Consensus theory and noncooperative game theory respectively deal with cooperative and noncooperative interactions among multiple players/agents. They provide a natural framework for road pricing design, since each mo...Consensus theory and noncooperative game theory respectively deal with cooperative and noncooperative interactions among multiple players/agents. They provide a natural framework for road pricing design, since each motorist may myopically optimize his or her own utility as a function of road price and collectively communicate with his or her friends and neighbors on traffic situation at the same time. This paper considers the road pricing design by using game theory and consensus theory. For the case where a system supervisor broadcasts information on the overall system to each agent, we present a variant of standard fictitious play called average strategy fictitious play(ASFP) for large-scale repeated congestion games.Only a weighted running average of all other players actions is assumed to be available to each player. The ASFP reduces the burden of both information gathering and information processing for each player. Compared to the joint strategy fictitious play(JSFP) studied in the literature, the updating process of utility functions for each player is avoided. We prove that there exists at least one pure strategy Nash equilibrium for the congestion game under investigation, and the players actions generated by the ASFP with inertia(players reluctance to change their previous actions) converge to a Nash equilibrium almost surely. For the case without broadcasting, a consensus protocol is introduced for individual agents to estimate the percentage of players choosing each resource, and the convergence property of players action profile is still ensured. The results are applied to road pricing design to achieve socially local optimal trip timing. Simulation results are provided based on the real traffic data for the Singapore case study.展开更多
This paper presents a distributed and adaptive fluctuation control scheme for many-to-one routing （FCM） in wireless sensor networks. Unlike well-known topology control schemes, the primary design objective is to red...This paper presents a distributed and adaptive fluctuation control scheme for many-to-one routing （FCM） in wireless sensor networks. Unlike well-known topology control schemes, the primary design objective is to reduce the fluctuation which happens due to overload of sensors in a data collection tree. More specifically, an estimation model of a sensor available capacity based on the number of its neighbors is proposed. In addition, this paper proposes a parent selection mechanism by three-way handshake. With such model and the selection mechanism, it is ensured that the load of a sensor does not exceed its available capacity. Finally, an adaptive maintenance mechanism is proposed to adjust the estimation of a sensor available capacity as the network environment changes. Simulation results demonstrate the effectiveness of the scheme.展开更多
基金Supported by National Research Foundation of Singapore （NRF-CRP8-2011-03） and National Natural Science Foundation of China （61120106011, 61034007, 61203045, 61304045）
文摘Consensus theory and noncooperative game theory respectively deal with cooperative and noncooperative interactions among multiple players/agents. They provide a natural framework for road pricing design, since each motorist may myopically optimize his or her own utility as a function of road price and collectively communicate with his or her friends and neighbors on traffic situation at the same time. This paper considers the road pricing design by using game theory and consensus theory. For the case where a system supervisor broadcasts information on the overall system to each agent, we present a variant of standard fictitious play called average strategy fictitious play(ASFP) for large-scale repeated congestion games.Only a weighted running average of all other players actions is assumed to be available to each player. The ASFP reduces the burden of both information gathering and information processing for each player. Compared to the joint strategy fictitious play(JSFP) studied in the literature, the updating process of utility functions for each player is avoided. We prove that there exists at least one pure strategy Nash equilibrium for the congestion game under investigation, and the players actions generated by the ASFP with inertia(players reluctance to change their previous actions) converge to a Nash equilibrium almost surely. For the case without broadcasting, a consensus protocol is introduced for individual agents to estimate the percentage of players choosing each resource, and the convergence property of players action profile is still ensured. The results are applied to road pricing design to achieve socially local optimal trip timing. Simulation results are provided based on the real traffic data for the Singapore case study.
文摘This paper presents a distributed and adaptive fluctuation control scheme for many-to-one routing （FCM） in wireless sensor networks. Unlike well-known topology control schemes, the primary design objective is to reduce the fluctuation which happens due to overload of sensors in a data collection tree. More specifically, an estimation model of a sensor available capacity based on the number of its neighbors is proposed. In addition, this paper proposes a parent selection mechanism by three-way handshake. With such model and the selection mechanism, it is ensured that the load of a sensor does not exceed its available capacity. Finally, an adaptive maintenance mechanism is proposed to adjust the estimation of a sensor available capacity as the network environment changes. Simulation results demonstrate the effectiveness of the scheme.
