Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2661118
Julio A. Corchado, J. A. Cortés, F. Cañete, L. Díez
This note corrects a recurrent erratum in Section VII of our paper “An MTL-based channel model for indoor broadband mimo power line communications” [1]. Errors are concerned with the quantification of the spatial correlation of MIMO channels by means of the condition number of the channel matrix. According to the definition given in expression (25) of the paper, the higher the condition number, the higher the spatial correlation. However, Section VII is written as if high condition numbers correspond to low spatially correlated channels. Hence, whenever it is said that a given fact reduces the spatial correlation or, equivalently, that it yields lower spatially correlated channels, it should say exactly the opposite, i.e, the referred fact increases the spatial correlation or yields higher spatially correlated channels; and vice versa.
{"title":"Correction to “An MTL-Based Channel Model for Indoor Broadband MIMO Power Line Communications”","authors":"Julio A. Corchado, J. A. Cortés, F. Cañete, L. Díez","doi":"10.1109/JSAC.2017.2661118","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2661118","url":null,"abstract":"This note corrects a recurrent erratum in Section VII of our paper “An MTL-based channel model for indoor broadband mimo power line communications” [1]. Errors are concerned with the quantification of the spatial correlation of MIMO channels by means of the condition number of the channel matrix. According to the definition given in expression (25) of the paper, the higher the condition number, the higher the spatial correlation. However, Section VII is written as if high condition numbers correspond to low spatially correlated channels. Hence, whenever it is said that a given fact reduces the spatial correlation or, equivalently, that it yields lower spatially correlated channels, it should say exactly the opposite, i.e, the referred fact increases the spatial correlation or yields higher spatially correlated channels; and vice versa.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"521-521"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2661118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46451139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659318
Junting Chen, Wenhan Dai, Yuan Shen, V. Lau, M. Win
Resource management in the power and time–frequency domains is an important issue in distributed network localization. Since highly accurate ranging requires a large amount of time–frequency resources, cooperation among nodes without proper link selection may not be feasible. To address this issue, two resource management games are formulated, and Stackelberg equilibrium and link bargaining equilibrium are proposed as the solution concepts for efficient link selection and power allocation. Distributed algorithms are derived and analyzed using game theoretical approaches. It is demonstrated that the proposed strategies can achieve a lower mean squared error of position estimation with fewer ranging measurements.
{"title":"Resource Management Games for Distributed Network Localization","authors":"Junting Chen, Wenhan Dai, Yuan Shen, V. Lau, M. Win","doi":"10.1109/JSAC.2017.2659318","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659318","url":null,"abstract":"Resource management in the power and time–frequency domains is an important issue in distributed network localization. Since highly accurate ranging requires a large amount of time–frequency resources, cooperation among nodes without proper link selection may not be feasible. To address this issue, two resource management games are formulated, and Stackelberg equilibrium and link bargaining equilibrium are proposed as the solution concepts for efficient link selection and power allocation. Distributed algorithms are derived and analyzed using game theoretical approaches. It is demonstrated that the proposed strategies can achieve a lower mean squared error of position estimation with fewer ranging measurements.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"317-329"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43097207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2683048
L. Sanguinetti, T. Alpcan, T. Başar, M. Bennis, R. Berry, Jianwei Huang, W. Saad
Next-generation networks will be characterized by three key features: heterogeneity , in terms of technologies and services, dynamics , in terms of rapidly varying environments and uncertainty, and size , in terms of the numbers of users, nodes, and services. The emergence of such large-scale and decentralized heterogeneous networks operating under dynamic and uncertain environments imposes new challenges in the design, analysis, and optimization of networks. The past decade has witnessed a confluence among the disciplines of networks, games, and economics, which has necessitated novel mathematical tools and designs that can truly remove the boundaries between these disciplines. In this context, advancing game-theoretic models and tailoring them towards the optimization and operation of future networked systems become pressing needs for our research community. The main goal of this IEEE JSAC Special Issue on “Game Theory for Networks” is to collect cutting-edge contributions that address and show the latest developments in game-theoretic models for emerging networking applications. The response of the community to the call has been overwhelming. We received a total of 120 submissions. We want to thank all the authors who submitted their works to this Special Issue. After a strict and selective review process, we accepted 40 papers and decided to publish two issues. Papers were selected based on their appropriateness for and relevance to the Special Issue as well as their technical merits. Unfortunately, a number of interesting papers did not make the cut because of the criteria set forth above and also due to the constraints on the total page count in a JSAC Special Issue. We hope that such interesting papers will find other venues for publication.
