Architecture, Services and Protocols for CRUTIAL

This document describes the complete specification of the architecture, services and protocols of the project CRUTIAL. The CRUTIAL Architecture intends to reply to a grand challenge of computer science and control engineering: how to achieve resilience of critical information infrastructures (CII), in particular in the electrical sector. In general lines, the document starts by presenting the main architectural options and components of the architecture, with a special emphasis on a protection device called the CRUTIAL Information Switch (CIS). Given the various criticality levels of the equipments that have to be protected, and the cost of using a replicated device, we define a hierarchy of CIS designs incrementally more resilient. The different CIS designs offer various trade offs in terms of capabilities to prevent and tolerate intrusions, both in the device itself and in the information infrastructure. The Middleware Services, APIs and Protocols chapter describes our approach to intrusion tolerant middleware. The CRUTIAL middleware comprises several building blocks that are organized on a set of layers. The Multipoint Network layer is the lowest layer of the middleware, and features an abstraction of basic communication services, such as provided by standard protocols, like IP, IPsec, UDP, TCP and SSL/TLS. The Communication Support layer features three important building blocks: the Randomized Intrusion-Tolerant Services (RITAS), the CIS Communication service and the Fosel service for mitigating DoS attacks. The Activity Support layer comprises the CIS Protection service, and the Access Control and Authorization service. The Access Control and Authorization service is implemented through PolyOrBAC, which defines the rules for information exchange and collaboration between sub-modules of the architecture, corresponding in fact to different facilities of the CII’s organizations. The Monitoring and Failure Detection layer contains a definition of the services devoted to monitoring and failure detection activities. The Runtime Support Services, APIs, and Protocols chapter features as a main component the Proactive-Reactive Recovery service, whose aim is to guarantee perpetual correct execution of any components it protects.Project co-funded by the European Commission within the Sixth Frame-work Programme (2002-2006

Resilience-Building Technologies: State of Knowledge -- ReSIST NoE Deliverable D12

This document is the first product of work package WP2, "Resilience-building and -scaling technologies", in the programme of jointly executed research (JER) of the ReSIST Network of Excellenc

Diagnostic and prognostic analysis tools for monitoring degradation in aged structures

This research addresses the problem of prolonging the life of aged structures of historical value that have already outlived their original designed lives many times. While a lot of research has been carried out in the field of structural monitoring, diagnostics and prognostics for high tech industries, this is not the case for historical aged structures. Currently most maintenance projects for aged structures have focused on the instrumentation and diagnostic techniques required to detect any damage with a certain degree of success. This research project involved the development of diagnostic and prognostic tools to be used for monitoring and predicting the ‘health’ of aged structures. The diagnostic and prognostic tools have been developed for the monitoring of Cutty Sark iron structures as a first application. The concept of canary and parrot sensor devices are developed where canary devices are small, accelerated devices, which will fail according to similar failure mechanisms occurring in an aged structures and parrot devices are designed to fail at the same rate as the structure, thus mimicking the structure. The model-driven prognostic tool uses a Physics-of-Failure (PoF) model to predict remaining life of a structure. It uses a corrosion model based on the decrease in corrosion rate over time to predict remaining life of an aged iron structures. The data-driven diagnostic tool developed uses Mahalanobis Distance analysis to detect anomalies in the behaviour of a structure. Bayesian Network models are then used as a fusion method, integrating remaining life predictions from the model-driven prognostic tool with information of possible anomalies from data-driven diagnostic tool to provide a probability distribution of predicted remaining life. The diagnostics and prognostic tools are validated and tested through demonstration example and experimental tests. This research primarily looks at applying diagnostic and prognostic technologies used in high-tech industries to aged iron structures. In order to achieve this, the model-driven and data-driven techniques commonly used had to be adapted taking into consideration the particular constraints of monitoring and maintaining aged structures. The fusion technique developed is a novel approach for prognostics for aged structures and provides the flexibility often needed for diagnostic and prognostic tools

Preliminary Specification of Services and Protocols

This document describes the preliminary specification of services and protocols for the Crutial Architecture. The Crutial Architecture definition, first addressed in Crutial Project Technical Report D4 (January 2007), intends to reply to a grand challenge of computer science and control engineering: how to achieve resilience of critical information infrastructures, in particular in the electrical sector. The definitions herein elaborate on the major architectural options and components established in the Preliminary Architecture Specification (D4), with special relevance to the Crutial middleware building blocks, and are based on the fault, synchrony and topological models defined in the same document. The document, in general lines, describes the Runtime Support Services and APIs, and the Middleware Services and APIs. Then, it delves into the protocols, describing: Runtime Support Protocols, and Middleware Services Protocols. The Runtime Support Services and APIs chapter features as a main component, the Proactive-Reactive Recovery Service, whose aim is to guarantee perpetual execution of any components it protects. The Middleware Services and APIs chapter describes our approach to intrusion-tolerant middleware. The middleware comprises several layers. The Multipoint Network layer is the lowest layer of CRUTIAL's middleware, and features an abstraction of basic communication services, such as provided by standard protocols, like IP, IPsec, UDP, TCP and SSL/TLS. The Communication Support Services feature two important building blocks: the Randomized Intrusion-Tolerant Services (RITAS), and the Overlay Protection Layer (OPL) against DoS attacks. The Activity Support Services currently defined comprise the CIS Protection service, and the Access Control and Authorization service. Protection as described in this report is implemented by mechanisms and protocols residing on a device called Crutial Information Switch (CIS). The Access Control and Authorization service is implemented through PolyOrBAC, which defines the rules for information exchange and collaboration between sub-modules of the architecture, corresponding in fact to different facilities of the CII's organizations.The Monitoring and Failure Detection layer contains a preliminary definition of the middleware services devoted to monitoring and failure detection activities. The remaining chapters describe the protocols implementing the above-mentioned services: Runtime Support Protocols, and Middleware Services Protocol

An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)

With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

On Autonomic HPC Clouds

Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015.The long tail of science using HPC facilities is looking nowadays to instant available HPC Clouds as a viable alternative to the long waiting queues of supercomputing centers. While the name of HPC Cloud is suggesting a Cloud service, the current HPC-as-a-Service is mainly an offer of bar metal, better named cluster-on-demand. The elasticity and virtualization benefits of the Clouds are not exploited by HPC-as-a-Service. In this paper we discuss how the HPC Cloud offer can be improved from a particular point of view, of automation. After a reminder of the characteristics of the Autonomic Cloud, we project the requirements and expectations to what we name Autonomic HPC Clouds. Finally, we point towards the expected results of the latest research and development activities related to the topics that were identified.The work related to Autonomic HPC Clouds is supported by the European Commission under grant agreement H2020-6643946 (CloudLightning). The CLoudLightning project proposal was prepared by eight partner institutions, three of them as earlier partners in the COST Action IC1305 NESUS, benefiting from its inputs for the proposal. The section related to Autonomic Clouds is supported by the Romanian UEFISCDI under grant agreement PN-II-ID-PCE-2011- 3-0260 (AMICAS)