The Experts below are selected from a list of 243231 Experts worldwide ranked by ideXlab platform
Jianwei Huang - One of the best experts on this subject based on the ideXlab platform.
-
Multi-Cap Optimization for Wireless Data Plans with Time Flexibility
IEEE Transactions on Mobile Computing, 2020Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination , i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with Time Flexibility . In this paper, we study the MNO's optimal multi-cap data plans with Time Flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users’ willingness-to-pay (captured by the slopes of users’ indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the Time-flexible data mechanisms increase both the MNO's profit (25 percent on average) and users’ payoffs (8.2 percent on average) under price discrimination.
-
Exploring Time Flexibility in Wireless Data Plans
IEEE Transactions on Mobile Computing, 2019Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:Recently, the mobile network operators (MNOs) are exploring more Time Flexibility with the rollover data plan, which allows the unused data from the previous month to be used in the current month. Motivated by this industry trend, we propose a general framework for designing and optimizing the mobile data plan with Time Flexibility. Such a framework includes the traditional data plan, two existing rollover data plans, and a new credit data plan as special cases. Under this framework, we formulate a monopoly MNO's optimal data plan design as a three-stage Stackelberg game: In Stage I, the MNO decides the data mechanism. In Stage II, the MNO further decides the corresponding data cap, subscription fee, and the per-unit fee. Finally, in Stage III, users make subscription decisions based on their own characteristics. Through backward induction, we analytically characterize the MNO's profit-maximizing data plan and the corresponding users’ subscriptions. Furthermore, we conduct a market survey to estimate the distribution of users’ two-dimensional characteristics, and evaluate the performance of different data mechanisms using the real data. We find that a more Time-flexible data mechanism increases MNO's profit and users’ payoffs, hence improves the social welfare.
-
Multi-Cap Optimization for Wireless Data Plans with Time Flexibility
IEEE Transactions on Mobile Computing, 2019Co-Authors: Zhiyuan Wang, Jianwei HuangAbstract:An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination, i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with Time Flexibility. In this paper, we study the MNO's optimal multi-cap data plans with Time Flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users' willingness-to-pay (captured by the slopes of users' indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the Time-flexible data mechanisms increase both the MNO's profit (25% on average) and users' payoffs (8.2% on average) under price discrimination.
-
economic viability of data trading with rollover
arXiv: Computer Science and Game Theory, 2019Co-Authors: Zhiyua Wang, Li Gao, Jianwei Huang, Iying ShouAbstract:Mobile Network Operators (MNOs) are providing more flexible wireless data services to attract subscribers and increase revenues. For example, the data trading market enables user-Flexibility by allowing users to sell leftover data to or buy extra data from each other. The rollover mechanism enables Time-Flexibility by allowing a user to utilize his own leftover data from the previous month in the current month. In this paper, we investigate the economic viability of offering the data trading market together with the rollover mechanism, to gain a deeper understanding of the interrelationship between the user-Flexibility and the Time-Flexibility. We formulate the interactions between the MNO and mobile users as a multi-slot dynamic game. Specifically, in each Time slot (e.g., every day), the MNO first determines the selling and buying prices with the goal of revenue maximization, then each user decides his trading action (by solving a dynamic programming problem) to maximize his long-term payoff. Due to the availability of monthly data rollover, a user's daily trading decision corresponds to a dynamic programming problem with two Time scales (i.e., day-to-day and month-to-month). Our analysis reveals an optimal trading policy with a target interval structure, specified by a buy-up-to threshold and a sell-down-to threshold in each Time slot. Moreover, we show that the rollover mechanism makes users sell less and buy more data given the same trading prices, hence it increases the total demand while decreasing the total supply in the data trading market. Finally, numerical results based on real-world data unveil that the Time-flexible rollover mechanism plays a positive role in the user-flexible data trading market, increasing the MNO's revenue by 25% and all users' payoff by 17% on average.
