Dynamic mechanism design for markets with strategic resources

The assignment of tasks to multiple resources becomes an interesting game theoretic problem, when both the task owner and the resources are strategic. In the classical, nonstrategic setting, where the states of the tasks and resources are observable by the controller, this problem is that of finding an optimal policy for a Markov decision process (MDP). When the states are held by strategic agents, the problem of an efficient task allocation extends beyond that of solving an MDP and becomes that of designing a mechanism. Motivated by this fact, we propose a general mechanism which decides on an allocation rule for the tasks and resources and a payment rule to incentivize agents' participation and truthful reports. In contrast to related dynamic strategic control problems studied in recent literature, the problem studied here has interdependent values: the benefit of an allocation to the task owner is not simply a function of the characteristics of the task itself and the allocation, but also of the state of the resources. We introduce a dynamic extension of Mezzetti's two phase mechanism for interdependent valuations. In this changed setting, the proposed dynamic mechanism is efficient, within period ex-post incentive compatible, and within period ex-post individually rational.

Optimal design of timer-based, distributed selection with unknown number of nodes

The timer-based selection scheme is a popular, simple, and distributed scheme that is used to select the best node from a set of available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal timer mapping that maximizes the average success probability for the practical scenario in which the number of nodes in the system is unknown but only its probability distribution is known. We show that it has a special discrete structure, and present a recursive characterization to determine it. We benchmark its performance with ad hoc approaches proposed in the literature, and show that it delivers significant gains. New insights about the optimality of some ad hoc approaches are also developed.

Design Of Start-up Power Circuit For Control Power Supplies With Wide Input Voltage Variation

This paper presents the design of a start up power circuit for a control power supply (CPS) which feeds power to the sub-systems of High Power Converters (HPC). The sub-systems such as gate drive card, annunciation card, protection and delay card etc; needs to be provided power for the operation of a HPC. The control power supply (CPS) is designed to operate over a wide range of input voltage from 90Vac to 270Vac. The CPS output supplies power at a desired voltage of Vout =24V to the auxiliary sub-systems of the HPC. During the starting, the power supply to the control circuitry of CPS in turn, is obtained using a separate start-up power supply. This paper discusses the various design issues of the start-up power circuit to ensure that start-up and shut down of the CPS occurs reliably. The CPS also maintains the power factor close to unity and low total harmonic distortion in input current. The paper also provides design details of gate drive circuits employed for the CPS as well as the design of on-board power supply for the CPS. Index terms: control power supply, start-up power supply, DSFC, pre-regulator

Optimal Binary Power Control for Underlay CR With Different Interference Constraints and Impact of Channel Estimation Errors

Adapting the power of secondary users (SUs) while adhering to constraints on the interference caused to primary receivers (PRxs) is a critical issue in underlay cognitive radio (CR). This adaptation is driven by the interference and transmit power constraints imposed on the secondary transmitter (STx). Its performance also depends on the quality of channel state information (CSI) available at the STx of the links from the STx to the secondary receiver and to the PRxs. For a system in which an STx is subject to an average interference constraint or an interference outage probability constraint at each of the PRxs, we derive novel symbol error probability (SEP)-optimal, practically motivated binary transmit power control policies. As a reference, we also present the corresponding SEP-optimal continuous transmit power control policies for one PRx. We then analyze the robustness of the optimal policies when the STx knows noisy channel estimates of the links between the SU and the PRxs. Altogether, our work develops a holistic understanding of the critical role played by different transmit and interference constraints in driving power control in underlay CR and the impact of CSI on its performance.

Design and Testing of a Control System for Supply Side Electrical Load Management

India's energy demand is increasing rapidly with the intensive growth of economy. The electricity demand in India exceeded the availability, both in terms of base load energy and peak availability. The efficient use of energy source and its conversion and utilizations are the viable alternatives available to the utilities or industry. There are essentially two approaches to electrical energy management. First at the supply / utility end (Supply Side Management or SSM) and the other at the consumer end (Demand Side Management or DSM). This work is based on Supply Side Management (SSM) protocol and consists of design, fabrication and testing of a control device that will be able to automatically regulate the power flow to an individual consumer's premise. This control device can monitor the overuse of electricity (above the connected load or contracted demand) by the individual consumers. The present project work specially emphasizes on contract demand of every consumer and tries to reduce the use beyond the contract demand. This control unit design includes both software and hardware work and designed for 0.5 kW contract demand. The device is tested in laboratory and reveals its potential use in the field.

Design and morphology control of a thiophene derivative through electrospraying using various solvents

In the present work, electrospraying of an organic molecule is carried out using various solvents, obtaining fibril structures along with a range of distinct morphologies. Solvent characteristics play a major role in determining the morphology of the organic material. A thiophene derivative (7,9-di(thiophen-2-yl)-8H-cyclopentaa]acenaphthylen-8-one) (DTCPA) of donor-acceptor-donor (DAD) architecture is used to study this solvent effect. Seven solvents with decreasing vapour pressure are selected for experiments. Electrospraying is conducted at a solution concentration of 1.5 wt% and a constant applied voltage of 15 kV. Gradual transformation in morphology of the electrospun product from spiked-spheres to only spikes is observed. A mechanism describing this transformation is proposed based on electron micrograph analysis and XRD analysis. These data indicate that the morphological change is due to the synergistic effect of both vapour pressure and dielectric constant of the solvents. Through a reasonable control of the crystallite size and morphology along with the proposal of the transformation mechanism, this study elucidates electrospraying as a prospective method for designing architectures in organic electronics.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.

Impact of lifetime control on the threshold of quantum dot lasers

Despite significant improvements in their properties as emitters, colloidal quantum dots have not had much success in emerging as suitable materials for laser applications. Gain in most colloidal systems is short lived, and needs to compete with biexcitonic decay. This has necessitated the use of short pulsed lasers to pump quantum dots to thresholds needed for amplified spontaneous emission or lasing. Continuous wave pumping of gain that is possible in some inorganic phosphors has therefore remained a very distant possibility for quantum dots. Here, we demonstrate that trilayer heterostructures could provide optimal conditions for demonstration of continuous wave lasing in colloidal materials. The design considerations for these materials are discussed in terms of a kinetic model. The electronic structure of the proposed dot architectures is modeled within effective mass theory.