{"title":"Guest Editorial Game Theory for Networks, Part I","authors":"L. Sanguinetti, T. Alpcan, T. Başar, M. Bennis, R. Berry, Jianwei Huang, W. Saad","doi":"10.1109/JSAC.2017.2683048","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2683048","url":null,"abstract":"Next-generation networks will be characterized by three key features: heterogeneity , in terms of technologies and services, dynamics , in terms of rapidly varying environments and uncertainty, and size , in terms of the numbers of users, nodes, and services. The emergence of such large-scale and decentralized heterogeneous networks operating under dynamic and uncertain environments imposes new challenges in the design, analysis, and optimization of networks. The past decade has witnessed a confluence among the disciplines of networks, games, and economics, which has necessitated novel mathematical tools and designs that can truly remove the boundaries between these disciplines. In this context, advancing game-theoretic models and tailoring them towards the optimization and operation of future networked systems become pressing needs for our research community. The main goal of this IEEE JSAC Special Issue on “Game Theory for Networks” is to collect cutting-edge contributions that address and show the latest developments in game-theoretic models for emerging networking applications. The response of the community to the call has been overwhelming. We received a total of 120 submissions. We want to thank all the authors who submitted their works to this Special Issue. After a strict and selective review process, we accepted 40 papers and decided to publish two issues. Papers were selected based on their appropriateness for and relevance to the Special Issue as well as their technical merits. Unfortunately, a number of interesting papers did not make the cut because of the criteria set forth above and also due to the constraints on the total page count in a JSAC Special Issue. We hope that such interesting papers will find other venues for publication.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"81 1","pages":"245-248"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72918778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659229
Xiang Zhang, G. Xue, Ruozhou Yu, Dejun Yang, Jian Tang
The proliferation of crowdsourcing brings both opportunities and challenges in various fields, such as environmental monitoring, healthcare, and so on. Often, the collaborative efforts from a large crowd of users are needed in order to complete crowdsourcing jobs. In recent years, the design of crowdsourcing incentive mechanisms has drawn much interest from the research community, where auction is one of the commonly adopted mechanisms. However, few of these auctions consider the robustness against false-name attacks (a.k.a. sybil attacks), where dishonest users generate fake identities to increase their utilities without devoting more efforts. To provide countermeasures against such attacks, we have designed a Truthful Auction with countermeasures against False-name Attacks (TAFA) as an auction-based incentive mechanism for crowdsourcing. We prove that TAFA is truthful, individually rational, budget-balanced, and computationally efficient. We also prove that TAFA provides countermeasures against false-name attacks, such that each user is better off not generating any false name. Extensive performance evaluations are conducted and the results further confirm our theoretical analysis.
