Fairness, Justice and an Individual Basis for Public Policy

Prior models of the policy process have examined how human characteristics can affect policy decision-making in such a way that it leads to aggregate effects on policy outcomes as a whole. I develop a model of the policy process which suggests that emotions related to fair and unfair experiences in the same policy domain are utilized by decision-makers as policy criteria. In the lab, I empirically tested this, and find that emotions and experience related to fairness do influence the policy decision to move away from the status quo alternative. Based upon this result, I simulated the evolution of a society of agents engaged in decision-making using similar criteria. The simulation suggests that incentives have an important role in leading to cooperation and social success. The external validity of the simulation also implies that it can act as a platform for future evolutionary policy experimentation.

Providing Reliable Data Transport for Dynamic Event Sensing in Wireless Sensor Networks

In this paper, we propose a Loss Tolerant Reliable (LTR) data transport mechanism for dynamic Event Sensing (LTRES) in WSNs. In LTRES, a reliable event sensing requirement at the transport layer is dynamically determined by the sink. A distributed source rate adaptation mechanism is designed, incorporating a loss rate based lightweight congestion control mechanism, to regulate the data traffic injected into the network so that the reliability requirement can be satisfied. An equation based fair rate control algorithm is used to improve the fairness among the LTRES flows sharing the congestion path. The performance evaluations show that LTRES can provide LTR data transport service for multiple events with short convergence time, low lost rate and high overall bandwidth utilization.