-
duopoly competition for mobile data plans with Time Flexibility
arXiv: Computer Science and Game Theory, 2019Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:The growing competition drives the mobile network operators (MNOs) to explore adding Time Flexibility to the traditional data plan, which consists of a monthly subscription fee, a data cap, and a per-unit fee for exceeding the data cap. The rollover data plan, which allows the unused data of the previous month to be used in the current month, provides the subscribers with the Time Flexibility. In this paper, we formulate two MNOs' market competition as a three-stage game, where the MNOs decide their data mechanisms (traditional or rollover) in Stage I and the pricing strategies in Stage II, and then users make their subscription decisions in Stage III. Different from the monopoly market where an MNO always prefers the rollover mechanism over the traditional plan in terms of profit, MNOs may adopt different data mechanisms at an equilibrium. Specifically, the high-QoS MNO would gradually abandon the rollover mechanism as its QoS advantage diminishes. Meanwhile, the low-QoS MNO would progressively upgrade to the rollover mechanism. The numerical results show that the market competition significantly limits MNOs' profits, but both MNOs obtain higher profits with the possible choice of the rollover data plan.
Lin Gao - One of the best experts on this subject based on the ideXlab platform.
-
Multi-Cap Optimization for Wireless Data Plans with Time Flexibility
IEEE Transactions on Mobile Computing, 2020Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination , i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with Time Flexibility . In this paper, we study the MNO's optimal multi-cap data plans with Time Flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users’ willingness-to-pay (captured by the slopes of users’ indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the Time-flexible data mechanisms increase both the MNO's profit (25 percent on average) and users’ payoffs (8.2 percent on average) under price discrimination.
-
Exploring Time Flexibility in Wireless Data Plans
IEEE Transactions on Mobile Computing, 2019Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:Recently, the mobile network operators (MNOs) are exploring more Time Flexibility with the rollover data plan, which allows the unused data from the previous month to be used in the current month. Motivated by this industry trend, we propose a general framework for designing and optimizing the mobile data plan with Time Flexibility. Such a framework includes the traditional data plan, two existing rollover data plans, and a new credit data plan as special cases. Under this framework, we formulate a monopoly MNO's optimal data plan design as a three-stage Stackelberg game: In Stage I, the MNO decides the data mechanism. In Stage II, the MNO further decides the corresponding data cap, subscription fee, and the per-unit fee. Finally, in Stage III, users make subscription decisions based on their own characteristics. Through backward induction, we analytically characterize the MNO's profit-maximizing data plan and the corresponding users’ subscriptions. Furthermore, we conduct a market survey to estimate the distribution of users’ two-dimensional characteristics, and evaluate the performance of different data mechanisms using the real data. We find that a more Time-flexible data mechanism increases MNO's profit and users’ payoffs, hence improves the social welfare.
-
A Novel Mobile Data Contract Design with Time Flexibility
IEEE Transactions on Mobile Computing, 2019Co-Authors: Yi Wei, Tat-ming Lok, Lin GaoAbstract:In conventional mobile data plans, the data is associated with a fixed period (e.g., one month) and the unused data will be cleared at the end of each period. To take advantage of consumers’ heterogeneous demands across different periods and meanwhile to provide more Time Flexibility, some mobile data service providers (SP) have offered data plans with different lengths of period. In this paper, we consider the data plan design problem for a single SP, who provides data plans with different lengths of period for consumers with different characteristics of data demands. We propose a contract-theoretic approach, wherein the SP offers a period-price data plan contract which consists of a set of period and price combinations, indicating the prices for data with different periods. We study the optimal data plan contract designs under two different models: discrete and continuous consumer-type models, depending on whether the consumer type is discrete or continuous. In the former model, each type of consumers are assigned with a specific period-price combination. In the latter model, the consumers are first categorized into a finite number of groups, and each group of consumers (possibly with different types) are assigned with a specific period-price combination. We systematically analyze the incentive compatibility (IC) constraint and individual rationality (IR) constraint, which ensure each consumer to choose the data plan with the period-price combination intended for his type. We further derive the optimal contract that maximizes the SP’s expected profit, meanwhile satisfying the IC and IR constraints of consumers. Our numerical results show that our proposed optimal contract can increase the SP’s profit over 35% comparing with the conventional monthly-period data plan.
