arXiv subjects

Jianwei Huang

Publications and source records attributed to Jianwei Huang.

At least 163 records · Page 9Linked to original sources

arXiv2015

Spectrum Reservation Contract Design in TV White Space Networks

In this paper, we study a broker-based TV white space market, where unlicensed white space devices (WSDs) purchase white space spectrum from TV licensees via a third-party geo-location database (DB), which serves as a spectrum broker, reserving spectrum from TV licensees and then reselling the reserved spectrum to WSDs. We propose a contract-theoretic framework for the database's spectrum reservation under demand stochasticity and information asymmetry. In such a framework, the database offers a set of contract items in the form of reservation amount and the corresponding payment, and each WSD chooses the best contract item based on its private information. We systematically study the optimal reservation contract design (that maximizes the database's expected profit) under two different risk-bearing schemes: DB-bearing-risk and WSD-bearing-risk, depending on who (the database or the WSDs) will bear the risk of over reservation. Counter-intuitively, we show that the optimal contract under DB-bearing-risk leads to a higher profit for the database and a higher total network profit.

cs.GT↗

arXiv2015

Proactive Demand Response for Data Centers: A Win-Win Solution

In order to reduce the energy cost of data centers, recent studies suggest distributing computation workload among multiple geographically dispersed data centers, by exploiting the electricity price difference. However, the impact of data center load redistribution on the power grid is not well understood yet. This paper takes the first step towards tackling this important issue, by studying how the power grid can take advantage of the data centers' load distribution proactively for the purpose of power load balancing. We model the interactions between power grid and data centers as a two-stage problem, where the utility company chooses proper pricing mechanisms to balance the electric power load in the first stage, and the data centers seek to minimize their total energy cost by responding to the prices in the second stage. We show that the two-stage problem is a bilevel quadratic program, which is NP-hard and cannot be solved using standard convex optimization techniques. We introduce benchmark problems to derive upper and lower bounds for the solution of the two-stage problem. We further propose a branch and bound algorithm to attain the globally optimal solution, and propose a heuristic algorithm with low computational complexity to obtain an alternative close-to-optimal solution. We also study the impact of background load prediction error using the theoretical framework of robust optimization. The simulation results demonstrate that our proposed scheme can not only improve the power grid reliability but also reduce the energy cost of data centers.

eess.SY↗

arXiv2015

Joint Scheduling and Power Allocations for Traffic Offloading via Dual-Connectivity

With the rapid growth of mobile traffic demand, a promising approach to relieve cellular network congestion is to offload users' traffic to small-cell networks. In this paper, we investigate how the mobile users (MUs) can effectively offload traffic by taking advantage of the capability of dual-connectivity, which enables an MU to simultaneously communicate with a macro base station (BS) and a small-cell access point (AP) via two radio-interfaces. Offloading traffic to the AP usually reduces the MUs' mobile data cost, but often at the expense of suffering increased interferences from other MUs at the same AP. We thus formulate an optimization problem that jointly determines each MU's traffic schedule (between the BS and AP) and power control (between two radio-interfaces). The system objective is to minimize all MUs' total cost, while satisfying each MU's transmit-power constraints through proper interference control. In spite of the non-convexity of the problem, we design both a centralized algorithm and a distributed algorithm to solve the joint optimization problem. Numerical results show that the proposed algorithms can achieve the close-to-optimum results comparing with the ones achieved by the LINGO (a commercial optimization software), but with significantly less computational complexity. The results also show that the proposed adaptive offloading can significantly reduce the MUs' cost, i.e., save more than 75% of the cost without offloading traffic and 65% of the cost with a fixed offloading.

