Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication

Device-to-device (D2D) communication underlaying cellular networks allows mobile devices such as smartphones and tablets to use the licensed spectrum allocated to cellular services for direct peer-to-peer transmission. D2D communication can use either one-hop transmission (i.e., in D2D direct communication) or multi-hop cluster-based transmission (i.e., in D2D local area networks). The D2D devices can compete or cooperate with each other to reuse the radio resources in D2D networks. Therefore, resource allocation and access for D2D communication can be treated as games. The theories behind these games provide a variety of mathematical tools to effectively model and analyze the individual or group behaviors of D2D users. In addition, game models can provide distributed solutions to the resource allocation problems for D2D communication. The aim of this article is to demonstrate the applications of game-theoretic models to study the radio resource allocation issues in D2D communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201

Mechanism Design in Social Networks

This paper studies an auction design problem for a seller to sell a commodity in a social network, where each individual (the seller or a buyer) can only communicate with her neighbors. The challenge to the seller is to design a mechanism to incentivize the buyers, who are aware of the auction, to further propagate the information to their neighbors so that more buyers will participate in the auction and hence, the seller will be able to make a higher revenue. We propose a novel auction mechanism, called information diffusion mechanism (IDM), which incentivizes the buyers to not only truthfully report their valuations on the commodity to the seller, but also further propagate the auction information to all their neighbors. In comparison, the direct extension of the well-known Vickrey-Clarke-Groves (VCG) mechanism in social networks can also incentivize the information diffusion, but it will decrease the seller's revenue or even lead to a deficit sometimes. The formalization of the problem has not yet been addressed in the literature of mechanism design and our solution is very significant in the presence of large-scale online social networks.Comment: In The Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, US, 04-09 Feb 201

Use of Devolved Controllers in Data Center Networks

In a data center network, for example, it is quite often to use controllers to manage resources in a centralized man- ner. Centralized control, however, imposes a scalability problem. In this paper, we investigate the use of multiple independent controllers instead of a single omniscient controller to manage resources. Each controller looks after a portion of the network only, but they together cover the whole network. This therefore solves the scalability problem. We use flow allocation as an example to see how this approach can manage the bandwidth use in a distributed manner. The focus is on how to assign components of a network to the controllers so that (1) each controller only need to look after a small part of the network but (2) there is at least one controller that can answer any request. We outline a way to configure the controllers to fulfill these requirements as a proof that the use of devolved controllers is possible. We also discuss several issues related to such implementation.Comment: Appears in INFOCOM 2011 Cloud Computing Worksho

An American Model for the EU Gas Market?

It is generally believed that the American model is not suitable for Europe, yet North America is the only large and working competitive gas market in the world. The paper shows how its model could be adapted as a target for market design within the European institutional framework. It starts from analysis of the main peculiar economic features of the gas transportation industry, which should underpin any efficient model. After the Third Package is properly implemented the EU will share several building blocks of the American model: effective unbundling of transportation and supply; regulated tariffs which, for long distance transportation, are in fact largely related to capacity and distance; investments based mostly on industry’s initiative and resources, and the related decisions are increasingly made after open and public processes. Yet Europe needs to harmonize tariff regulation criteria, which could be achieved through a monitoring process. National separation of main investment decisions should be overcome, possibly by organising a common platform where market forces and public authorities interact with private suppliers to require existing and develop new capacity, whereas industry competitively offers its solutions. Such platform would allow for long term capacity reservation, subject to caps and congestion management provisions. Auctions and possibly market coupling would play an important role in the allocation of short term capacity but a limited one in long term. Market architecture and the organisation of hubs would also be developed mostly by market forces under regulatory oversight. The continental nature of the market suggests a likely concentration of trading in a very limited number of main markets, whereas minor markets would have a limited role and would be connected to major ones, with price differences reflecting transportation costs and market conditions. Excessive interference or pursuit of political goals in less than transparent ways involves the risk of slower liquidity development and higher market fragmentation. With this view as a background, regulatory work aimed at completing the European market should be based on ensuring the viability of interconnections between current markets and on the establishment of common platforms and co-ordinated tariff systems, fostering the conditions for upstream and transportation capacity development.Hubs; infrastructure; target model; network tariffs; gas market design; capacity allocation