{"title":"Countermeasures Against False-Name Attacks on Truthful Incentive Mechanisms for Crowdsourcing","authors":"Xiang Zhang, G. Xue, Ruozhou Yu, Dejun Yang, Jian Tang","doi":"10.1109/JSAC.2017.2659229","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659229","url":null,"abstract":"The proliferation of crowdsourcing brings both opportunities and challenges in various fields, such as environmental monitoring, healthcare, and so on. Often, the collaborative efforts from a large crowd of users are needed in order to complete crowdsourcing jobs. In recent years, the design of crowdsourcing incentive mechanisms has drawn much interest from the research community, where auction is one of the commonly adopted mechanisms. However, few of these auctions consider the robustness against false-name attacks (a.k.a. sybil attacks), where dishonest users generate fake identities to increase their utilities without devoting more efforts. To provide countermeasures against such attacks, we have designed a Truthful Auction with countermeasures against False-name Attacks (TAFA) as an auction-based incentive mechanism for crowdsourcing. We prove that TAFA is truthful, individually rational, budget-balanced, and computationally efficient. We also prove that TAFA provides countermeasures against false-name attacks, such that each user is better off not generating any false name. Extensive performance evaluations are conducted and the results further confirm our theoretical analysis.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"478-485"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659229","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47305246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659259
Xiaoxi Zhang, Zhiyi Huang, Chuan Wu, Zongpeng Li, F. Lau
With the recent advent of network functions virtualization (NFV), enterprises and businesses are looking into network service provisioning through the service chains of virtual network functions (VNFs), instead of relying on dedicated hardware middleboxes. Accompanying this trend, an NFV market is emerging, where NFV service providers create VNF instances, assemble VNF service chains, and sell them for the use of customers, using resources (computing, bandwidth) that they own or rent from other resource suppliers. Efficient service chain provisioning and pricing mechanisms are still missing, to charge assembled service chains according to demand and the supply of resources at any time. We propose an online stochastic auction mechanism for on-demand service chain provisioning and pricing at an NFV provider. Our auction takes in buy bids for service chains from multiple customers and sell bids from various resource suppliers to supplement the NFV provider’s geo-distributed resource pool, with resource occupation/contribution durations. We extend online primal-dual optimization framework for handling both buyers and sellers, with a new competitive analysis. The online mechanism maximizes the expected social welfare of the NFV ecosystem (the NFV provider, customers and resource suppliers) with a good competitive ratio as compared with the expected offline optimal social welfare, while guaranteeing truthfulness in bidding, individual rationality for both buyers and sellers, and polynomial time for computation. We evaluate our mechanism through trace-driven simulation studies, and demonstrate a close-to-offline-optimal performance in expected social welfare under realistic settings.
{"title":"Online Stochastic Buy-Sell Mechanism for VNF Chains in the NFV Market","authors":"Xiaoxi Zhang, Zhiyi Huang, Chuan Wu, Zongpeng Li, F. Lau","doi":"10.1109/JSAC.2017.2659259","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659259","url":null,"abstract":"With the recent advent of network functions virtualization (NFV), enterprises and businesses are looking into network service provisioning through the service chains of virtual network functions (VNFs), instead of relying on dedicated hardware middleboxes. Accompanying this trend, an NFV market is emerging, where NFV service providers create VNF instances, assemble VNF service chains, and sell them for the use of customers, using resources (computing, bandwidth) that they own or rent from other resource suppliers. Efficient service chain provisioning and pricing mechanisms are still missing, to charge assembled service chains according to demand and the supply of resources at any time. We propose an online stochastic auction mechanism for on-demand service chain provisioning and pricing at an NFV provider. Our auction takes in buy bids for service chains from multiple customers and sell bids from various resource suppliers to supplement the NFV provider’s geo-distributed resource pool, with resource occupation/contribution durations. We extend online primal-dual optimization framework for handling both buyers and sellers, with a new competitive analysis. The online mechanism maximizes the expected social welfare of the NFV ecosystem (the NFV provider, customers and resource suppliers) with a good competitive ratio as compared with the expected offline optimal social welfare, while guaranteeing truthfulness in bidding, individual rationality for both buyers and sellers, and polynomial time for computation. We evaluate our mechanism through trace-driven simulation studies, and demonstrate a close-to-offline-optimal performance in expected social welfare under realistic settings.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"392-406"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659259","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45479927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659061
Abhinav Sinha, A. Anastasopoulos
Mechanism design for incentivizing strategic agents to maximize their sum of utilities (SoU) is a well-studied problem in the context of resource allocation in networks. There are, however, a number of network resource allocation problems of interest where a designer may have a different objective than maximization of the SoU. The obvious reason for seeking a different objective is that this notion of efficiency does not account for fairness of allocation. A second, more subtle, reason for demanding fairer allocation is that it indirectly implies less variation in taxes paid by agents. This is desirable in a situation where implicit individual agent budgetary constraints make payment of large taxes unrealistic. In this paper, we study a family of social utilities that provide fair allocation (with SoU being subsumed as an extreme case) and derive conditions under which Bayesian and dominant strategy implementation is possible. Furthermore, it is shown how a modification of the above-mentioned mechanism by adding just one message per agent can guarantee full Bayesian implementation, i.e., no extraneous equilibria. We consider the problem of demand-side management in smart grids as a specific motivating application, and through numerical analysis, it is demonstrated that in this application, the proposed method can result in significant gains in fairness of allocation and a reduction in tax variation among agents.
