Budgeting Under-Specified Tasks for Weakly-Hard Real-Time Systems

In this paper, we present an extension of slack analysis for budgeting in the design of weakly-hard real-time systems. During design, it often happens that some parts of a task set are fully specified while other parameters, e.g. regarding recovery or monitoring tasks, will be available only much later. In such cases, slack analysis can help anticipate how these missing parameters can influence the behavior of the whole system so that a resource budget can be allocated to them. It is, however, sufficient in many application contexts to budget these tasks in order to preserve weakly-hard rather than hard guarantees. We thus present an extension of slack analysis for deriving task budgets for systems with hard and weakly-hard requirements. This work is motivated by and validated on a realistic case study inspired by industrial practice

A Mechanism for Participatory Budgeting With Funding Constraints and Project Interactions

Participatory budgeting (PB) has been widely adopted and has attracted significant research efforts; however, there is a lack of mechanisms for PB which elicit project interactions, such as substitution and complementarity, from voters. Also, the outcomes of PB in practice are subject to various minimum/maximum funding constraints on 'types' of projects. There is an insufficient understanding of how these funding constraints affect PB's strategic and computational complexities. We propose a novel preference elicitation scheme for PB which allows voters to express how their utilities from projects within 'groups' interact. We consider preference aggregation done under minimum and maximum funding constraints on 'types' of projects, where a project can have multiple type labels as long as this classification can be defined by a 1-laminar structure (henceforth called 1-laminar funding constraints). Overall, we extend the Knapsack voting model of Goel et al. in two ways - enriching the preference elicitation scheme to include project interactions and generalizing the preference aggregation scheme to include 1-laminar funding constraints. We show that the strategyproofness results of Goel et al. for Knapsack voting continue to hold under 1-laminar funding constraints. Although project interactions often break the strategyproofness, we study a special case of vote profiles where truthful voting is a Nash equilibrium under substitution project interactions. We then turn to the study of the computational complexity of preference aggregation. Social welfare maximization under project interactions is NP-hard. As a workaround for practical instances, we give a fixed parameter tractable (FPT) algorithm for social welfare maximization with respect to the maximum number of projects in a group

Proportionally Representative Clustering

In recent years, there has been a surge in effort to formalize notions of fairness in machine learning. We focus on clustering -- one of the fundamental tasks in unsupervised machine learning. We propose a new axiom ``proportional representation fairness'' (PRF) that is designed for clustering problems where the selection of centroids reflects the distribution of data points and how tightly they are clustered together. Our fairness concept is not satisfied by existing fair clustering algorithms. We design efficient algorithms to achieve PRF both for unconstrained and discrete clustering problems. Our algorithm for the unconstrained setting is also the first known polynomial-time approximation algorithm for the well-studied Proportional Fairness (PF) axiom (Chen, Fain, Lyu, and Munagala, ICML, 2019). Our algorithm for the discrete setting also matches the best known approximation factor for PF.Comment: Revised version includes a new author (Jeremy Vollen) and new results: Our algorithm for the unconstrained setting is also the first known polynomial-time approximation algorithm for the well-studied Proportional Fairness (PF) axiom (Chen, Fain, Lyu, and Munagala, ICML, 2019). Our algorithm for the discrete setting also matches the best known approximation factor for P