-
duopoly competition for mobile data plans with Time Flexibility
arXiv: Computer Science and Game Theory, 2019Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:The growing competition drives the mobile network operators (MNOs) to explore adding Time Flexibility to the traditional data plan, which consists of a monthly subscription fee, a data cap, and a per-unit fee for exceeding the data cap. The rollover data plan, which allows the unused data of the previous month to be used in the current month, provides the subscribers with the Time Flexibility. In this paper, we formulate two MNOs' market competition as a three-stage game, where the MNOs decide their data mechanisms (traditional or rollover) in Stage I and the pricing strategies in Stage II, and then users make their subscription decisions in Stage III. Different from the monopoly market where an MNO always prefers the rollover mechanism over the traditional plan in terms of profit, MNOs may adopt different data mechanisms at an equilibrium. Specifically, the high-QoS MNO would gradually abandon the rollover mechanism as its QoS advantage diminishes. Meanwhile, the low-QoS MNO would progressively upgrade to the rollover mechanism. The numerical results show that the market competition significantly limits MNOs' profits, but both MNOs obtain higher profits with the possible choice of the rollover data plan.
-
A Novel Mobile Data Contract Design with Time Flexibility.
arXiv: Computer Science and Game Theory, 2018Co-Authors: Yi Wei, Tat-ming Lok, Lin GaoAbstract:In conventional mobile data plans, the data is associated with a fixed period (e.g., one month) and the unused data will be cleared at the end of each period. To take advantage of consumers' heterogeneous demands across different periods and meanwhile to provide more Time Flexibility, some mobile data service providers (SP) have offered data plans with different lengths of period. In this paper, we consider the data plan design problem for a single SP, who provides data plans with different lengths of period for consumers with different characteristics of data demands. We propose a contract-theoretic approach, wherein the SP offers a period-price data plan contract which consists of a set of period and price combinations, indicating the prices for data with different periods. We study the optimal data plan contract designs under two different models: discrete and continuous consumer-type models, depending on whether the consumer type is discrete or continuous. In the former model, each type of consumers are assigned with a specific period-price combination. In the latter model, the consumers are first categorized into a finite number of groups, and each group of consumers (possibly with different types) are assigned with a specific period-price combination. We systematically analyze the incentive compatibility (IC) constraint and individual rationality (IR) constraint, which ensure each consumer to choose the data plan with the period-price combination intended for his type. We further derive the optimal contract that maximizes the SP's expected profit, meanwhile satisfying the IC and IR constraints of consumers. Our numerical results show that the proposed optimal contract can increase the SP's profit by 35%, comparing with the conventional fixed monthly-period data plan.
Zhiyuan Wang - One of the best experts on this subject based on the ideXlab platform.
-
Multi-Cap Optimization for Wireless Data Plans with Time Flexibility
IEEE Transactions on Mobile Computing, 2020Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination , i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with Time Flexibility . In this paper, we study the MNO's optimal multi-cap data plans with Time Flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users’ willingness-to-pay (captured by the slopes of users’ indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the Time-flexible data mechanisms increase both the MNO's profit (25 percent on average) and users’ payoffs (8.2 percent on average) under price discrimination.
