Protocol combinators for modeling, testing, and execution of distributed systems

2021 ◽  
Vol 31 ◽  
Author(s):  
KRISTOFFER JUST ARNDAL ANDERSEN ◽  
ILYA SERGEY
Keyword(s):  
Distributed Systems ◽  
Message Passing ◽  
State Of The Art ◽  
Bounded Model Checking ◽  
Dynamic Verification ◽  
Programming Framework ◽  
Main Ideas ◽  
User Friendly ◽  
Conference Publication

Abstract Distributed systems are hard to get right, model, test, debug, and teach. Their textbook definitions, typically given in a form of replicated state machines, are concise, yet prone to introducing programming errors if naïvely translated into runnable implementations. In this work, we present Distributed Protocol Combinators (DPC), a declarative programming framework that aims to bridge the gap between specifications and runnable implementations of distributed systems, and facilitate their modeling, testing, and execution. DPC builds on the ideas from the state-of-the art logics for compositional systems verification. The contribution of DPC is a novel family of program-level primitives, which facilitates construction of larger distributed systems from smaller components, streamlining the usage of the most common asynchronous message-passing communication patterns, and providing machinery for testing and user-friendly dynamic verification of systems. This paper describes the main ideas behind the design of the framework and presents its implementation in Haskell. We introduce DPC through a series of characteristic examples and showcase it on a number of distributed protocols from the literature. This paper extends our preceeding conference publication (Andersen & Sergey, 2019a) with an exploration of randomized testing for protocols and their implementations, and an additional case study demonstrating bounded model checking of protocols.

Building Attention and Edge Convolution Neural Networks for Bioactivity and Physical-Chemical Property Prediction

2019 ◽  
Author(s):  
Michael Withnall ◽  
Edvard Lindelöf ◽  
Ola Engkvist ◽  
Hongming Chen
Keyword(s):  
Message Passing ◽  
State Of The Art ◽  
A Priori ◽  
Model Performance ◽  
Learning Approaches ◽  
Physical Chemical ◽  
Chemical Descriptor ◽  
Derived Properties ◽  
Memory Schemes ◽  
Hyperparameter Selection

We introduce Attention and Edge Memory schemes to the existing Message Passing Neural Network framework for graph convolution, and benchmark our approaches against eight different physical-chemical and bioactivity datasets from the literature. We remove the need to introduce <i>a priori</i> knowledge of the task and chemical descriptor calculation by using only fundamental graph-derived properties. Our results consistently perform on-par with other state-of-the-art machine learning approaches, and set a new standard on sparse multi-task virtual screening targets. We also investigate model performance as a function of dataset preprocessing, and make some suggestions regarding hyperparameter selection.

Optimales Layout einer Walderschliessung

2016 ◽  
Vol 167 (5) ◽  
pp. 294-301
Author(s):  
Leo Bont
Keyword(s):  
Road Network ◽  
Spatial Arrangement ◽  
Problem Situation ◽  
Optimal Layout ◽  
Forest Road ◽  
The Road ◽  
Network Cost ◽  
User Friendly ◽  
Short Time

Optimal layout of a forest road network The road network is the backbone of forest management. When creating or redesigning a forest road network, one important question is how to shape the layout, this means to fix the spatial arrangement and the dimensioning standard of the roads. We consider two kinds of layout problems. First, new forest road network in an area without any such development yet, and second, redesign of existing road network for actual requirements. For each problem situation, we will present a method that allows to detect automatically the optimal road and harvesting layout. The method aims to identify a road network that concurrently minimizes the harvesting cost, the road network cost (construction and maintenance) and the hauling cost over the entire life cycle. Ecological issues can be considered as well. The method will be presented and discussed with the help of two case studies. The main benefit of the application of optimization tools consists in an objective-based planning, which allows to check and compare different scenarios and objectives within a short time. The responses coming from the case study regions were highly positive: practitioners suggest to make those methods a standard practice and to further develop the prototype to a user-friendly expert software.

Centrality Measures

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
State Of The Art ◽  
Centrality Measures ◽  
Eigenvector Centrality ◽  
Multilayer Networks ◽  
Comprehensive Description ◽  
Multilayer Network ◽  
Suitable Definition ◽  
Katz Centrality ◽  
Pagerank Centrality

Defining the centrality of nodes and layers in multilayer networks is of fundamental importance for a variety of applications from sociology to biology and finance. This chapter presents the state-of-the-art centrality measures able to characterize the centrality of nodes, the influences of layers or the centrality of replica nodes in multilayer and multiplex networks. These centrality measures include modifications of the eigenvector centrality, Katz centrality, PageRank centrality and Communicability to the multilayer network scenario. The chapter provides a comprehensive description of the research of the field and discusses the main advantages and limitations of the different definitions, allowing the readers that wish to apply these techniques to choose the most suitable definition for his or her case study.