cs.NI↗

arXiv2015

MINE GOLD to Deliver Green Cognitive Communications

Geo-location database-assisted TV white space network reduces the need of energy-intensive processes (such as spectrum sensing), hence can achieve green cognitive communication effectively. The success of such a network relies on a proper business model that provides incentives for all parties involved. In this paper, we propose MINE GOLD (a Model of INformation markEt for GeO-Location Database), which enables databases to sell the spectrum information to unlicensed white space devices (WSDs) for profit. Specifically, we focus on an oligopoly information market with multiple databases, and study the interactions among databases and WSDs using a two-stage hierarchical model. In Stage I, databases compete to sell information to WSDs by optimizing their information prices. In Stage II, each WSD decides whether and from which database to purchase the information, to maximize his benefit of using the TV white space. We first characterize how the WSDs' purchasing behaviors dynamically evolve, and what is the equilibrium point under fixed information prices from the databases. We then analyze how the system parameters and the databases' pricing decisions affect the market equilibrium, and what is the equilibrium of the database price competition. Our numerical results show that, perhaps counter-intuitively, the databases' aggregate revenue is not monotonic with the number of databases. Moreover, numerical results show that a large degree of positive network externality would improve the databases' revenues and the system performance.

cs.NI↗

arXiv2015

Common Electronic Origin of Superconductivity in (Li,Fe)OHFeSe Bulk Superconductor and Single-Layer FeSe/SrTiO3 Films

The mechanism of high temperature superconductivity in the iron-based superconductors remains an outstanding issue in condensed matter physics. The electronic structure, in particular the Fermi surface topology, is considered to play an essential role in dictating the superconductivity. Recent revelation of distinct electronic structure and possible high temperature superconductivity with a transition temperature Tc above 65 K in the single-layer FeSe films grown on the SrTiO3 substrate provides key information on the roles of Fermi surface topology and interface in inducing or enhancing superconductivity. Here we report high resolution angle-resolved photoemission measurement on the electronic structure and superconducting gap of a novel FeSe-based superconductor, (Li0.84Fe0.16)OHFe0.98Se, with a Tc at 41 K. We find that this single-phase bulk superconductor shows remarkably similar electronic behaviors to that of the superconducting single-layer FeSe/SrTiO3 film in terms of Fermi surface topology, band structure and nearly isotropic superconducting gap without nodes. These observations provide significant insights in understanding high temperature superconductivity in the single-layer FeSe/SrTiO3 film in particular, and the mechanism of superconductivity in the iron-based superconductors in general.

cond-mat.supr-con↗

arXiv2015

Electronic Structure and Superconductivity of FeSe-Related Superconductors

The FeSe superconductor and its related systems have attracted much attention in the iron-based superconductors owing to their simple crystal structure and peculiar electronic and physical properties. The bulk FeSe superconductor has a superconducting transition temperature (Tc) of ~8 K; it can be dramatically enhanced to 37 K at high pressure. On the other hand, its cousin system, FeTe, possesses a unique antiferromagnetic ground state but is non-superconducting. Substitution of Se by Te in the FeSe superconductor results in an enhancement of Tc up to 14.5 K and superconductivity can persist over a large composition range in the Fe(Se,Te) system. Intercalation of the FeSe superconductor leads to the discovery of the AxFe2-ySe2 (A=K, Cs and Tl) system that exhibits a Tc higher than 30 K and a unique electronic structure of the superconducting phase. The latest report of possible high temperature superconductivity in the single-layer FeSe/SrTiO3 films with a Tc above 65 K has generated much excitement in the community. This pioneering work opens a door for interface superconductivity to explore for high Tc superconductors. The distinct electronic structure and superconducting gap, layer-dependent behavior and insulator-superconductor transition of the FeSe/SrTiO3 films provide critical information in understanding the superconductivity mechanism of the iron-based superconductors. In this paper, we present a brief review on the investigation of the electronic structure and superconductivity of the FeSe superconductor and related systems, with a particular focus on the FeSe films.

cond-mat.supr-con↗

arXiv2015

Incentive Design and Market Evolution of Mobile User-Provided Networks

An operator-assisted user-provided network (UPN) has the potential to achieve a low cost ubiquitous Internet connectivity, without significantly increasing the network infrastructure investment. In this paper, we consider such a network where the network operator encourages some of her subscribers to operate as mobile Wi-Fi hotspots (hosts), providing Internet connectivity for other subscribers (clients). We formulate the interaction between the operator and mobile users as a two-stage game. In Stage I, the operator determines the usage-based pricing and quota-based incentive mechanism for the data usage. In Stage II, the mobile users make their decisions about whether to be a host, or a client, or not a subscriber at all. We characterize how the users' membership choices will affect each other's payoffs in Stage II, and how the operator optimizes her decision in Stage I to maximize her profit. Our theoretical and numerical results show that the operator's maximum profit increases with the user density under the proposed hybrid pricing mechanism, and the profit gain can be up to 50\% in a dense network comparing with a pricing-only approach with no incentives.

