Cloud Computing Operations Research

Iyoob, Ilyas; Zarifoglu, Emrah; Dieker, A. B.

doi:10.1287/serv.1120.0038

Cited by 44 publications

(16 citation statements)

References 27 publications

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“…In addition, IoT (Atzori et al 2010), big data (Lim et al 2018b), cloud computing (Iyoob et al 2013), wearable devices (Patel et al 2015), cyber-physical systems (Lee 2008), Industry 4.0 (Hofmann and Rüsch 2017), blockchain (Kshetri 2018), IoT-enabled servitization (Lim and Kim 2015), and service-oriented data use (Kim et al 2018) are Service Science, 2018, vol. 10, no.…”

Section: Literature Reviewmentioning

confidence: 99%

Data-Driven Understanding of Smart Service Systems Through Text Mining

2018

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Abstract. Smart service systems are everywhere, in homes and in the transportation, energy, and healthcare sectors. However, such systems have yet to be fully understood in the literature. Given the widespread applications of and research on smart service systems, we used text mining to develop a unified understanding of such systems in a data-driven way. Specifically, we used a combination of metrics and machine learning algorithms to preprocess and analyze text data related to smart service systems, including text from the scientific literature and news articles. By analyzing 5,378 scientific articles and 1,234 news articles, we identify important keywords, 16 research topics, 4 technology factors, and 13 application areas. We define "smart service system" based on the analytics results. Furthermore, we discuss the theoretical and methodological implications of our work, such as the 5Cs (connection, collection, computation, and communications for co-creation) of smart service systems and the text mining approach to understand service research topics. We believe this work, which aims to establish common ground for understanding these systems across multiple disciplinary perspectives, will encourage further research and development of modern service systems.

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Section: Literature Reviewmentioning

confidence: 99%

Data-Driven Understanding of Smart Service Systems Through Text Mining

2018

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“…The major players of the cloud environment are classified into three categories as follows: cloud provider (Provider), the service provider (Broker), and service customer (Consumer) [10]- [12]…”

Section: Cloud Computing Stakeholdersmentioning

confidence: 99%

Identifying the Top Threats in Cloud Computing and Its Suggested Solutions: A Survey

Kofahi¹,

Al-Rabadi²

2018

NET

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The interest in cloud computing has increased rapidly in the last two decades. This increased interest is attributed to the important role played by cloud computing in the various aspects of our life. Cloud computing is recently emerged as a new paradigm for hosting and delivering services over the Internet. It is attractive to business owners as well as to researchers as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. As cloud computing is done through the Internet, it faces several kinds of threats due to its nature, where it depends on the network and its users who are distributed around the world. These threats differ in type, its side effect, its reasons, and its main purposes. This survey presents the most critical threats to cloud computing with its impacts, its reasons, and some suggested solutions. In addition, this survey determines what the main aspects of the cloud and the security attributes that are affected by each one of these threats. As a result of this survey, we order the most critical threats according to the level of its impact.

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“…Their results reflect the effects of problem size, risk attitude, interval size, and additional allocation requirements on solution quality, and they demonstrate connections between optimizing server consolidation and cloud computing service management. We refer interested readers to a comprehensive review that demonstrates the linkage between cloud computing and operations research problems by Iyoob et al (2013).…”

Section: Cloudmentioning

confidence: 99%

Stochastic Modeling and Approaches for Managing Energy Footprints in Cloud Computing Service

Shen

Wang²

2014

Service Science

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I n this paper, we formulate several stochastic optimization models for trading off between energy footprints and quality of service associated with server consolidation in cloud computing data centers. We consider finite service times with uncertain workloads at each period and minimize the expected energy consumption. Decisions include workload scheduling and switching servers on or off based on estimated loads. In models involving backlogging and penalizing unmet demand, we first incorporate zero-delay and zero-work-loss criteria, of which the latter allows backlogging but sets deadlines and penalty cost for all delays. We also formulate alternative chance-constrained programs to ensure that workload delay percentage is within a certain risk tolerance. By assuming scenario-based workload realizations, we solve each model as an mixed-integer program. For the zero-work-loss model, when all servers are homogeneous (i.e., have the same computational efficiency), we provide a heuristic approach. We also consider a benchmark two-stage stochastic program, which involves recourse scheduling decisions and is solved using the Benders decomposition. Numerical results demonstrate the computational efficacy and reduction of energy consumption for certain patterns of workload realizations. In particular, we consider instances generated from a typical daily workload pattern existing in many data centers and provide managerial insights.

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Cloud Computing Operations Research

Cited by 44 publications

References 27 publications

Data-Driven Understanding of Smart Service Systems Through Text Mining

Data-Driven Understanding of Smart Service Systems Through Text Mining

Identifying the Top Threats in Cloud Computing and Its Suggested Solutions: A Survey

Stochastic Modeling and Approaches for Managing Energy Footprints in Cloud Computing Service

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