scholarly journals Photovoltaics Enabling Sustainable Energy Communities: Technological Drivers and Emerging Markets

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1862
Author(s):  
Alexandros-Georgios Chronis ◽  
Foivos Palaiogiannis ◽  
Iasonas Kouveliotis-Lysikatos ◽  
Panos Kotsampopoulos ◽  
Nikos Hatziargyriou
Keyword(s):  
State Of The Art ◽  
Research Question ◽  
Economic Benefits ◽  
Energy Market ◽  
Small Scale ◽  
Local Energy ◽  
Community Members ◽  
Open Research ◽  
Energy Community

In this paper, we investigate the economic benefits of an energy community investing in small-scale photovoltaics (PVs) when local energy trading is operated amongst the community members. The motivation stems from the open research question on whether a community-operated local energy market can enhance the investment feasibility of behind-the-meter small-scale PVs installed by energy community members. Firstly, a review of the models, mechanisms and concepts required for framing the relevant concepts is conducted, while a clarification of nuances at important terms is attempted. Next, a tool for the investigation of the economic benefits of operating a local energy market in the context of an energy community is developed. We design the local energy market using state-of-the-art formulations, modified according to the requirements of the case study. The model is applied to an energy community that is currently under formation in a Greek municipality. From the various simulations that were conducted, a series of generalizable conclusions are extracted.

A Simulation Software for the Evaluation of Vulnerabilities in Reputation Management Systems

2021 ◽  
Vol 37 (1-4) ◽  
pp. 1-30
Author(s):  
Vincenzo Agate ◽  
Alessandra De Paola ◽  
Giuseppe Lo Re ◽  
Marco Morana
Keyword(s):  
Quality Of Service ◽  
Distributed Systems ◽  
State Of The Art ◽  
Simulation Software ◽  
Reputation Management ◽  
Management Systems ◽  
Security Attacks ◽  
Vulnerability Evaluation ◽  
Multi Agent

Multi-agent distributed systems are characterized by autonomous entities that interact with each other to provide, and/or request, different kinds of services. In several contexts, especially when a reward is offered according to the quality of service, individual agents (or coordinated groups) may act in a selfish way. To prevent such behaviours, distributed Reputation Management Systems (RMSs) provide every agent with the capability of computing the reputation of the others according to direct past interactions, as well as indirect opinions reported by their neighbourhood. This last point introduces a weakness on gossiped information that makes RMSs vulnerable to malicious agents’ intent on disseminating false reputation values. Given the variety of application scenarios in which RMSs can be adopted, as well as the multitude of behaviours that agents can implement, designers need RMS evaluation tools that allow them to predict the robustness of the system to security attacks, before its actual deployment. To this aim, we present a simulation software for the vulnerability evaluation of RMSs and illustrate three case studies in which this tool was effectively used to model and assess state-of-the-art RMSs.

scholarly journals Sampo-UI: A full stack JavaScript framework for developing semantic portal user interfaces

Semantic Web ◽  
2021 ◽  
pp. 1-16
Author(s):  
Esko Ikkala ◽  
Eero Hyvönen ◽  
Heikki Rantala ◽  
Mikko Koho
Keyword(s):  
User Interfaces ◽  
Linked Data ◽  
State Of The Art ◽  
Software Framework ◽  
End User ◽  
Faceted Search ◽  
Software Developer ◽  
Current State ◽  
Knowledge Graphs ◽  
User Friendly

This paper presents a new software framework, Sampo-UI, for developing user interfaces for semantic portals. The goal is to provide the end-user with multiple application perspectives to Linked Data knowledge graphs, and a two-step usage cycle based on faceted search combined with ready-to-use tooling for data analysis. For the software developer, the Sampo-UI framework makes it possible to create highly customizable, user-friendly, and responsive user interfaces using current state-of-the-art JavaScript libraries and data from SPARQL endpoints, while saving substantial coding effort. Sampo-UI is published on GitHub under the open MIT License and has been utilized in several internal and external projects. The framework has been used thus far in creating six published and five forth-coming portals, mostly related to the Cultural Heritage domain, that have had tens of thousands of end-users on the Web.

scholarly journals How to Use Online Tools to Generate New Hypotheses for Mammary Gland Biology Research: A Case Study for Wnt7b

2021 ◽  
Author(s):  
Yorick Bernardus Cornelis van de Grift ◽  
Nika Heijmans ◽  
Renée van Amerongen
Keyword(s):  
Mammary Gland ◽  
In Silico ◽  
Online Tools ◽  
Mammary Gland Biology ◽  
User Friendly ◽  
In Silico Analyses ◽  
Biology Research ◽  
Selection Of

AbstractAn increasing number of ‘-omics’ datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific ‘-omics’ datasets and thereby expand the in silico toolbox.

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