{"title":"Incentive Mechanisms for Fairness Among Strategic Agents","authors":"Abhinav Sinha, A. Anastasopoulos","doi":"10.1109/JSAC.2017.2659061","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659061","url":null,"abstract":"Mechanism design for incentivizing strategic agents to maximize their sum of utilities (SoU) is a well-studied problem in the context of resource allocation in networks. There are, however, a number of network resource allocation problems of interest where a designer may have a different objective than maximization of the SoU. The obvious reason for seeking a different objective is that this notion of efficiency does not account for fairness of allocation. A second, more subtle, reason for demanding fairer allocation is that it indirectly implies less variation in taxes paid by agents. This is desirable in a situation where implicit individual agent budgetary constraints make payment of large taxes unrealistic. In this paper, we study a family of social utilities that provide fair allocation (with SoU being subsumed as an extreme case) and derive conditions under which Bayesian and dominant strategy implementation is possible. Furthermore, it is shown how a modification of the above-mentioned mechanism by adding just one message per agent can guarantee full Bayesian implementation, i.e., no extraneous equilibria. We consider the problem of demand-side management in smart grids as a specific motivating application, and through numerical analysis, it is demonstrated that in this application, the proposed method can result in significant gains in fairness of allocation and a reduction in tax variation among agents.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"288-301"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48067849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In crowdsourcing markets, a requester announces a task and calls for contribution from potential participants. With strategic participants, the requester needs to reward the participants to introduce the incentives of participation. However, it is natural to ask whether it is worth introducing incentives if the total payment for eliciting incentives is too high. This paper addresses such a fundamental concern by designing a frugal mechanism with minimum payment used to procure the total amount of service contributions demanded. We design two mechanisms to provide the incentives of participation while minimizing the payment used by the requester. We first propose a frugal auction-based mechanism, which stimulates participants to truthfully report their information. We theoretically prove that the payment used is not more than the optimal cost (with no incentive considered) plus a bounded additive. We then design a Stackelberg-game-based mechanism, in which the requester fixes a certain total payment at the very beginning so as to encourage the participants to compete for it and participate in the task. We verify the existence of a unique Nash equilibrium (NE) and develop a novel algorithm to find the NE, as well as the optimal payment to extract the NE. Our simulation results show that the payment used in these mechanisms is close to the optimal solution with no incentive considered, while the extra payment caused by introducing truthfulness in auction-based mechanism is about twice that of the NE in Stakelberg-game-based mechanism.
{"title":"Incentive Mechanism Design to Meet Task Criteria in Crowdsourcing: How to Determine Your Budget","authors":"Weiwei Wu, Wanyuan Wang, Minming Li, Jianping Wang, Xiaolin Fang, Yichuan Jiang, Junzhou Luo","doi":"10.1109/JSAC.2017.2659278","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659278","url":null,"abstract":"In crowdsourcing markets, a requester announces a task and calls for contribution from potential participants. With strategic participants, the requester needs to reward the participants to introduce the incentives of participation. However, it is natural to ask whether it is worth introducing incentives if the total payment for eliciting incentives is too high. This paper addresses such a fundamental concern by designing a frugal mechanism with minimum payment used to procure the total amount of service contributions demanded. We design two mechanisms to provide the incentives of participation while minimizing the payment used by the requester. We first propose a frugal auction-based mechanism, which stimulates participants to truthfully report their information. We theoretically prove that the payment used is not more than the optimal cost (with no incentive considered) plus a bounded additive. We then design a Stackelberg-game-based mechanism, in which the requester fixes a certain total payment at the very beginning so as to encourage the participants to compete for it and participate in the task. We verify the existence of a unique Nash equilibrium (NE) and develop a novel algorithm to find the NE, as well as the optimal payment to extract the NE. Our simulation results show that the payment used in these mechanisms is close to the optimal solution with no incentive considered, while the extra payment caused by introducing truthfulness in auction-based mechanism is about twice that of the NE in Stakelberg-game-based mechanism.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"502-516"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659278","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48362611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659258
