Electronic Communications of the EASST (European Association of Software Science and Technology)
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Molecular Communication Channel Modelling in FPGA Technology
Full text linkMolecular Communication (MC) is a new paradigm for communication processes with a variety of applications such as health care and industrial sectors. The rapid development of MC, with the support of testbeds and simulators, requires scalable modeling tools. In this paper, we propose a field-programmable gate array (FPGA) design-based approach for the emission, diffusion, and reception of molecules. Results exhibit a close correspondence to state of the art analytical modeling of MC processes
Towards Deterministic Reconfigurable Networks
Full text linkCompared with legacy networks, programmable networks are highlyflexible and need to be reconfigured dynamically. In this early work paper, we studythe fast and consistent network update which is the key enabler to realize deterministicreconfigurable networks. The reconfiguration speed is one side of the coin. Theongoing best-effort traffic cannot be interrupted during the network reconfigurationas well. In terms of reconfiguration speed, we implement and compare our methodwith the state-of-the-art decentralized and centralized update methods
Information Management for Multi-Agent Systems
Full text linkMulti-Agent Systems (MAS) are becoming increasingly popular in large-scale dynamic domains such as Smart Cities and Search \& Rescue (S\&R) missions. In order for agents to cooperate efficiently in such domains, they need to distribute tasks, share knowledge, resolve conflicts, incorporate unknown agents, assign roles among each other, assign and keep track of teams of agents, etc. The cooperation in such dynamic domains requires both a software platform that supports the interoperability of cyber-physical agents as well as a shared Knowledge Base that stores general semantic information about the entities of discourse as well as live status information. ALICA, which is an in-house Multi-Agent platform, addresses such domains and is well suited to tackle a lot of these problems. To further enhance its capabilities, an extension is planned in order to integrate the standardised context information interface NGSI-LD as well as the widely used FIWARE models and components for Smart Cities, which enables the management of static and dynamic context information in normal and crisis situations
Congestion Aware Objects Filtering for Collective Perception
Full text linkThis paper addresses collective perception for connected and automated driving. It proposes the adaptation of filtering rules based on the currently available channel resources, referred to as Enhanced DCC-Aware Filtering (EDAF)
Demo: Simulation-as-a-Service to Benchmark Opportunistic Networks
Full text linkRepeatability, reproducibility, and replicability are essential aspects of experimental and simulation-driven research. Use of benchmarks in such evaluations further assists corroborative performance evaluations. In this work, we present a demonstrator of a simulation service, called ”OPS on the bench” which tackles these challenges in performance evaluations of opportunistic networks
Federated User Clustering for non-IID Federated Learning
Full text linkFederated Learning (FL) is one of the leading learning paradigms for enabling a more significant presence of intelligent applications in networking considering highly distributed environments while preserving user privacy.However, FL has the significant shortcoming of requiring user data to be Independent Identically Distributed (IID) to make reliable predictions for a given group of users.We present a Neural Network-based Federated Clustering mechanism capable of clustering the local models trained by users of the network with no access to their raw data.We also present an alternative to the FedAvg aggregation algorithm used in traditional FL, which significantly increases the aggregated models' reliability in Mean Square Error by creating several training models over IID users
Evolve: Language-Driven Engineering in Industrial Practice
Full text linkIn general software projects still, have a very high failure rate. We noticed that one of our projects did not gather pace. It was delayed from the beginning and on the way to fail. After investigating the development process, we located the issue in the chosen architecture of the software. Although the used technology has many advantages, it handicapped the application developers by the cumbersome architecture. The challenge was how we could keep the advantages, but simplify the work of the application developers. We came up with the approach to build a toolkit and family of dedicated Domain-Specific Languages which is developed alongside the project. We called it Evolve, and it is built upon the Language-Driven Engineering paradigm. We were able to salvage the project and establish Evolve in the development process of related applications. With Evolve we successfully brought Language-Driven Engineering to industrial practice. It will play a major role in our future software development
Guidance in Model-based Compilations
Full text linkThe modeler should not be burdened with maintaining an overview over all potential conflicts. They should further be able to understand what is happening. Model-based compilers and modeling tools in general should guide a modeler.The KIELER Compiler constructs transformation snapshots and augmented models automatically during compilation. We demonstrate six different transient views that can help the modeler to refine their models and to solve modeling issues, such as causality problems in synchronous languages
Thoughts about using Constraint Solvers in Action
Full text linkSMT solvers power many automated security analysis tools today. Nevertheless, a smooth integration of SMT solvers into programs is still a challenge that lead to different approaches for doing it the right way. In this paper, we review the state of the art for interacting with constraint solvers. Based on the different ideas found in literature we deduce requirements for a constraint solving service simplifying the integration challenge. We identify that for some of those ideas, it is required to run large scale experiments for evaluating some of the ideas behind the requirements empirically. We show that the platform is capable of running such an experiment for the case of measuring the impacts of seeds on the solver runtime
Workflow Discovery with Semantic Constraints: The SAT-Based Implementation of APE
Full text linkScience today is increasingly computational, and many researchers regularly face the need of creating purpose-specific computational pipelines for their specific data analysis problems. The manual composition and implementation of such workflows regularly costs valuable research time. Hence, many scientists wish for a system that would only require an abstract description of their intended data analysis process, and from there automatically compose and implement suitable workflows. In this paper we describe APE (the Automated Pipeline Explorer), a new implementation of a synthesis-based workflow discovery framework that aims to accomplish such automated composition. The framework captures the required technical domain knowledge in the form of tool and type taxonomies and functional tool annotations. Based on this semantic domain model, the framework allows users to specify their intents about workflows at an abstract, conceptual level in the form of natural-language templates. Internally, APE maps them to a temporal logic and translates them into a propositional logic instance of the problem that can be solved by an off-the-shelf SAT solver. From the solutions provided by the solver, APE then constructs executable workflow implementations. First applications of APE on realistic scientific workflow scenarios have shown that it is able to efficiently synthesize meaningful workflows. We use an example from the geospatial application domain as a running example in this paper