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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM.RACCES058
Volume:
10 |
4 |
April 2026
Pages:
1--
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
Computer Science & Engineering
Bharathiyar Institute of Engineering for women (Autonomous) Salem, TamilNadu, India
With booming growth of cloud computing industry, computational resources are readily and elastically available to the customers. In order to attract customers with various demands, most Infrastructure-as-a-service (iaas) cloud service providers offer several pricing strategies such as pay as you go, pay less per unit when you use more (so called volume discount), and pay even less when you reserve. The diverse pricing schemes among different iaas service providers or even in the same provider form a complex economic landscape that nurtures the market of cloud brokers. By strategically scheduling multiple customers' resource requests, a cloud broker can fully take advantage of the discounts offered by cloud service providers. In this paper, we focus on how a broker may help a group of customers to fully utilize the volume discount pricing strategy offered by cloud service providers through cost-efficient online resource scheduling. We present a randomized online stack-centric scheduling algorithm (ROSA) and theoretically prove the lower bound of its competitive ratio. Our simulation shows that ROSA achieves a competitive ratio close to the theoretical lower bound under a special case cost function.
KEYWORDS
Cloud computing is an evolving paradigm, where new service providers are frequently coming into existence, offering services of similar functionality. Major challenge for a cloud customer is to select an appropriate service provider from the cloud marketplace to support its business needs. How-ever, service guarantees provided by vendors through SLAs contain ambiguous clauses which makes the job of selecting an ideal provider even more difficult. As customers use cloud services to process and store their individual client’s data, guarantees related to service quality level is of utmost importance. For this purpose, it is imperative from a customer’s perspective to establish trust relationship with a provider. Moreover, as customers are outsourcing their businesses onto a third-party cloud, capability or competence of CSP determines if former’s objectives are going to be accomplished.
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Publication Date
5/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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