-
Exploring Time Flexibility in Wireless Data Plans
IEEE Transactions on Mobile Computing, 2019Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:Recently, the mobile network operators (MNOs) are exploring more Time Flexibility with the rollover data plan, which allows the unused data from the previous month to be used in the current month. Motivated by this industry trend, we propose a general framework for designing and optimizing the mobile data plan with Time Flexibility. Such a framework includes the traditional data plan, two existing rollover data plans, and a new credit data plan as special cases. Under this framework, we formulate a monopoly MNO's optimal data plan design as a three-stage Stackelberg game: In Stage I, the MNO decides the data mechanism. In Stage II, the MNO further decides the corresponding data cap, subscription fee, and the per-unit fee. Finally, in Stage III, users make subscription decisions based on their own characteristics. Through backward induction, we analytically characterize the MNO's profit-maximizing data plan and the corresponding users’ subscriptions. Furthermore, we conduct a market survey to estimate the distribution of users’ two-dimensional characteristics, and evaluate the performance of different data mechanisms using the real data. We find that a more Time-flexible data mechanism increases MNO's profit and users’ payoffs, hence improves the social welfare.
-
Multi-Cap Optimization for Wireless Data Plans with Time Flexibility
IEEE Transactions on Mobile Computing, 2019Co-Authors: Zhiyuan Wang, Jianwei HuangAbstract:An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination, i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with Time Flexibility. In this paper, we study the MNO's optimal multi-cap data plans with Time Flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users' willingness-to-pay (captured by the slopes of users' indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the Time-flexible data mechanisms increase both the MNO's profit (25% on average) and users' payoffs (8.2% on average) under price discrimination.
-
duopoly competition for mobile data plans with Time Flexibility
arXiv: Computer Science and Game Theory, 2019Co-Authors: Zhiyuan Wang, Lin Gao, Jianwei HuangAbstract:The growing competition drives the mobile network operators (MNOs) to explore adding Time Flexibility to the traditional data plan, which consists of a monthly subscription fee, a data cap, and a per-unit fee for exceeding the data cap. The rollover data plan, which allows the unused data of the previous month to be used in the current month, provides the subscribers with the Time Flexibility. In this paper, we formulate two MNOs' market competition as a three-stage game, where the MNOs decide their data mechanisms (traditional or rollover) in Stage I and the pricing strategies in Stage II, and then users make their subscription decisions in Stage III. Different from the monopoly market where an MNO always prefers the rollover mechanism over the traditional plan in terms of profit, MNOs may adopt different data mechanisms at an equilibrium. Specifically, the high-QoS MNO would gradually abandon the rollover mechanism as its QoS advantage diminishes. Meanwhile, the low-QoS MNO would progressively upgrade to the rollover mechanism. The numerical results show that the market competition significantly limits MNOs' profits, but both MNOs obtain higher profits with the possible choice of the rollover data plan.
-
multi dimensional contract design for mobile data plan with Time Flexibility
Mobile Ad Hoc Networking and Computing, 2018Co-Authors: Zhiyuan Wang, Jianwei HuangAbstract:Mobile network operators (MNOs) have been offering mobile data plans with different data caps and subscription fees as an effective way of achieving price discrimination and improving revenue. Recently, some MNOs are investigating innovative data plans with Time Flexibility based on the multi-cap scheme. The rollover data plan and the credit data plan are such innovative data plans with Time Flexibility. In this paper, we study how the MNO optimizes its multi-cap data plan with Time Flexibility in the realistic asymmetric information scenario, where each user is associated with multidimensional private information, i.e., the data valuation and the network substitutability. Specifically, we consider a multi-dimensional contract-theoretic approach, and analyze the optimal data caps and the subscription fees design systematically. We find that each user's willingness-to-pay for a particular data cap can be captured by the slope of his indifference curve on the contract plane, and the feasible contract (satisfying the incentive compatibility and individual rationality conditions) will allocate larger data caps for users with higher willingness-to-pay. Furthermore, we conduct a market survey to estimate the statistical distribution of users' private information, and examine the performance of our proposed multi-dimensional contract design using the empirical data. Numerical results further reveal that the optimal contract may provide price discounts (i.e., negative subscription fees) to attract low valuation users to select a small-cap (possibly zero-cap) contract item. A data mechanism with better Time Flexibility brings users higher payoffs and the MNO more profit, hence increases the social welfare.
Aurnab Ghose - One of the best experts on this subject based on the ideXlab platform.
