Introduction

Project context

Distributed systems are at the core of the information society, ranging from everyday’s applications such as banking or health care to highly specialised systems used in automation, transportation, and air traffic control. The key element for achieving scalable and maintainable distributed software systems is dependability, because otherwise the complexity of distribution would leave the system brittle, vulnerable, and uncontrollable at the end.

DeDiSys provides concepts for optimized dependability for two classes of distributed systems: Tightly coupled, data-centric systems such as distributed object systems and loosely coupled, service-oriented systems such as Web service based Grid systems or peer-to-peer systems.

Addressed problem

The major focus of DeDiSys is on optimized dependability by adaptively balancing (trading) availability and constraint consistency. System entities (objects, services) are constraint consistent if constraints (typically predicates stemming from requirements) put on them are satisfied. In data-centric applications the data itself is subject to constraints (data integrity). In service-oriented systems we focus on quality of service constraints.

If constraint consistency has to be ensured all time (e.g., bank applications), even in the presence of failures, the system becomes unavailable in degraded scenarios. However, some applications (e.g., safety-critical systems) exist where constraint consistency can be relaxed in order to achieve higher availability.

The aim of DeDiSys is to investigate the optimum between the two extremes: Can some of the data and service constraints be adaptively negotiated and (temporarily) relaxed to improve the availability of the distributed system?