528 research outputs found
Asynchronous Distributed Execution of Fixpoint-Based Computational Fields
Coordination is essential for dynamic distributed systems whose components exhibit interactive and autonomous behaviors. Spatially distributed, locally interacting, propagating computational fields are particularly appealing for allowing components to join and leave with little or no overhead. Computational fields are a key ingredient of aggregate programming, a promising software engineering methodology particularly relevant for the Internet of Things. In our approach, space topology is represented by a fixed graph-shaped field, namely a network with attributes on both nodes and arcs, where arcs represent interaction capabilities between nodes. We propose a SMuC calculus where mu-calculus- like modal formulas represent how the values stored in neighbor nodes should be combined to update the present node. Fixpoint operations can be understood globally as recursive definitions, or locally as asynchronous converging propagation processes. We present a distributed implementation of our calculus. The translation is first done mapping SMuC programs into normal form, purely iterative programs and then into distributed programs. Some key results are presented that show convergence of fixpoint computations under fair asynchrony and under reinitialization of nodes. The first result allows nodes to proceed at different speeds, while the second one provides robustness against certain kinds of failure. We illustrate our approach with a case study based on a disaster recovery scenario, implemented in a prototype simulator that we use to evaluate the performance of a recovery strategy
COBOL to Java and Newspapers Still Get Delivered
This paper is an experience report on migrating an American newspaper
company's business-critical IBM mainframe application to Linux servers by
automatically translating the application's source code from COBOL to Java and
converting the mainframe data store from VSAM KSDS files to an Oracle
relational database. The mainframe application had supported daily home
delivery of the newspaper since 1979. It was in need of modernization in order
to increase interoperability and enable future convergence with newer
enterprise systems as well as to reduce operating costs. Testing the modernized
application proved to be the most vexing area of work. This paper explains the
process that was employed to test functional equivalence between the legacy and
modernized applications, the main testing challenges, and lessons learned after
having operated and maintained the modernized application in production over
the last eight months. The goal of delivering a functionally equivalent system
was achieved, but problems remained to be solved related to new feature
development, business domain knowledge transfer, and recruiting new software
engineers to work on the modernized application.Comment: 4 pages, Accepted to be Published in: Proceedings of the 2018 IEEE
International Conference on Software Maintenance and Evolution (ICSME),
September 23-29, 2018, Madrid, Spai
Engineering Resilient Collective Adaptive Systems by Self-Stabilisation
Collective adaptive systems are an emerging class of networked computational
systems, particularly suited in application domains such as smart cities,
complex sensor networks, and the Internet of Things. These systems tend to
feature large scale, heterogeneity of communication model (including
opportunistic peer-to-peer wireless interaction), and require inherent
self-adaptiveness properties to address unforeseen changes in operating
conditions. In this context, it is extremely difficult (if not seemingly
intractable) to engineer reusable pieces of distributed behaviour so as to make
them provably correct and smoothly composable.
Building on the field calculus, a computational model (and associated
toolchain) capturing the notion of aggregate network-level computation, we
address this problem with an engineering methodology coupling formal theory and
computer simulation. On the one hand, functional properties are addressed by
identifying the largest-to-date field calculus fragment generating
self-stabilising behaviour, guaranteed to eventually attain a correct and
stable final state despite any transient perturbation in state or topology, and
including highly reusable building blocks for information spreading,
aggregation, and time evolution. On the other hand, dynamical properties are
addressed by simulation, empirically evaluating the different performances that
can be obtained by switching between implementations of building blocks with
provably equivalent functional properties. Overall, our methodology sheds light
on how to identify core building blocks of collective behaviour, and how to
select implementations that improve system performance while leaving overall
system function and resiliency properties unchanged.Comment: To appear on ACM Transactions on Modeling and Computer Simulatio
Investigation of a 2-Colour Undulator FEL Using Puffin
Initial studies of a 2-colour FEL amplifier using one monoenergetic electron
beam are presented. The interaction is modelled using the unaveraged, broadband
FEL code Puffin. A series of undulator modules are tuned to generate two
resonant frequencies along the FEL interaction and a self-consistent 2-colour
FEL interaction at widely spaced non-harmonic wavelengths at 1nm and 2.4nm is
demonstrated.Comment: Submitted to The 35th International Free-Electron Laser Conference,
Manhattan, New York (2013
Accident Management in VVER-1000
The present paper deals with the investigation study on accident management in VVER-1000 reactor type conducted in the framework of a European Commission funded project. The mentioned study involved both experimental and computational fields. The purpose of this paper is to summarize the main findings from the execution of a wide-range analysis focused on AM in VVER-1000 with main regard to the qualification of computational tools and the proposal for an optimal AM strategy for this kind of NPP
Recent Advances and Applications of Fractional-Order Neural Networks
This paper focuses on the growth, development, and future of various forms of fractional-order neural networks. Multiple advances in structure, learning algorithms, and methods have been critically investigated and summarized. This also includes the recent trends in the dynamics of various fractional-order neural networks. The multiple forms of fractional-order neural networks considered in this study are Hopfield, cellular, memristive, complex, and quaternion-valued based networks. Further, the application of fractional-order neural networks in various computational fields such as system identification, control, optimization, and stability have been critically analyzed and discussed
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