A service dependency modeling framework for policy-based response enforcement

International audienceThe use of dynamic access control policies for threat response adapts local response decisions to high level system constraints. However, security policies are often carefully tightened during system design-time, and the large number of service dependencies in a system architecture makes their dynamic adaptation di±cult. The enforcement of a single re- sponse rule requires performing multiple con¯guration changes on multi- ple services. This paper formally describes a Service Dependency Frame- work (SDF) in order to assist the response process in selecting the pol- icy enforcement points (PEPs) capable of applying a dynamic response rule. It automatically derives elementary access rules from the generic access control, either allowed or denied by the dynamic response pol- icy, so they can be locally managed by local PEPs. SDF introduces a requires/provides model of service dependencies. It models the service architecture in a modular way, and thus provides both extensibility and reusability of model components. SDF is de¯ned using the Architecture Analysis and Design Language, which provides formal concepts for mod- eling system architectures. This paper presents a systematic treatment of the dependency model which aims to apply policy rules while minimizing con¯guration changes and reducing resource consumption

Component-based Adaptation Methods for Service-Oriented Peer-to-Peer Software Architectures

Service-oriented peer-to-peer architectures aim at supporting application scenarios of dispersed collaborating groups in which the participating users are capable of providing and consuming local resources in terms of peer services. From a conceptual perspective, service-oriented peer-to-peer architectures adopt relevant concepts of two well-established state-of-the-art software architectural styles, namely service-oriented architectures (also known as SOA) and peer-to-peer architectures (P2P). One major argumentation of this thesis is that the adoption of end-user adaptability (or tailorability) concepts is of major importance for the successful deployment of service-oriented peer-to-peer architectures that support user collaboration. Since tailorability concepts have so far not been analyzed for both peer-to-peer and service-oriented architectures, no relevant models exist that could serve as a tailorability model for service-oriented peer-to-peer architectures. In order to master the adaptation of peer services, as well as peer service compositions within service-oriented peer-to-peer architectures, this dissertation proposes the adoption of component-oriented development methods. These so-called component-based adaptation methods enable service providers to adapt their provided services during runtime. Here, a model for analyzing existing dependencies on subscribed ser-vice consumers ensures that a service provider is able to adapt his peer services without violating any dependencies. In doing so, an adaptation policy that can be pre-arranged within a peer group regulates the procedures of how to cope with existing dependencies in the scope of a group. The same methods also serve as a way to handle exceptional cases, in particular the failure of a dependent service provider peer and, hence, a service that is part of a local service composition. In this, the hosting runtime environment is responsible for detecting exceptions and for initiating the process of exception resolution. During the resolution phase, a user can be actively involved at selected decision points in order to resolve the occurred exception in unpredictable contexts. An exception could also be the reason for the violation of an integrity constraint that serves as a contract between various peers that interact within a given collaboration. The notion of integrity constraints and the model of handling the constraint violation aim at improving the reliability of target-oriented peer collaborations. This dissertation is composed of three major parts that each makes a significant contribution to the state of the art. First of all, a formal architectural style (SOP2PA) is introduced to define the fundamental elements that are necessary to build service-oriented peer-to-peer architectures, as well as their relationships, constraints, and operational semantics. This architectural style also formalizes the above-mentioned adaptation methods, the exception handling model that embraces these methods, the analysis model for managing consumer dependencies, as well as the integrity constraints model. Subsequently, on this formal basis, a concrete (specific) service-oriented peer-to-peer architecture (DEEVOLVE) is conceptualized that serves as the default implementation of that style. Here, the notions described above are materialized based on state-of-the-art software engineering methods and models. Finally, the third contribution of this work outlines an application scenario stemming from the area of construction informatics, in which the default implementation DEEVOLVE is deployed in order to support dispersed planning activities of structural engineers

Adaptive monitoring and control framework in Application Service Management environment

The economics of data centres and cloud computing services have pushed hardware and software requirements to the limits, leaving only very small performance overhead before systems get into saturation. For Application Service Management–ASM, this carries the growing risk of impacting the execution times of various processes. In order to deliver a stable service at times of great demand for computational power, enterprise data centres and cloud providers must implement fast and robust control mechanisms that are capable of adapting to changing operating conditions while satisfying service–level agreements. In ASM practice, there are normally two methods for dealing with increased load, namely increasing computational power or releasing load. The first approach typically involves allocating additional machines, which must be available, waiting idle, to deal with high demand situations. The second approach is implemented by terminating incoming actions that are less important to new activity demand patterns, throttling, or rescheduling jobs. Although most modern cloud platforms, or operating systems, do not allow adaptive/automatic termination of processes, tasks or actions, it is administrators’ common practice to manually end, or stop, tasks or actions at any level of the system, such as at the level of a node, function, or process, or kill a long session that is executing on a database server. In this context, adaptive control of actions termination remains a significantly underutilised subject of Application Service Management and deserves further consideration. For example, this approach may be eminently suitable for systems with harsh execution time Service Level Agreements, such as real–time systems, or systems running under conditions of hard pressure on power supplies, systems running under variable priority, or constraints set up by the green computing paradigm. Along this line of work, the thesis investigates the potential of dimension relevance and metrics signals decomposition as methods that would enable more efficient action termination. These methods are integrated in adaptive control emulators and actuators powered by neural networks that are used to adjust the operation of the system to better conditions in environments with established goals seen from both system performance and economics perspectives. The behaviour of the proposed control framework is evaluated using complex load and service agreements scenarios of systems compatible with the requirements of on–premises, elastic compute cloud deployments, server–less computing, and micro–services architectures