Analysis of Embedded Controllers Subject to Computational Overruns

Microcontrollers have become an integral part of modern everyday embedded systems, such as smart bikes, cars, and drones. Typically, microcontrollers operate under real-time constraints, which require the timely execution of programs on the resource-constrained hardware. As embedded systems are becoming increasingly more complex, microcontrollers run the risk of violating their timing constraints, i.e., overrunning the program deadlines. Breaking these constraints can cause severe damage to both the embedded system and the humans interacting with the device. Therefore, it is crucial to analyse embedded systems properly to ensure that they do not pose any significant danger if the microcontroller overruns a few deadlines.However, there are very few tools available for assessing the safety and performance of embedded control systems when considering the implementation of the microcontroller. This thesis aims to fill this gap in the literature by presenting five papers on the analysis of embedded controllers subject to computational overruns. Details about the real-time operating system's implementation are included into the analysis, such as what happens to the controller's internal state representation when the timing constraints are violated. The contribution includes theoretical and computational tools for analysing the embedded system's stability, performance, and real-time properties.The embedded controller is analysed under three different types of timing violations: blackout events (when no control computation is completed during long periods), weakly-hard constraints (when the number of deadline overruns is constrained over a window), and stochastic overruns (when violations of timing constraints are governed by a probabilistic process). These scenarios are combined with different implementation policies to reduce the gap between the analysis and its practical applicability. The analyses are further validated with a comprehensive experimental campaign performed on both a set of physical processes and multiple simulations.In conclusion, the findings of this thesis reveal that the effect deadline overruns have on the embedded system heavily depends the implementation details and the system's dynamics. Additionally, the stability analysis of embedded controllers subject to deadline overruns is typically conservative, implying that additional insights can be gained by also analysing the system's performance

The Political Economy of Fiscal Policy

If there has been a dominant trend in the evolution of the modern industrial societies of this century it has been the growing importance of government in the allocation of social resources. It is important that we appreciate the fundamentally political nature of the formation of government economic policy. This survey reviews and assesses our present understanding of how the political system might shape a nation's fiscal policy. Our approach is eclectic, drawing both from economics and political science, and decidedly micro-analytic in its orientation. From economics we adopt the perspective of utility maximizing agents and the analytics of trade, agreement, and market failure. From political science we learn just how and when these individual agents might act collectively to provide public goods, redistribute income, or issue government debt. Together the micro-analytics of economics and political science form the core theory of the 'new' political economy and provide a framework for understanding the emergence, and the performance, of governments. There is no more important test for the new discipline than providing a compelling explanation for the formation of fiscal policy in democratic societies.

Control-System Stability Under Consecutive Deadline Misses Constraints

This paper deals with the real-time implementation of feedback controllers. In particular, it provides an analysis of the stability property of closed-loop systems that include a controller that can sporadically miss deadlines. In this context, the weakly hard m-K computational model has been widely adopted and researchers used it to design and verify controllers that are robust to deadline misses. Rather than using the m-K model, we focus on another weakly-hard model, the number of consecutive deadline misses, showing a neat mathematical connection between real-time systems and control theory. We formalise this connection using the joint spectral radius and we discuss how to prove stability guarantees on the combination of a controller (that is unaware of deadline misses) and its system-level implementation. We apply the proposed verification procedure to a synthetic example and to an industrial case study

Are managers indeed motivated by their bonuses?

Management;Incentives;labour economics

Is There a Market for Work Group Servers? Evaluating Market Level Demand Elasticities Using Micro and Macro Models

This paper contains an empirical analysis demand for "work-group" (or low-end) servers. Servers are at thecentre of many US and EU anti-trust debates, including the Hewlett-Packard/Compaq merger and investigationsinto the activities of Microsoft. One question in these policy decisions is whether a high share of work serversindicates anything about shortrun market power. To investigate price elasticities we use model-level panel dataon transaction prices, sales and characteristics of practically every server in the world. We contrast estimatesfrom the traditional "macro" approaches that aggregate across brands and modern "micro" approaches that usebrand-level information (including both "distance metric" and logit based approaches). We find that the macroapproaches lead to overestimates of consumer price sensitivity. Our preferred micro-based estimates of themarket level elasticity of demand for work group servers are around 0.3 to 0.6 (compared to 1 to 1.3 in themacro estimates). Even at the higher range of the estimates, however, we find that demand elasticities aresufficiently low to imply a distinct "anti-trust" market for work group servers and their operating systems. It isunsurprising that firms with large shares of work group servers have come under some antitrust scrutiny.demand elasticities, network servers, computers, anti-trust