Behavioural assume-guarantee contracts for linear dynamical systems

Motivated by the growing requirements on theoperation of complex engineering systems, we present con-tracts as specifications for continuous-time linear dynamicalsystems with inputs and outputs. A contract is defined asa pair of assumptions and guarantees, both characterized ina behavioural framework. The assumptions encapsulate theavailable information about the dynamic behaviour of theenvironment in which the system is supposed to operate, whilethe guarantees express the desired dynamic behaviour of thesystem when interconnected with relevant environments. Inaddition to defining contracts, we characterize contract imple-mentation, and we find necessary conditions for the existence ofan implementation. We also characterize contract refinement,which is used to characterize contract conjunction in two specialcases. These concepts are then illustrated by an example of avehicle following system

Behavioural contracts for linear dynamical systems:Input assumptions and output guarantees

We introduce contracts for linear dynamical systems with inputs and outputs. Contracts are used to express formal specifications on the dynamic behaviour of such systems through two aspects: assumptions and guarantees. The assumptions are a linear system that captures the available knowledge about the dynamic behaviour of the environment in which the system is supposed to operate. The guarantees are a linear system that captures the required dynamic behaviour of the system when interconnected with its environment. In addition to contracts, we also define and characterize notions of contract refinement and contract conjunction. Contract refinement allows one to determine if a contract expresses a stricter specifications than another contract. On the other hand, contract conjunction allows one to combine multiple contracts into a single contract that fuses the specifications they expres

Systemically Important or “Too Big to Fail” Financial Institutions

Although “too big to fail” (TBTF) has been a perennial policy issue, it was highlighted by the near-collapse of several large financial firms in 2008. Large financial firms that failed or required extraordinary government assistance in the recent crisis included depositories (Citigroup and Washington Mutual), government-sponsored enterprises (Fannie Mae and Freddie Mac), insurance companies (AIG), and investment banks (Bear Stearns and Lehman Brothers).1 In many of these cases, policy makers justified the use of government resources on the grounds that the firms were “systemically important” or “too big to fail.” TBTF is the concept that a firm’s disorderly failure would cause widespread disruptions in financial markets that could not easily be contained. While the government had no explicit policy to rescue TBTF firms, several were rescued on those grounds once the crisis struck. TBTF subsequently became one of the systemic risk issues that policy makers grappled with in the wake of the recent crisis. This report discusses the economic issues raised by TBTF, broad policy options, and policy changes made by the relevant Dodd-Frank provisions. This report also discusses recent legislation addressing the TBTF issue in the 113th Congress. The report ends with an Appendix reviewing the historical experience with TBTF before and during the recent crisis

Composition of behavioural assume-guarantee contracts

The growing complexity of modern engineering systems necessitates a method for design and analysis that is inherently modular. Methods based on using contracts for system design have successfully tackled this issue for a variety of system classes, but mostly in the context of discrete software systems. Motivated by this, we present assume-guarantee contracts for continuous linear dynamical systems with inputs and outputs. Such contracts serve as system specifications through two aspects. The assumptions specify the dynamic behaviour of the environment of the system, which provides inputs for it, while the guarantees specify the desired dynamic behaviour of the output of the system when interconnected with a relevant environment. This is formalized by utilizing the behavioural approach to system theory. We define and characterize notions of contract implementation and contract refinement, where the latter is used to compare contracts. We also define and characterize two notions of contract composition that allow one to reason about two types of system interconnections: series and feedback. The properties of refinement and composition allow contracts to be used for modular design and analysis.</p

Four Futures for Finance; A scenario study

This document presents four scenarios for the future of finance. The goal of our study is to imagine the future of finance and to identify challenges faced by policymakers in fighting systemic risk. It builds upon a tradition within the CPB to develop scenarios for policy analysis. We develop four scenarios for the future of finance. Our scenarios differ in two dimensions. First, to what extent soft information lies at the core of banks’ business. Second, to what extent scope economies exist between different banking activities. By combining these two dimensions, we obtain four scenarios: Isolated Islands, Big Banks, Competing Conglomerates, and Flat Finance. Market structure, market failures, and government failures vary between scenarios. These differences then translate into differences in the complexity of balance sheets, the ability to coordinate policy internationally, the information gap faced by regulators, the size of banks’ balance sheets, the tradability of banks’ assets, the level of interconnectedness, the potential for market discipline, and the threat of regulatory capture. As a result, each scenario calls for a different set of policies to combat systemic risk.

SensorCloud: Towards the Interdisciplinary Development of a Trustworthy Platform for Globally Interconnected Sensors and Actuators

Although Cloud Computing promises to lower IT costs and increase users' productivity in everyday life, the unattractive aspect of this new technology is that the user no longer owns all the devices which process personal data. To lower scepticism, the project SensorCloud investigates techniques to understand and compensate these adoption barriers in a scenario consisting of cloud applications that utilize sensors and actuators placed in private places. This work provides an interdisciplinary overview of the social and technical core research challenges for the trustworthy integration of sensor and actuator devices with the Cloud Computing paradigm. Most importantly, these challenges include i) ease of development, ii) security and privacy, and iii) social dimensions of a cloud-based system which integrates into private life. When these challenges are tackled in the development of future cloud systems, the attractiveness of new use cases in a sensor-enabled world will considerably be increased for users who currently do not trust the Cloud.Comment: 14 pages, 3 figures, published as technical report of the Department of Computer Science of RWTH Aachen Universit