Optimising infrastructure as a service provider revenue through customer satisfaction and efficient resource provisioning in cloud computing

Badshah, Afzal; Ghani, Anwar; Shamshirband, Shahaboddin; Chronopoulos, Anthony T.

doi:10.1049/iet-com.2019.0554

Cited by 14 publications

(4 citation statements)

References 33 publications

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“…using related resources as multivariate variables in research. Tis is reinforced by several studies that always focus on these three things alternately, such as the research studies conducted in [64][65][66] and [67]. Tis means that in this case there are very few studies that simultaneously use all the three.…”

Section: Production Process Analysismentioning

confidence: 99%

Optimizing Decision Making on Business Processes Using a Combination of Process Mining, Job Shop, and Multivariate Resource Clustering

Prasetyo

Sarno

Wijaya

et al. 2023

Applied Computational Intelligence and Soft Computing

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The current business environment has no room for inefficiency as it can cause companies to lose out to their competitors, to lose customer trust, and to experience cost overruns. Business processes within the company continue to grow and cause them to run more complex. The large scale and complexity of business processes pose a challenge in improving the quality of process model because the effectiveness of time and the efficiency of existing resources are the biggest challenges. In the context of optimizing business processes with a process mining approach, most current process models are optimized with a trace clustering approach to explore the model and to perform analysis on the resulting process model. Meanwhile, in the event log data, not only the activities but also the other resources, such as records of employee or staff working time, process service time, and processing costs, are recorded. This article proposes a mechanism alternative to optimize business processes by exploring the resources that occur in the process. The mechanism is carried out in three stages. The first stage is optimizing the job shop scheduling method from the generated event log. Scheduling the time becomes a problem in the job shop. Utilizing the right time can increase the effectiveness of performance in order to reduce costs. Scheduling can be defined as the allocation of multiple jobs in a series of machines, in which each machine only does one job at a time. In general, scheduling becomes a problem when sequencing the operations and allocating them into specific time slots without prolonging the technical and capacity constraints. The second stage is generating the resource value that is recorded in the event log from the results of analysis of the previous stage, namely, job shop scheduling. The resource values are multivariate and then clustered to determine homogeneous clusters. The last stage is optimizing the nonlinear multipolynomials in the homogeneous cluster formed by using the Hessian solution. The results obtained are analyzed to get recommendations on business processes that are appropriate for the company’s needs. The impact of long waiting times will increase service costs, but by improving workload, costs can be reduced. The process model and the value of service costs resulting from the mechanism in the research can be a reference for process owners in evaluating and improving ongoing processes.

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Section: Production Process Analysismentioning

confidence: 99%

Optimizing Decision Making on Business Processes Using a Combination of Process Mining, Job Shop, and Multivariate Resource Clustering

Prasetyo

Sarno

Wijaya

et al. 2023

Applied Computational Intelligence and Soft Computing

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“…The revenue maximization is not an exclusive goal of network managers, which provides SFC services to their customers. Several works tried to optimize the revenue in cloud environments, which also is based on virtualization, i.e., launching virtual machines to host applications [83,90,5,4]. However, the way in which revenue will be maximized may differ in an SFC scenario.…”

Section: Revenuementioning

confidence: 99%

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

et al. 2021

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The network function virtualization (NFV) paradigm is an emerging technology that provides network flexibility by allowing the allocation of network functions over commodity hardware, like legacy servers in an IT infrastructure. In comparison with traditional network functions, implemented by dedicated hardware, the use of NFV reduces the operating and capital expenses and improves service deployment. In some scenarios, a complete network service can be composed of several functions, following a specific order, known as a service function chain (SFC). SFC placement is a complex task, already proved to be NP-hard. Moreover, in highly distributed scenarios, the network performance can also be impacted by other factors, such as traffic oscillations and high delays. Therefore, a given SFC placement strategy must be carefully developed to meet the network operator service constraints. In this paper, we present a systematic review of SFC placement advances in dis-

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“…When managing an Infrastructure as a Service (IaaS), it is essential to perform an efficient use of the available resources attending the previously established service level agreements and operation level agreements (SLAs/OLAs). In [20], the employed infrastructure to provide services to costumers is optimized from both the point of view of resource provisioning in the cloud, as well as the satisfaction of costumers. In practice, authors propose a hiring resource model for providers by considering several parameters, such as SLAs, resource allocation, satisfaction, and costs, in order to maximize revenues.…”

Section: State Of the Artmentioning

confidence: 99%

Emulating and Evaluating Virtual Remote Laboratories for Cybersecurity

Robles-Gómez

Tobarra

Vargas

et al. 2020

Sensors

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Our society is nowadays evolving towards a digital era, due to the extensive use of computer technologies and their interconnection mechanisms, i.e., social networks, Internet resources, IoT services, etc. This way, new threats and vulnerabilities appear. Therefore, there is an urgent necessity of training students in the topic of cybersecurity, in which practical skills have to be acquired. In distance education, the inclusion of on-line resources for hands-on activities in its curricula is a key step in meeting that need. This work presents several contributions. First, the fundamentals of a virtual remote laboratory hosted in the cloud are detailed. This laboratory is a step forward since the laboratory combines both virtualization and cloud paradigms to dynamically create emulated environments. Second, this laboratory has also been integrated into the practical curricula of a cybersecurity subject, as an additional on-line resource. Third, the students’ traceability, in terms of their interactions with the laboratory, is also analyzed. Psychological TAM/UTAUT factors (perceived usefulness, estimated effort, social influence, attitude, ease of access) that may affect the intention of using the laboratory are analyzed. Fourth, the degree of satisfaction is analyzed with a great impact, since the mean values of these factors are most of them higher than 4 points out of 5. In addition to this, the students’ acceptance of the presented technology is exhaustively studied. Two structural equation models have been hypothesized and validated. Finally, the acceptance of the technology can be concluded as very good in order to be used in other Engineering contexts. In this sense, the calculated statistical values for the improved proposed model are within the expected ranges of reliability (X2 = 0.6, X2/DF = 0.3, GFI = 0.985, CIF = 0.985, RMSEA = 0) by considering the literature.

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Optimising infrastructure as a service provider revenue through customer satisfaction and efficient resource provisioning in cloud computing

Cited by 14 publications

References 33 publications

Optimizing Decision Making on Business Processes Using a Combination of Process Mining, Job Shop, and Multivariate Resource Clustering

Optimizing Decision Making on Business Processes Using a Combination of Process Mining, Job Shop, and Multivariate Resource Clustering

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

Emulating and Evaluating Virtual Remote Laboratories for Cybersecurity

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