cs.GT↗

arXiv2015

Distributed Time-Sensitive Task Selection in Mobile Crowdsensing

With the rich set of embedded sensors installed in smartphones and the large number of mobile users, we witness the emergence of many innovative commercial mobile crowdsensing applications that combine the power of mobile technology with crowdsourcing to deliver time-sensitive and location-dependent information to their customers. Motivated by these real-world applications, we consider the task selection problem for heterogeneous users with different initial locations, movement costs, movement speeds, and reputation levels. Computing the social surplus maximization task allocation turns out to be an NP-hard problem. Hence we focus on the distributed case, and propose an asynchronous and distributed task selection (ADTS) algorithm to help the users plan their task selections on their own. We prove the convergence of the algorithm, and further characterize the computation time for users' updates in the algorithm. Simulation results suggest that the ADTS scheme achieves the highest Jain's fairness index and coverage comparing with several benchmark algorithms, while yielding similar user payoff to a greedy centralized benchmark. Finally, we illustrate how mobile users coordinate under the ADTS scheme based on some practical movement time data derived from Google Maps.

cs.GT↗

arXiv2015

DAWN: Delay-Aware Wi-Fi Offloading and Network Selection

To accommodate the explosive growth in mobile data traffic, both mobile cellular operators and mobile users are increasingly interested in offloading the traffic from cellular networks to Wi-Fi networks. However, previously proposed offloading schemes mainly focus on reducing the cellular data usage, without paying too much attention on the quality of service (QoS) requirements of the applications. In this paper, we study the Wi-Fi offloading problem with delay-tolerant applications under usage-based pricing. We aim to achieve a good tradeoff between the user's payment and its QoS characterized by the file transfer deadline. We first propose a general Delay-Aware Wi-Fi Offloading and Network Selection (DAWN) algorithm for a general single-user decision scenario. We then analytically establish the sufficient conditions, under which the optimal policy exhibits a threshold structure in terms of both the time and file size. As a result, we propose a monotone DAWN algorithm that approximately solves the general offloading problem, and has a much lower computational complexity comparing to the optimal algorithm. Simulation results show that both the general and monotone DAWN schemes achieve a high probability of completing file transfer under a stringent deadline, and require the lowest payment under a non-stringent deadline as compared with three heuristic schemes.

cs.NI↗

arXiv2014

Pricing for local and global WiFi markets

This paper analyzes two pricing schemes commonly used in WiFi markets: the flat-rate and the usage-based pricing. The flat-rate pricing encourages the maximum usage, while the usage-based pricing can flexibly attract more users especially those with low valuations in mobile Internet access. First, we use theoretical analysis to compare the two schemes and show that for a single provider in a market, as long as the WiFi capacity is abundant, the flat-rate pricing leads to more revenue. Second, we study how a global provider (e.g., Skype) collaborates with this monopolist in each local market to provide a global WiFi service. We formulate {the interactions between the global and local providers as a dynamic game. In Stage I, the global provider bargains with the local provider in each market to determine the global WiFi service price and revenue sharing agreement. In Stage II, local users and travelers choose local or global WiFi services. We analytically show that the global provider prefers to use the usage-based pricing to avoid a severe competition with the local provider. At the equilibrium, the global provider always shares the majority of his revenue with the local provider to incentivize the cooperation. Finally, we analytically study how the interaction changes if the local market has more than one local provider. In this case, the global provider can integrate the coverages of multiple local providers and provide a better service. Compared to the local monopoly case, local market competition enables the global provider to share less revenue with each of the local providers. However, we numerically show that the global provider's revenue could decrease, as he shares his revenue with more providers and can only charge a lower price.