Incentive compatible route coordination of crowdsourced resources and its application to GeoPresence-as-a-Service

With the recent trend in crowdsourcing, i.e., using the power of crowds to assist in satisfying demand, the pool of resources suitable for GeoPresen- ce-capable systems has expanded to include already roaming devices, such as mobile phones, and moving vehicles. We envision an environment, in which the motion of these crowdsourced mobile resources is coordinated, according to their preexisting schedules to satisfy geo-temporal demand on a mobility field. In this paper, we propose an incentive compatible route coordination mechanism for crowdsourced resources, in which participating mobile agents satisfy geo-temporal requests in return for monetary rewards. We define the Flexible Route Coordination (FRC) problem, in which an agent's exibility is exploited to maximize the coverage of a mo- bility field, with an objective to maximize the revenue collected from sat- isfied paying requests. Given that the FRC problem is NP-hard, we define an optimal algorithm to plan the route of a single agent on a graph with evolving labels, then we use that algorithm to define a 1 2 -approximation algorithm to solve the problem in its general model, with multiple agents. Moreover, we define an incentive compatible, rational, and cash-positive payment mechanism, which guarantees that an agent's truthfulness about its exibility is an ex-post Nash equilibrium strategy. Finally, we analyze the proposed mechanisms theoretically, and evaluate their performance experimentally using real mobility traces from urban environments.Supported in part by NSF Grants, #1430145, #1414119, #1347522, #1239021, and #1012798

Incentive-compatible route coordination of crowdsourced resources

Technical ReportWith the recent trend in crowdsourcing, i.e., using the power of crowds to assist in satisfying demand, the pool of resources suitable for GeoPresen-ce-capable systems has expanded to include already roaming devices, such as mobile phones, and moving vehicles. We envision an environment, in which the motion of these crowdsourced mobile resources is coordinated, according to their preexisting schedules to satisfy geo-temporal demand on a mobility field. In this paper, we propose an incentive compatible route coordination mechanism for crowdsourced resources, in which participating mobile agents satisfy geo-temporal requests in return for monetary rewards. We define the Flexible Route Coordination (FRC) problem, in which an agent’s flexibility is exploited to maximize the coverage of a mobility field, with an objective to maximize the revenue collected from satisfied paying requests. Given that the FRC problem is NP-hard, we define an optimal algorithm to plan the route of a single agent on a graph with evolving labels, then we use that algorithm to define a 1-approximation algorithm to solve the 2 problem in its general model, with multiple agents. Moreover, we define an incentive compatible, rational, and cash-positive payment mechanism, which guarantees that an agent’s truthfulness about its flexibility is an ex-post Nash equilibrium strategy. Finally, we analyze the proposed mechanisms theoretically, and evaluate their performance experimentally using real mobility traces from urban environments

What’s in it for me? Incentive-compatible route coordination of crowdsourced resources

With the recent trend in crowdsourcing, i.e., using the power of crowds to assist in satisfying demand, the pool of resources suitable for GeoPresence-capable systems has expanded to include already roaming devices, such as mobile phones, and moving vehicles. We envision an environment, in which the motion of these crowdsourced mobile resources is coordinated, according to their preexisting schedules to satisfy geo-temporal demand on a mobility field. In this paper, we propose an incentive compatible route coordination mechanism for crowdsourced resources, in which participating mobile agents satisfy geo-temporal requests in return for monetary rewards. We define the Flexible Route Coordination (FRC) problem, in which an agent’s flexibility is exploited to maximize the coverage of a mobility field, with an objective to maximize the revenue collected from satisfied paying requests. Given that the FRC problem is NP-hard, we define an optimal algorithm to plan the route of a single agent on a graph with evolving labels, then we use that algorithm to define a 1/2-approximation algorithm to solve the problem in its general model, with multiple agents. Moreover, we define an incentive compatible, rational, and cash-positive payment mechanism, which guarantees that an agent’s truthfulness about its flexibility is an ex-post Nash equilibrium strategy. Finally, we analyze the proposed mechanisms theoretically, and evaluate their performance experimentally using real mobility traces from urban environments.Supported in part by NSF Grants, #1430145, #1414119, #1347522, #1239021, and #1012798