-
camp signaling mediates behavioral Flexibility and consolidation of social status in drosophila aggression
The Journal of Experimental Biology, 2017Co-Authors: Nitin Singh Chouhan, Krithika Mohan, Aurnab GhoseAbstract:ABSTRACT Social rituals, such as male–male aggression in Drosophila , are often stereotyped and the component behavioral patterns modular. The likelihood of transition from one behavioral pattern to another is malleable by experience and confers Flexibility to the behavioral repertoire. Experience-dependent modification of innate aggressive behavior in flies alters fighting strategies during fights and establishes dominant–subordinate relationships. Dominance hierarchies resulting from agonistic encounters are consolidated to longer-lasting, social-status-dependent behavioral modifications, resulting in a robust loser effect. We showed that cAMP dynamics regulated by the calcium–calmodulin-dependent adenylyl cyclase, Rut, and the cAMP phosphodiesterase, Dnc, but not the Amn gene product, in specific neuronal groups of the mushroom body and central complex, mediate behavioral plasticity necessary to establish dominant–subordinate relationships. rut and dnc mutant flies were unable to alter fighting strategies and establish dominance relationships during agonistic interactions. This real-Time Flexibility during a fight was independent of changes in aggression levels. Longer-term consolidation of social status in the form of a loser effect, however, required additional Amn -dependent inputs to cAMP signaling and involved a circuit-level association between the α/β and γ neurons of the mushroom body. Our findings implicate cAMP signaling in mediating the plasticity of behavioral patterns in aggressive behavior and in the generation of a temporally stable memory trace that manifests as a loser effect.
-
camp signaling mediates behavioral Flexibility and consolidation of social status in drosophila aggression
bioRxiv, 2017Co-Authors: Nitin Singh Chouhan, Krithika Mohan, Aurnab GhoseAbstract:ABSTRACT Social rituals, like male-male aggression in Drosophila, are often stereotyped and the component behavioral patterns modular. The likelihood of transition from one behavioral pattern to another is malleable by experience and confers Flexibility to the behavioral repertoire. Experience-dependent modification of innate aggressive behavior in flies alters fighting strategies during fights and establishes dominant-subordinate relationships. Dominance hierarchies resulting from agonistic encounters are consolidated to longer lasting social status-dependent behavioral modifications resulting in a robust loser effect. We show that cyclic adenosine monophosphate (cAMP) dynamics regulated by the calcium/calmodulin-dependent adenylyl cyclase, Rut and the cAMP phosphodiesterase, Dnc but not the Amn gene product, in specific neuronal groups of the mushroom body and central complex, mediate behavioral plasticity necessary to establish dominant- subordinate relationships. rut and dnc mutant flies are unable to alter fighting strategies and establish dominance relationships during agonistic interactions. This real-Time Flexibility during a fight is independent of changes in aggression levels. Longer-term consolidation of social status in the form of a loser effect, however, requires additional Amn-dependent inputs to cAMP signaling and involves a circuit-level association between the α/β and γ neurons of the mushroom body. Our findings implicate cAMP signaling in mediating plasticity of behavioral patterns in aggressive behavior and in the generation of a temporally stable memory trace that manifests as a loser effect. SUMMARY STATEMENT Phasic recruitment of different cAMP signaling modalities in specific neuronal groups lead to the formation of temporally distinct components of learning and memory in fly aggression.
