An Incentive Mechanism for Game-Based QoS-Aware Service Selection

Wang, Puwei; Du, Xiaoyong

doi:10.1007/978-3-642-45005-1_38

“…Thus, there is a challenge for the requester: how can it find the optimal service provider under incomplete information? Wang and Du [10] proposed an approach to find the optimal service providers by predicting their service prices based on only the distribution of provider's price-performance indexes. We thus obtained the usage experiences of requesters for various service providers.…”

Section: Resultsmentioning

confidence: 99%

“…Based on the prediction results, we propose a multi-round Vickrey auction to obtain a solution that satisfy the QoS requirement and the budget restriction. Finally, we conduct a set of evaluations that show that our prediction approach is more effective and efficient than Wang and Du's approach [10].…”

Section: Resultsmentioning

confidence: 99%

“…Wang and Du [10] proposed a twostep method for estimating the minimum price for a desired QoS. First, they introduce the price-performance index to describe a service provider's capability to offer the minimum price for a desired QoS.…”

Section: Problem Analysismentioning

confidence: 99%

“…Hence, there is an incomplete information game for QoS-aware service selection, thereby suggesting the need for predicting the minimum service prices of service providers Wang and Du [10] proposed an iterative approach based on the predictions of the minimum prices of the service providers. Figure 1 Figure 1.…”

Section: Incomplete Information Gamementioning

confidence: 99%

“…Thus, we need an effective and efficient approach for a service requester to predict providers' minimum service prices given its QoS requirements, thereby finding the optimal service providers. Wang and Du [10] proposed an approach to estimate the minimum service price from a lower value to a higher value for each task, until the service requester and one of the service providers agree about the QoS desired by the requester and the service price demanded by the service provider. Adopting Wang and Du's approach, we can obtain the past usage experience records including QoS, the predictions of providers' minimum service prices, and so on.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Predicting Service Price for Game-Theoretic Qos-Aware Service Selection

Wang¹,

Anup²,

Munindar³

2016

STSC

Self Cite

2

0

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In QoS-aware service selection, a service requester seeks to maximize his utility by selecting service providers that charges the lowest service prices while meeting the requester's global QoS requirements. In existing selection approaches, a service requester focuses on finding providers based on their QoS and thereby ignores their service prices that could change with their QoS. High QoS may provide more benefits, but may require a high service price. As a result, the highest QoS may not produce the maximum utility. A service requester and service providers have a conflicting interest over service prices. We model the process of QoS-aware service selection as a price competition game. In the case where the providers' minimum prices are public knowledge, we propose an approach to compute a ε-Nash equilibrium that maximizes the service requester's utility. However, in general, a service provider would not reveal its minimum acceptable price. Thus, it is important for a service requester to predict the minimum price for a service that meets its QoS requirements. We propose a collaborative approach to predicting a provider's minimum price for a desired QoS based on prior usage experiences. Based on the prediction results of the service providers' minimum prices, we propose a multi-round mechanism where the service requester chooses a service for each task by using a Vickrey auction with reserve price. The experimental results show our approach can find the optimal service providers efficiently and effectively.

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A Collaborative Approach to Predicting Service Price for QoS-Aware Service Selection

Wang

¹

,

Kalia

²

,

Singh

³

2015

2015 IEEE International Conference on Web Services

View full text Add to dashboard Cite

In QoS-aware service selection, a service requester seeks to maximize his utility by selecting service providers that charges the lowest service prices while meeting the requester's global QoS requirements. In existing selection approaches, a service requester focuses on finding providers based on their QoS and thereby ignores their service prices that could change with their QoS. High QoS may provide more benefits, but may require a high service price. As a result, the highest QoS may not produce the maximum utility. A service requester and service providers have a conflicting interest over service prices. We model the process of QoS-aware service selection as a price competition game. In the case where the providers' minimum prices are public knowledge, we propose an approach to compute a ε-Nash equilibrium that maximizes the service requester's utility. However, in general, a service provider would not reveal its minimum acceptable price. Thus, it is important for a service requester to predict the minimum price for a service that meets its QoS requirements. We propose a collaborative approach to predicting a provider's minimum price for a desired QoS based on prior usage experiences. Based on the prediction results of the service providers' minimum prices, we propose a multi-round mechanism where the service requester chooses a service for each task by using a Vickrey auction with reserve price. The experimental results show our approach can find the optimal service providers efficiently and effectively.

show abstract