The Competitive Effects of Variance-based Pricing

Dierks, Ludwig; Seuken, Sven

doi:10.24963/ijcai.2020/51

Cited by 6 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are also open questions regarding mechanism design in the cloud domain. In subsequent work, Dierks and Seuken (2020) have already analyzed the competitive effects of employing the variance-based payment rule we proposed in this paper in a duopoly model. They find that, in equilibrium, while using a variance-based payment rule weakly increases welfare, the effects on the providers' profits are ambiguous.…”

Section: Discussionmentioning

confidence: 99%

On the Cluster Admission Problem for Cloud Computing

Dierks

Kash²,

Seuken³

2021

jair

Self Cite

View full text Add to dashboard Cite

Cloud computing providers face the problem of matching heterogeneous customer workloads to resources that will serve them. This is particularly challenging if customers, who are already running a job on a cluster, scale their resource usage up and down over time. The provider therefore has to continuously decide whether she can add additional workloads to a given cluster or if doing so would impact existing workloads’ ability to scale. Currently, this is often done using simple threshold policies to reserve large parts of each cluster, which leads to low efficiency (i.e., low average utilization of the cluster). We propose more sophisticated policies for controlling admission to a cluster and demonstrate that they significantly increase cluster utilization. We first introduce the cluster admission problem and formalize it as a constrained Partially Observable Markov Decision Process (POMDP). As it is infeasible to solve the POMDP optimally, we then systematically design admission policies that estimate moments of each workload’s distribution of future resource usage. Via extensive simulations grounded in a trace from Microsoft Azure, we show that our admission policies lead to a substantial improvement over the simple threshold policy. We then show that substantial further gains are possible if high-quality information is available about arriving workloads. Based on this, we propose an information elicitation approach to incentivize users to provide this information and simulate its effects.

show abstract

Section: Discussionmentioning

confidence: 99%

On the Cluster Admission Problem for Cloud Computing

Dierks

Kash²,

Seuken³

2021

jair

Self Cite

View full text Add to dashboard Cite

show abstract

“…Dierks and Seuken [11] investigated the interplay between two types of services offered by server providers; i.e., the main market where computing time is sold at a fixed price and the spot market where the resources left unused by the main market are priced dynamically. The same authors studied in [12] the competition between fixed price-per-unit strategies with respect to type-dependent ones, characterizing the Bayesian Nash Equilibria of a market where different server providers use the two strategies. Kash et al [23] considered the problem faced by a server provider that is willing to periodically adopt new technologies and has to devise a pricing strategy that takes into consideration the switching cost of its clients from the old contract to the new ones.…”

Section: Related Workmentioning

confidence: 99%

Online revenue maximization for server pricing

Boodaghians

Fusco

Leonardi

et al. 2022

Auton Agent Multi-Agent Syst

View full text Add to dashboard Cite

Efficient and truthful mechanisms to price resources on servers/machines have been the subject of much work in recent years due to the importance of the cloud market. This paper considers revenue maximization in the online stochastic setting with non-preemptive jobs and a unit capacity server. One agent/job arrives at every time step, with parameters drawn from the underlying distribution. We design a posted-price mechanism which can be efficiently computed and is revenue-optimal in expectation and in retrospect, up to additive error. The prices are posted prior to learning the agent’s type, and the computed pricing scheme is deterministic, depending only on the length of the allotted time interval and on the earliest time the server is available. We also prove that the proposed pricing strategy is robust to imprecise knowledge of the job distribution and that a distribution learned from polynomially many samples is sufficient to obtain a near-optimal truthful pricing strategy.

show abstract

“…Despite economical basis approaches used in designing the Cloud costing scheme, there are three different pricing methods used (i) pricing for provider's profit, (ii) pricing for user's utility and (iii) equilibrium pricing. In response to the issue in determining the right prices for improving the profit, the variance-based pricing is proposed by the authors in [17]. In their pricing scheme, the providers' competitors have influenced in determining the range of service price.…”

Section: Related Workmentioning

confidence: 99%

Generic Costing Scheme Using General Equilibrium Theory for Fair Cloud Service Charging

2021

KSII TIIS

View full text Add to dashboard Cite

Cloud Service Providers (CSPs) enable their users to access Cloud computing and storage services from anywhere in quick and flexible manners through the Internet. With the basis of 'pay-as-you-go' model, it makes the interactions between CSPs and the users play a vital role in shaping the Cloud computing market. A pool of virtualized and dynamically scalable Cloud services that delivered on demand to the users is associated with guaranteed performance and cost-provisioning. It needed a costing scheme for determining suitable charges in order to secure lease pricing of the Cloud services. However, it is hard to meet the satisfied prices for both CSPs and users due to their conflicting needs. Furthermore, there is lack of Service Level Agreements (SLAs) that allowing the users to take part into price negotiating process. The users may lose their interest to use Cloud services while reducing CSPs profit. Therefore, this paper proposes a generic costing scheme for Cloud services using General Equilibrium Theory (GET). GET helps to formulate the price function for various services' factors to match with various demands from the users. It is initially determined by identifying the market circumstances that a general equilibrium will be hold and reached. Specifically, there are two procedures of agreement made in response to (i) established equilibrium supply and demand, and (ii) service price formed and constructed in a price range. The SLAs in our costing scheme is integrated to satisfy both CSPs and users' needs while minimizing their conflicts. The price ranging strategy is deliberated to provide prices' options to the users with respect their budget limit. Meanwhile, the CSPs can adaptively charge based on users' preferences without losing their profit. The costing scheme is testable and analyzed in multi-tenant computing environments. The results from our simulation experiments demonstrate that the proposed costing scheme provides better users' satisfaction while fostering fairness pricing in the Cloud market.

show abstract

The Competitive Effects of Variance-based Pricing

Cited by 6 publications

References 6 publications

On the Cluster Admission Problem for Cloud Computing

On the Cluster Admission Problem for Cloud Computing

Online revenue maximization for server pricing

Generic Costing Scheme Using General Equilibrium Theory for Fair Cloud Service Charging

Contact Info

Product

Resources

About