cs.GT↗

arXiv2014

Bargaining-based Mobile Data Offloading

The unprecedented growth of mobile data traffic challenges the performance and economic viability of today's cellular networks, and calls for novel network architectures and communication solutions. Data offloading through third-party WiFi or femtocell access points (APs) can effectively alleviate the cellular network congestion in a low operational and capital expenditure. This solution requires the cooperation and agreement of mobile cellular network operators (MNOs) and AP owners (APOs). In this paper, we model and analyze the interaction among one MNO and multiple APOs (for the amount of MNO's offloading data and the respective APOs' compensations) by using the Nash bargaining theory. Specifically, we introduce a one-to-many bargaining game among the MNO and APOs, and analyze the bargaining solution (game equilibrium) systematically under two different bargaining protocols: (i) sequential bargaining, where the MNO bargains with APOs sequentially, with one APO at a time, in a given order, and (ii) concurrent bargaining, where the MNO bargains with all APOs concurrently. We quantify the benefits for APOs when bargaining sequentially and earlier with the MNO, and the losses for APOs when bargaining concurrently with the MNO. We further study the group bargaining scenario where multiple APOs form a group bargaining with the MNO jointly, and quantify the benefits for APOs when forming such a group. Interesting, our analysis indicates that grouping of APOs not only benefits the APOs in the group, but may also benefit some APOs not in the group. Our results shed light on the economic aspects and the possible outcomes of the MNO/APOs interactions, and can be used as a roadmap for designing policies for this promising data offloading solution.

cs.GT↗

arXiv2014

Spatial Spectrum Access Game

A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mechanisms. In this paper, we propose a framework of spatial spectrum access games on directed interference graphs, which can model quite general interference relationship with spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any spatial spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the spatial spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the spatial spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any spatial spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to superior performance improvement over a random access algorithm.

cs.NI↗

arXiv2014

Imitation-based Social Spectrum Sharing

Dynamic spectrum sharing is a promising technology for improving the spectrum utilization. In this paper, we study how secondary users can share the spectrum in a distributed fashion based on social imitations. The imitation-based mechanism leverages the social intelligence of the secondary user crowd and only requires a low computational power for each individual user. We introduce the information sharing graph to model the social information sharing relationship among the secondary users. We propose an imitative spectrum access mechanism on a general information sharing graph such that each secondary user first estimates its expected throughput based on local observations, and then imitates the channel selection of another neighboring user who achieves a higher throughput. We show that the imitative spectrum access mechanism converges to an imitation equilibrium, where no beneficial imitation can be further carried out on the time average. Numerical results show that the imitative spectrum access mechanism can achieve efficient spectrum utilization and meanwhile provide good fairness across secondary users.

cs.NI↗

arXiv2014

Motivating Smartphone Collaboration in Data Acquisition and Distributed Computing

This paper analyzes and compares different incentive mechanisms for a master to motivate the collaboration of smartphone users on both data acquisition and distributed computing applications. To collect massive sensitive data from users, we propose a reward-based collaboration mechanism, where the master announces a total reward to be shared among collaborators, and the collaboration is successful if there are enough users wanting to collaborate. We show that if the master knows the users' collaboration costs, then he can choose to involve only users with the lowest costs. However, without knowing users' private information, then he needs to offer a larger total reward to attract enough collaborators. Users will benefit from knowing their costs before the data acquisition. Perhaps surprisingly, the master may benefit as the variance of users' cost distribution increases. To utilize smartphones' computation resources to solve complex computing problems, we study how the master can design an optimal contract by specifying different task-reward combinations for different user types. Under complete information, we show that the master involves a user type as long as the master's preference characteristic outweighs that type's unit cost. All collaborators achieve a zero payoff in this case. If the master does not know users' private cost information, however, he will conservatively target at a smaller group of users with small costs, and has to give most benefits to the collaborators.

cs.GT↗

arXiv2013

Fermi Surface and Band Structure of (Ca,La)FeAs2 Superconductor from Angle-Resolved Photoemission Spectroscopy

