Logico-numerical Control for Software Components Reconfiguration

International audienceWe target the problem of the safe control of reconfigurations in component-based software systems, where strategies of adaptation to variations in both their environment and internal resource demands need to be enforced. In this context, the computing system involves software components that are subject to control decisions. We approach this problem under the angle of Discrete Event Systems (DES), involving properties on events observed during the execution (e.g., requests of computing tasks, work overload), and a state space representing different configurations such as activity or assemblies of components. We consider in particular the potential of applying novel logico-numerical control techniques to extend the expressivity of control models and objectives, thereby extending the application of DES in component-based software systems. We elaborate methodological guidelines for the application of logico-numerical control based on a case- study, and validate the result experimentally

Robust and reliable reconfiguration of cloud applications

International audienceCloud applications involve a set of interconnected software components running on remote virtual machines. The deployment and dynamic reconfigu-ration of cloud applications, involving the addition/removal of virtual machines and components hosted on these virtual machines, are error-prone tasks. They must preserve the application consistency and respect important architectural invariants related to software dependencies. In this paper, we introduce a protocol for automating these reconfiguration tasks. In order to ensure its correctness and robustness, we implement the protocol with the support of the Maude system for rapid prototyping purposes, and we verify it with its formal analysis tools

SMT-Based Planning Synthesis for Distributed System Reconfigurations

International audienceLarge distributed systems with an emphasis on adaptability are now considered a necessity in many domains, yet reconfiguration of these systems is still largely carried out in an ad hoc fashion, a process that is both inefficient and error-prone. In this paper, we tackle the planification problem for the reconfiguration of distributed systems in the component-based reconfiguration model Concerto. Specifically, given some tasks to execute and a desired final state of the system, we show how to compute a reconfiguration plan that guarantees satisfaction of inter-component dependencies and is also optimized for parallel execution. Our technique relies on an SMT solver to compute the required dependencies between components and ultimately schedule the reconfiguration. We illustrate the use of this technique on a variety of synthetic examples as well as a real use case in the context of an OpenStack system

High-level Language Support for the Control of Reconfigurations in Component-based Architectures

International audienceNowadays, smart home is extended beyond the house itself to encompass connected platforms on the Cloud as well as mobile personal devices. This Smart Home Extended Architecture (SHEA) helps customers to remain in touch with their home everywhere and any time. The endless increase of connected devices in the home and outside within the SHEA multiplies the deployment possibilities for any application. Therefore, SHEA should be taken from now as the actual target platform for smart home application deployment. Every home is different and applications offer different services according to customer preferences. To manage this variability, we extend the feature modeling from software product line domain with deployment constraints and we present an example of a model that could address this deployment challenge

Evolution of Network Architecture in a Granular Material Under Compression

As a granular material is compressed, the particles and forces within the system arrange to form complex and heterogeneous collective structures. Force chains are a prime example of such structures, and are thought to constrain bulk properties such as mechanical stability and acoustic transmission. However, capturing and characterizing the evolving nature of the intrinsic inhomogeneity and mesoscale architecture of granular systems can be challenging. A growing body of work has shown that graph theoretic approaches may provide a useful foundation for tackling these problems. Here, we extend the current approaches by utilizing multilayer networks as a framework for directly quantifying the progression of mesoscale architecture in a compressed granular system. We examine a quasi-two-dimensional aggregate of photoelastic disks, subject to biaxial compressions through a series of small, quasistatic steps. Treating particles as network nodes and interparticle forces as network edges, we construct a multilayer network for the system by linking together the series of static force networks that exist at each strain step. We then extract the inherent mesoscale structure from the system by using a generalization of community detection methods to multilayer networks, and we define quantitative measures to characterize the changes in this structure throughout the compression process. We separately consider the network of normal and tangential forces, and find that they display a different progression throughout compression. To test the sensitivity of the network model to particle properties, we examine whether the method can distinguish a subsystem of low-friction particles within a bath of higher-friction particles. We find that this can be achieved by considering the network of tangential forces, and that the community structure is better able to separate the subsystem than a purely local measure of interparticle forces alone. The results discussed throughout this study suggest that these network science techniques may provide a direct way to compare and classify data from systems under different external conditions or with different physical makeup

Development of Measures to Assess Product Modularity and Reconfigurability

Several fundamental benefits of modularity are agreed upon by industry including reusability, flexibility, reconfigurability and extensibility. Interfaces within or between modules which establish provide/depend relationships are the focus of current modularity measures. This research outlines a new method and measures for assessing product modularity in terms of degree of coupling and the recognized modularity benefits. A five–step analysis process is developed and used to guide the modularity assessment. Defining and decomposing products are performed first. Using the resultant functional model from the first step, the identified functions are mapped to modules in a product in the second step. In the third and fourth steps, module-to-module interfaces are identified and captured in design structure matrices or a tensor plot. Finally, using results from steps 1–4, the Vector Modularity Measure that includes a reconfigurability measure can be calculated. The measures and analysis process are demonstrated using two precision guided munitions in the United States Air Force inventory. After this demonstration, the research focuses on extending the approach to a modular satellite design problem, namely AFRL’s Plug-and-Play Satellite (PnPSat) concept for Operationally Responsive Space. Using the resulting analysis, recommendations to the existing PnPSat design to further increase modularity and its derived benefits are given. Lastly, the modularity analysis process and applications are used to draw conclusions and make recommendations for future research to include identifying factors that influence both modularity and the timeline to perform product assembly and check-out

Surfaces with Patterned Wettability: Design and Applications.

Surfaces with patterned wettability have well-defined domains containing both wettable and non-wettable regions. One of the key features of the surfaces with patterned wettability is their ability to localize wetting of liquids preferentially within the patterned wettable regions. This ability of the patterned surfaces has been widely explored as a simple route to pattern both liquids, as well as, solids for various applications such as microfluidics, electronic and optical devices, surfaces with enhanced heat transfer properties, etc. However, most of the patterned surfaces exhibit wettability contrast only with high surface tension liquids such as water, thereby limiting the applications of the patterned surfaces to only aqueous systems. Herein, we utilize the design principles of superomniphobicity (repellency towards all liquids) to develop the first-ever patterned superomniphobic-superomniphilic surfaces that exhibit extremely wettability contrast with both high and low surface tension liquids. Utilizing these patterned surfaces, we demonstrate site-selective self-assembly of various liquids including: oils, alcohols, polymer solutions and solid dispersions. We also demonstrate site-selective condensation and boiling with low surface tension liquids, which is crucial when designing surfaces with significantly enhanced, phase-change, heat-transfer properties. We have further utilized surfaces with patterned wettability as templates for fabricating monodisperse, multi-phasic micro- and nano-particles. The developed technique termed WETS (Wettability Engendered Templated Self-assembly) provides us with an unprecedented ability to manufacture multi-phasic particles, on a large-scale, with precise control over the size (down to 25 nm), shape, chemistry and surface charge of the particles. We further demonstrate the utility of the WETS technique in developing amphiphilic building blocks for self-assembly and multi-functional cargo carriers. Finally, we have also studied stimuli-responsive shape reconfigurations of the multi-phasic WETS particles. Overall, this dissertation puts forward design principles for developing surfaces with patterned wettability that are universal to almost all liquids, thus enabling novel applications for the patterned surfaces, such as the WETS technique reported here.PhDMacromolecular Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116726/1/saireddy_1.pd