potential cloud end users and cloud service providers.

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Section: Resource Management and Challenges 4) Resource Management Momentioning

confidence: 99%

Cloud Service Level Agreements and Resource Management

Odun-Ayo¹,

Udemezue²,

Kilanko³

2019

Adv. sci. technol. eng. syst. j.

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Responses of extreme high temperatures to urbanization in the Beijing–Tianjin–Hebei urban agglomeration in the context of a changing climate

Wang

Ren

Song

et al. 2021

Meteorological Applications

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Extreme high-temperature event is one of the most urgent climate issues faced by coordinated development of the Beijing-Tianjin-Hebei region (BTH) in the future due to global warming and urbanization. Based on the homogenized daily temperatures from 174 meteorological observation stations, six extreme hot events were detected. The results revealed the spatiotemporal change characteristics of the extreme high temperature in the BTH. The acquired evidence showed the maximum daily minimum temperature (TNx), high-temperature days (SU35), hot night days (TR25), and heatwave spell durations (HWDI) have significantly increased, while the daily temperature range (DTR) has significantly decreased (p < 0.01) during 1961-2018. The SU35, TR25 and HWDI in 2010s were 68%, 2.8 times and 2.1 times higher than that in 1980s, respectively. Moreover, since 1961, the high-temperature season in the BTH has been getting longer at a rate of 7.4d/10a. The study also revealed the contribution of urbanization on high-temperature indices depends on city size and location in the BTH. The magnitudes of the indices change in the downtown area of Beijing, Tianjin and Shijiazhuang ranked top in the 13 cities of the BTH, which are closely related to the urban development. The mean contribution of urbanization on maximum daily maximum temperature (TXx), TNx, SU35 and TR25 was 68%, 45% and 27% in Beijing, Tianjin and Shijiazhuang, respectively. The socio-economic driving factors have an important impact on the change rates of the extreme high-temperature indices, which means that controlling population, city size and reducing energy consumption could effectively alleviate the urban heat island (UHI) effect and slow down the high-temperature events in the BTH. In the future, it is vital to further study and investigate the mechanism of the extreme high-temperature changes through numerical simulations and to research their impact and response in this region.

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