The (Ca,R)FeAs2 (R=La,Pr and etc.) superconductors with a signature of superconductivity transition above 40 K possess a new kind of block layers that consist of zig-zag As chains. In this paper, we report the electronic structure of the new (Ca,La)FeAs2 superconductor investigated by both band structure calculations and high resolution angle-resolved photoemission spectroscopy measurements. Band structure calculations indicate that there are four hole-like bands around the zone center $Γ$(0,0) and two electron-like bands near the zone corner M(pi,pi) in CaFeAs2. In our angle-resolved photoemission measurements on (Ca0.9La0.1})FeAs2, we have observed three hole-like bands around the Gamma point and one electron-like Fermi surface near the M(pi,pi) point. These results provide important information to compare and contrast with the electronic structure of other iron-based compounds in understanding the superconductivity mechanism in the iron-based superconductors.

cond-mat.supr-con↗

arXiv2013

Quality of Service Games for Spectrum Sharing

Today's wireless networks are increasingly crowded with an explosion of wireless users, who have greater and more diverse quality of service (QoS) demands than ever before. However, the amount of spectrum that can be used to satisfy these demands remains finite. This leads to a great challenge for wireless users to effectively share the spectrum to achieve their QoS requirements. This paper presents a game theoretic model for spectrum sharing, where users seek to satisfy their QoS demands in a distributed fashion. Our spectrum sharing model is quite general, because we allow different wireless channels to provide different QoS, depending upon their channel conditions and how many users are trying to access them. Also, users can be highly heterogeneous, with different QoS demands, depending upon their activities, hardware capabilities, and technology choices. Under such a general setting, we show that it is NP hard to find a spectrum allocation which satisfies the maximum number of users' QoS requirements in a centralized fashion. We also show that allowing users to self-organize through distributed channel selections is a viable alternative to the centralized optimization, because better response updating is guaranteed to reach a pure Nash equilibria in polynomial time. By bounding the price of anarchy, we demonstrate that the worst case pure Nash equilibrium can be close to optimal, when users and channels are not very heterogenous. We also extend our model by considering the frequency spatial reuse, and consider the user interactions as a game upon a graph where players only contend with their neighbors. We prove that better response updating is still guaranteed to reach a pure Nash equilibrium in this more general spatial QoS satisfaction game.

cs.NI↗

arXiv2013

Price Differentiation for Communication Networks

We study the optimal usage-based pricing problem in a resource-constrained network with one profit-maximizing service provider and multiple groups of surplus-maximizing users. With the assumption that the service provider knows the utility function of each user (thus complete information), we find that the complete price differentiation scheme can achieve a large revenue gain (e.g., 50%) compared to no price differentiation, when the total network resource is comparably limited and the high willingness to pay users are minorities. However, the complete price differentiation scheme may lead to a high implementational complexity. To trade off the revenue against the implementational complexity, we further study the partial price differentiation scheme, and design a polynomial-time algorithm that can compute the optimal partial differentiation prices. We also consider the incomplete information case where the service provider does not know which group each user belongs to. We show that it is still possible to realize price differentiation under this scenario, and provide the sufficient and necessary condition under which an incentive compatible differentiation scheme can achieve the same revenue as under complete information.

cs.NI↗

arXiv2013

Complex Networks from Simple Rewrite Systems

Complex networks are all around us, and they can be generated by simple mechanisms. Understanding what kinds of networks can be produced by following simple rules is therefore of great importance. We investigate this issue by studying the dynamics of extremely simple systems where are `writer' moves around a network, and modifies it in a way that depends upon the writer's surroundings. Each vertex in the network has three edges incident upon it, which are colored red, blue and green. This edge coloring is done to provide a way for the writer to orient its movement. We explore the dynamics of a space of 3888 of these `colored trinet automata' systems. We find a large variety of behaviour, ranging from the very simple to the very complex. We also discover simple rules that generate forms which are remarkably similar to a wide range of natural objects. We study our systems using simulations (with appropriate visualization techniques) and analyze selected rules mathematically. We arrive at an empirical classification scheme which reveals a lot about the kinds of dynamics and networks that can be generated by these systems.

cs.SI↗