Queueing game models for differentiated services

Dube, Parijat; Jain, Rahul

doi:10.1109/gamenets.2009.5137441

Cited by 4 publications

(3 citation statements)

References 27 publications

(25 reference statements)

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“…Afèche and Mendelson [2] extend this to more general waiting costs. Dube and Jain [9] consider a different problem with competing GI/GI/1 priority queues; arriving jobs decide which queue to join. They find conditions for the existence of a Nash equilibrium.…”

Section: Related Workmentioning

confidence: 99%

Fixed and market pricing for cloud services

Abhishek

Kash

Key

2012

2012 Proceedings IEEE INFOCOM Workshops

124

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We study a model of congestible resources, where pricing and scheduling are intertwined. Motivated by the problem of pricing cloud instances, we model a cloud computing service as linked GI/GI/· queuing systems where the provider chooses to offer a fixed pricing service, a dynamic market based service, or a hybrid of both, where jobs can be preempted in the market-based service. Users (jobs), who are heterogeneous in both the value they place on service and their cost for waiting, then choose between the services offered. Combining insights from auction theory with queuing theory we are able to characterize user equilibrium behavior, and show its insensitivity to the precise market design mechanism used. We then provide theoretical and simulation based evidence suggesting that a fixed price typically, though not always, generates a higher expected revenue than the hybrid system for the provider.

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Section: Related Workmentioning

confidence: 99%

Fixed and market pricing for cloud services

Abhishek

Kash

Key

2012

2012 Proceedings IEEE INFOCOM Workshops

124

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“…None of these contributions however has considered queuing dynamics. Game theory has been also applied to wireless networks for queueing analysis [19], [35]- [38]. For example, the work in [35] formulated a multi-class queueing game to study differentiated services; in [36], the authors studied throughput-delay tradeoffs by formulating a M/M/1 queueing game; a dynamic pricing game for uplink wireless random access was introduced in [37]; and [38] formulated the problem of energy management in "sparse" distributed aloha networks as a stochastic evolutionary game.…”

Section: Related Workmentioning

confidence: 99%

To Transmit or Not to Transmit? Distributed Queueing Games in Infrastructureless Wireless Networks

Guan

Melodia

Scutari

2016

IEEE/ACM Trans. Networking

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We study distributed queueing games in interference-limited wireless networks. We formulate the throughput maximization problem via distributed selection of users' transmission thresholds as a Nash Equilibrium Problem (NEP). We first focus on the solution analysis of the NEP and derive sufficient conditions for the existence and uniqueness of a Nash Equilibrium (NE). Then, we develop a general best-response-based algorithmic framework wherein the users can explicitly choose the degree of desired cooperation and signaling, converging to different types of solutions, namely: 1) a NE of the NEP when there is no cooperation among users and 2) a stationary point of the Network Utility Maximization (NUM) problem associated with the NEP, when some cooperation among the users in the form of (pricing) message passing is allowed. Finally, as a benchmark, we design a globally optimal but centralized solution method for the nonconvex NUM problem. Our experiments show that in many scenarios the sum-throughput at the NE of the NEP is very close to the global optimum of the NUM problem, which validates our noncooperative and distributed approach. When the gap of the NE from the global optimality is non negligible (e.g., in the presence of "high" coupling among users), exploiting cooperation among the users in the form of pricing enhances the system performance.Index Terms-Decentralized control, interference limited wireless networks, queueing games, successive convex approximation..

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“…Although technological developments have enabled Internet service providers (ISPs) to provide different services for different types of users, this idea is not yet realised [1]. Currently, ISPs only offer services with predefined user's maximum rate or traffic [2].…”

Section: Introductionmentioning

confidence: 99%

Analytic model for network resource management between ISPs and users

Lolaee

Akhaee

2017

IET Networks

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Fixed Communication Provider (FCP) is a consortium of Internet Service Providers (ISPs) which users can switch easily and freely between their ISPs. In order to increase the QoS of the ISPs, we propose a two class service model as the following. ISPs divide their available bandwidth into two parts to provide their end users with optimal services. One dedicated to primary users, and the other for secondary users. Primary users are those who pay more and thus, expect dedicated bandwidth that is always available. Secondary services are provided by ISPs for the other users who cannot afford the dedicated bandwidth. In this study, by defining the utility functions for both user types, we aim at dividing the ISP bandwidth between these two services such that the utility function of the users is maximized. Since the primary users do not always use the maximum bandwidth, an algorithm is proposed for ISPs to estimate the primary users' required bandwidth in each time segment based on the previous segments. Based on this estimate, the expected bandwidth is dedicated to the primary users, and the remaining bandwidth is devoted to the secondary users to improve the Quality of Service (QoS). On the other hand, an ISP is penalized if it fails to provide the primary users with the required bandwidth mentioned in their contract. Therefore, there exists a trade-off between the conservative estimation of the primary users' rate, QoS of the secondary users and the achieved utility of the ISPs.keywords: Network analysis, Network management, Quality of service (QoS).

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Queueing game models for differentiated services

Cited by 4 publications

References 27 publications

Fixed and market pricing for cloud services

Fixed and market pricing for cloud services

To Transmit or Not to Transmit? Distributed Queueing Games in Infrastructureless Wireless Networks

Analytic model for network resource management between ISPs and users

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