-
distinct camp signaling modalities mediate behavioral Flexibility and consolidation of social status in drosophila aggression
bioRxiv, 2016Co-Authors: Nitin Singh Chouhan, Krithika Mohan, Aurnab GhoseAbstract:Social rituals, like male-male aggression in Drosophila, are often stereotyped and its component behavioral patterns modular. The likelihood of transition from one behavioral pattern to another is malleable by experience and confers Flexibility to the behavioral repertoire. Experiential modification of innate aggressive behavior in flies alters fighting strategies during fights and establishes dominant-subordinate relationships. Dominance hierarchies resulting from agonistic encounters are consolidated to longer lasting social status-dependent behavioral modifications resulting in a robust loser effect. We show that cAMP dynamics regulated by Rut and Dnc but not the neuropeptide Amn, in specific neuronal groups of the mushroom body and central complex, mediate behavioral plasticity necessary to establish dominant-subordinate relationships. rut and dnc mutant flies are unable to alter fighting strategies and establish dominance relationships during agonistic interactions. This real Time Flexibility during a fight is independent of changes in aggression levels. Longer-term consolidation of social status in the form of a loser effect, however, requires additional Amn neuropeptide mediated inputs to cAMP signaling and involves a circuit-level association between the α/β and γ neurons of the mushroom body. Our findings implicate distinct modalities of cAMP signaling in mediating plasticity of behavioral patterns in aggressive behavior and in the generation of a temporally stable memory trace that manifests as a loser effect.
Yi Wei - One of the best experts on this subject based on the ideXlab platform.
-
A Novel Mobile Data Contract Design with Time Flexibility
IEEE Transactions on Mobile Computing, 2019Co-Authors: Yi Wei, Tat-ming Lok, Lin GaoAbstract:In conventional mobile data plans, the data is associated with a fixed period (e.g., one month) and the unused data will be cleared at the end of each period. To take advantage of consumers’ heterogeneous demands across different periods and meanwhile to provide more Time Flexibility, some mobile data service providers (SP) have offered data plans with different lengths of period. In this paper, we consider the data plan design problem for a single SP, who provides data plans with different lengths of period for consumers with different characteristics of data demands. We propose a contract-theoretic approach, wherein the SP offers a period-price data plan contract which consists of a set of period and price combinations, indicating the prices for data with different periods. We study the optimal data plan contract designs under two different models: discrete and continuous consumer-type models, depending on whether the consumer type is discrete or continuous. In the former model, each type of consumers are assigned with a specific period-price combination. In the latter model, the consumers are first categorized into a finite number of groups, and each group of consumers (possibly with different types) are assigned with a specific period-price combination. We systematically analyze the incentive compatibility (IC) constraint and individual rationality (IR) constraint, which ensure each consumer to choose the data plan with the period-price combination intended for his type. We further derive the optimal contract that maximizes the SP’s expected profit, meanwhile satisfying the IC and IR constraints of consumers. Our numerical results show that our proposed optimal contract can increase the SP’s profit over 35% comparing with the conventional monthly-period data plan.
-
A Novel Mobile Data Contract Design with Time Flexibility.
arXiv: Computer Science and Game Theory, 2018Co-Authors: Yi Wei, Tat-ming Lok, Lin GaoAbstract:In conventional mobile data plans, the data is associated with a fixed period (e.g., one month) and the unused data will be cleared at the end of each period. To take advantage of consumers' heterogeneous demands across different periods and meanwhile to provide more Time Flexibility, some mobile data service providers (SP) have offered data plans with different lengths of period. In this paper, we consider the data plan design problem for a single SP, who provides data plans with different lengths of period for consumers with different characteristics of data demands. We propose a contract-theoretic approach, wherein the SP offers a period-price data plan contract which consists of a set of period and price combinations, indicating the prices for data with different periods. We study the optimal data plan contract designs under two different models: discrete and continuous consumer-type models, depending on whether the consumer type is discrete or continuous. In the former model, each type of consumers are assigned with a specific period-price combination. In the latter model, the consumers are first categorized into a finite number of groups, and each group of consumers (possibly with different types) are assigned with a specific period-price combination. We systematically analyze the incentive compatibility (IC) constraint and individual rationality (IR) constraint, which ensure each consumer to choose the data plan with the period-price combination intended for his type. We further derive the optimal contract that maximizes the SP's expected profit, meanwhile satisfying the IC and IR constraints of consumers. Our numerical results show that the proposed optimal contract can increase the SP's profit by 35%, comparing with the conventional fixed monthly-period data plan.