Pricing under Demand Flexibility and Predictability

Dalkilic, Ozgur; Tadrous, John; Eryılmaz, Atilla; El‐Gamal, Hesham

doi:10.1002/9781118899250.ch4

Cited by 5 publications

(2 citation statements)

References 49 publications

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“…Dynamic pricing approach has gained a considerable amount of attention as a natural means of influencing the users' economic responsiveness to reduce their peak demand [6]. In fact, some network operators outside the USA (such as Orange, MTN and Uninor) have already started using adaptive pricing schemes to mitigate the excessive cost resulting from high bandwidth consumption [7]- [8].…”

Section: Introductionmentioning

confidence: 99%

Towards A Marketplace for Mobile Content: Dynamic Pricing and Proactive Caching

Alotaibi,

Hosny,

Tadrous

et al. 2015

Preprint

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In this work, we investigate the profit maximization problem for a wireless network carrier and the payment minimization for end-users. Motivated by recent findings on proactive resource allocation, we focus on the scenario whereby end-users who are equipped with device-to-device (D2D) communication can harness predictable demand in proactive data contents caching and the possibility of trading their proactive downloads to minimize their expected payments. The carrier, on the other hand, utilizes a dynamic pricing scheme to differentiate between off-peak and peak time prices and applies commissions on each trading process to further maximize its profit. A novel marketplace that is based on risk sharing between end-users is proposed where the tension between carrier and end-users is formulated as a Stackelberg game. The existence and uniqueness of the non-cooperative sub-game Nash equilibrium is shown. Furthermore, we explore the equilibrium points for the case when the D2D is available and when it is not available, and study the impact of the uncertainty of users' future demands on the system's performance. In particular, we compare the new equilibria with the baseline scenario of flat pricing.Despite end-users connectivity with each other, the uncertainty of their future demands, and the freshness of the pre-cached contents, we characterize a new equilibria region which yields to a win-win situation with respect to the baseline equilibrium. We show that end-users' activity patterns can be harnessed to maximize the carrier's profit while minimizing the end-users expected payments.

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Section: Introductionmentioning

confidence: 99%

Towards A Marketplace for Mobile Content: Dynamic Pricing and Proactive Caching

Alotaibi,

Hosny,

Tadrous

et al. 2015

Preprint

View full text Add to dashboard Cite

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“…Smart pricing approach gives users an incentive to change their behaviour as a way to reach flat demands [4]. Adaptive pricing schemes were also discussed in [5] to mitigate the This work is supported by the QNRF grant NPRP 7-923-2-344, and by the NSF grants CNS-WiFiUS-1456806, CCSS-EARS-1444026, and CAREER-CNS-0953515.…”

Section: Introductionmentioning

confidence: 99%

A game theoretic approach to content trading in proactive wireless networks

Alotaibi

Hosny

Gamal

et al. 2015

2015 IEEE International Symposium on Information Theory (ISIT)

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In this paper, the interactions between a wireless network carrier and a set of end-users trading data contents that were downloaded proactively are studied. In particular, we investigate the profit maximization problem for wireless network carrier and payment minimization for end-users. Motivated by recent findings on proactive resource allocation, we focus on the scenario whereby end-users harness their predictable demands and the possibility of being connected together in downloading proactive data and selling them again to minimize their expected payments. The carrier, on the other hand, takes a commission from each trade and utilizes smart pricing schemes to differentiate between off-peak and peak hour prices to spreadout the peak load and maximize its profit. A marketplace based on risk sharing concept is achieved where the tension between carrier and end-users and the competition between end-users themselves is formulated as a Stackelberg game. The existence and uniqueness of the non-cooperative sub-game Nash equilibrium is shown. We compare the new equilibria with the baseline scenario of smart pricing proactive model without trading between users. Despite the uncertainty about future demand, and the freshness of proactively downloaded contents, we characterize new equilibria point that yield to a win-win situation with respect to the baseline equilibrium. We show that users' activity patterns can be harnessed to create a marketplace that will maximize the carrier's profit while users pay less.

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