Zhenzhe Zheng, Yanqing Peng, Fan Wu, Shaojie Tang, Guihai Chen
As a significant business paradigm, data trading has attracted increasing attention. However, the study of data acquisition in data markets is still in its infancy. Mobile crowdsensing has been recognized as an efficient and scalable way to acquire large-scale data. Designing a practical data acquisition scheme for crowd-sensed data markets has to consider three major challenges: crowd-sensed data trading format determination, profit maximization with polynomial computational complexity, and payment minimization in strategic environments. In this paper, we jointly consider these design challenges, and propose VENUS, which is the first profit-driVEN data acqUiSition framework for crowd-sensed data markets. Specifically, VENUS consists of two complementary mechanisms: VENUS-PRO for profit maximization and VENUS-PAY for payment minimization. Given the expected payment for each of the data acquisition points, VENUS-PRO greedily selects the most “cost-efficient” data acquisition points to achieve a sub-optimal profit. To determine the minimum payment for each data acquisition point, we further design VENUS-PAY, which is a data procurement auction in Bayesian setting. Our theoretical analysis shows that VENUS-PAY can achieve both strategy-proofness and optimal expected payment. We evaluate VENUS on a public sensory data set, collected by Intel Research, Berkeley Laboratory. Our evaluation results show that VENUS-PRO approaches the optimal profit, and VENUS-PAY outperforms the canonical second-price reverse auction, in terms of total payment.
{"title":"Trading Data in the Crowd: Profit-Driven Data Acquisition for Mobile Crowdsensing","authors":"Zhenzhe Zheng, Yanqing Peng, Fan Wu, Shaojie Tang, Guihai Chen","doi":"10.1109/JSAC.2017.2659258","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659258","url":null,"abstract":"As a significant business paradigm, data trading has attracted increasing attention. However, the study of data acquisition in data markets is still in its infancy. Mobile crowdsensing has been recognized as an efficient and scalable way to acquire large-scale data. Designing a practical data acquisition scheme for crowd-sensed data markets has to consider three major challenges: crowd-sensed data trading format determination, profit maximization with polynomial computational complexity, and payment minimization in strategic environments. In this paper, we jointly consider these design challenges, and propose VENUS, which is the first profit-driVEN data acqUiSition framework for crowd-sensed data markets. Specifically, VENUS consists of two complementary mechanisms: VENUS-PRO for profit maximization and VENUS-PAY for payment minimization. Given the expected payment for each of the data acquisition points, VENUS-PRO greedily selects the most “cost-efficient” data acquisition points to achieve a sub-optimal profit. To determine the minimum payment for each data acquisition point, we further design VENUS-PAY, which is a data procurement auction in Bayesian setting. Our theoretical analysis shows that VENUS-PAY can achieve both strategy-proofness and optimal expected payment. We evaluate VENUS on a public sensory data set, collected by Intel Research, Berkeley Laboratory. Our evaluation results show that VENUS-PRO approaches the optimal profit, and VENUS-PAY outperforms the canonical second-price reverse auction, in terms of total payment.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"486-501"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42786360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659558
M. Hajiesmaili, Lei Deng, Minghua Chen, Zongpeng Li
The device-to-device load balancing (D2D-LB) paradigm has been advocated in recent small-cell architecture design for cellular networks. The idea is to exploit inter-cell D2D communication and dynamically relay traffic of a busy cell to adjacent under-utilized cells to improve spectrum temporal efficiency, addressing a fundamental drawback of small-cell architecture. Technical challenges of D2D-LB have been studied in previous works. The potential of D2D-LB, however, cannot be fully realized without providing proper incentive mechanism for device participation. In this paper, we address this economical challenge using an online procurement auction framework. In our design, multiple sellers (devices) submit bids to participate in D2D-LB and the auctioneer (cellular service provider) evaluates all the bids and decides to purchase a subset of them to fulfill load balancing requirement with the minimum social cost. Different from similar auction design studies for cellular offloading, battery limit of relaying devices imposes a time-coupled capacity constraint that turns the underlying problem into a challenging multi-slot one. Furthermore, the dynamics in the input to the multi-slot auction problem emphasize the need for online algorithm design. We first tackle the single-slot version of the problem, show that it is NP-hard, and design a polynomial-time offline algorithm with a small approximation ratio. Building upon the single-slot results, we design an online algorithm for the multi-slot problem with sound competitive ratio. Our auction algorithm design ensures that truthful bidding is a dominant strategy for devices. Extensive experiments using real-world traces demonstrate that our proposed solution achieves near offline-optimum and reduces the cost by 45% compared with an alternative heuristic.
