Optimal Smoothing for Guaranteed Service

We consider a scenario where multimedia data is sent over a network offering a guaranteed service such as ATM VBR or the guaranteed service of the IETF. A smoothing device writes the stream into a networking device for transmission, possibly with some pre-fetching; at the destination, the decoder waits for an initial playback delay and reads the stream from the receive buffer. We consider the problem of whether there exists a smoothing which minimizes the playback delay and the receive buffer size over all possible strategies, given that we know a service curve property for the flow in the network. We show that there does exist such an optimal smoothing. It can be expressed using the deconvolution operator of min-plus algebra. We obtain the smallest playback delay which can be achieved by smoothing, provided that the information about the network is reduced to its service curve . We also give a constructive expression for the deconvolution operator, using a time inversion transform, introduced in the paper. We illustrate on some examples the difference with optimal shaping, a smoothing strategy which aims at minimizing buffer and delay on the sender side but does not allow pre-fetching. We apply the theory to the determination of the minimum T-SPEC required to support a given flow with admissible playback delay or decoding buffer size constraints

Domestic versus External Borrowing and Fiscal Policy in Emerging Markets

Domestic public debt issued by emerging markets has risen significantly relative to international debt in recent years. Some recent empirical evidence also suggests that sovereigns have defaulted differentially on debt held by domestic and external creditors. Standard models of sovereign debt, however, mainly focus on how the actions of foreign creditors influence default decisions of sovereigns. Contrasting this one-sided focus, this paper adds to a new theoretical literature that points at the possibility of default on domestic debt and the consequences of doing so. It presents a model of an emerging market economy in which the government can selectively default on its domestic or external debt obligations. The model shows that the differential ability of domestic and foreign creditors to punish the government creates a gap in the expected default costs to the sovereign, and hence a differential in its propensity to default on its domestic versus foreign debt. The extent to which the possibility of differential treatment of creditors affects the composition of debt is explored. It shows that a country characterized by volatile output, sovereign risk, and costly tax collection will want to borrow in domestic markets as well as in international capital markets. The optimal allocation of debt between domestic and foreign creditors can thus be viewed as the government's purchase of insurance against macroeconomic shocks that affect its budget.Debt management; International topics

Statistic Rate Monotonic Scheduling

In this paper we present Statistical Rate Monotonic Scheduling (SRMS), a generalization of the classical RMS results of Liu and Layland that allows scheduling periodic tasks with highly variable execution times and statistical QoS requirements. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. The feasibility test for SRMS ensures that using SRMS' scheduling algorithms, it is possible for a given periodic task set to share a given resource (e.g. a processor, communication medium, switching device, etc.) in such a way that such sharing does not result in the violation of any of the periodic tasks QoS constraints. The SRMS scheduling algorithm incorporates a number of unique features. First, it allows for fixed priority scheduling that keeps the tasks' value (or importance) independent of their periods. Second, it allows for job admission control, which allows the rejection of jobs that are not guaranteed to finish by their deadlines as soon as they are released, thus enabling the system to take necessary compensating actions. Also, admission control allows the preservation of resources since no time is spent on jobs that will miss their deadlines anyway. Third, SRMS integrates reservation-based and best-effort resource scheduling seamlessly. Reservation-based scheduling ensures the delivery of the minimal requested QoS; best-effort scheduling ensures that unused, reserved bandwidth is not wasted, but rather used to improve QoS further. Fourth, SRMS allows a system to deal gracefully with overload conditions by ensuring a fair deterioration in QoS across all tasks---as opposed to penalizing tasks with longer periods, for example. Finally, SRMS has the added advantage that its schedulability test is simple and its scheduling algorithm has a constant overhead in the sense that the complexity of the scheduler is not dependent on the number of the tasks in the system. We have evaluated SRMS against a number of alternative scheduling algorithms suggested in the literature (e.g. RMS and slack stealing), as well as refinements thereof, which we describe in this paper. Consistently throughout our experiments, SRMS provided the best performance. In addition, to evaluate the optimality of SRMS, we have compared it to an inefficient, yet optimal scheduler for task sets with harmonic periods.National Science Foundation (CCR-970668

q-Gaussian based Smoothed Functional Algorithm for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.Comment: 5 pages, 1 figur