{"title":"Incentivizing Device-to-Device Load Balancing for Cellular Networks: An Online Auction Design","authors":"M. Hajiesmaili, Lei Deng, Minghua Chen, Zongpeng Li","doi":"10.1109/JSAC.2017.2659558","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659558","url":null,"abstract":"The device-to-device load balancing (D2D-LB) paradigm has been advocated in recent small-cell architecture design for cellular networks. The idea is to exploit inter-cell D2D communication and dynamically relay traffic of a busy cell to adjacent under-utilized cells to improve spectrum temporal efficiency, addressing a fundamental drawback of small-cell architecture. Technical challenges of D2D-LB have been studied in previous works. The potential of D2D-LB, however, cannot be fully realized without providing proper incentive mechanism for device participation. In this paper, we address this economical challenge using an online procurement auction framework. In our design, multiple sellers (devices) submit bids to participate in D2D-LB and the auctioneer (cellular service provider) evaluates all the bids and decides to purchase a subset of them to fulfill load balancing requirement with the minimum social cost. Different from similar auction design studies for cellular offloading, battery limit of relaying devices imposes a time-coupled capacity constraint that turns the underlying problem into a challenging multi-slot one. Furthermore, the dynamics in the input to the multi-slot auction problem emphasize the need for online algorithm design. We first tackle the single-slot version of the problem, show that it is NP-hard, and design a polynomial-time offline algorithm with a small approximation ratio. Building upon the single-slot results, we design an online algorithm for the multi-slot problem with sound competitive ratio. Our auction algorithm design ensures that truthful bidding is a dominant strategy for devices. Extensive experiments using real-world traces demonstrate that our proposed solution achieves near offline-optimum and reduces the cost by 45% compared with an alternative heuristic.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"265-279"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659558","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44097480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-02-01DOI: 10.1109/JSAC.2017.2659038
Richard T. B. Ma
As the Internet continues to evolve, traditional peering agreements cannot accommodate the changing market conditions. Premium peering has emerged where access providers (APs) charge content providers (CPs) for premium services beyond best-effort connectivity. Although prioritized peering raises concerns about net neutrality, the U.S. FCC exempted peering agreements from its recent ruling, as it falls short of background in the Internet peering context. In this paper, we consider the premium peering options provided by APs and study whether CPs will choose to peer. Based on a novel choice model of complementary services, we characterize the market shares and utilities of the providers under various peering decisions and identify the value of premium peering for the CPs that fundamentally determine CPs’ peering decisions. We find that high-value CPs have peer pressure when low-value CPs peer; however, low-value CPs behave oppositely. The peering decisions of the high-value and low-value CPs are substantially influenced by their baseline market shares and user stickiness, respectively, but not vice versa.
{"title":"Pay or Perish: The Economics of Premium Peering","authors":"Richard T. B. Ma","doi":"10.1109/JSAC.2017.2659038","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659038","url":null,"abstract":"As the Internet continues to evolve, traditional peering agreements cannot accommodate the changing market conditions. Premium peering has emerged where access providers (APs) charge content providers (CPs) for premium services beyond best-effort connectivity. Although prioritized peering raises concerns about net neutrality, the U.S. FCC exempted peering agreements from its recent ruling, as it falls short of background in the Internet peering context. In this paper, we consider the premium peering options provided by APs and study whether CPs will choose to peer. Based on a novel choice model of complementary services, we characterize the market shares and utilities of the providers under various peering decisions and identify the value of premium peering for the CPs that fundamentally determine CPs’ peering decisions. We find that high-value CPs have peer pressure when low-value CPs peer; however, low-value CPs behave oppositely. The peering decisions of the high-value and low-value CPs are substantially influenced by their baseline market shares and user stickiness, respectively, but not vice versa.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"353-366"},"PeriodicalIF":16.4,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42482406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：