INTELLIGENT DISTRIBUTED DYNAMIC FOG COMPUTING FRAMEWORK

Одним из направлений развития сетей связи 5G и сетей связи 2030 является интегрирование в сеть распределенных вычислительных структур, таких как системы пограничных и туманных вычислений (Fog), которые призваны выполнить децентрализацию вычислительной части сетей. В связи с этим необходимо исследовать и определить принципы предоставления услуг на основе распределенной вычислительной инфраструктуры, в том числе в условиях ограниченности ресурсов отдельно взятых составных частей (Fog-устройства). Предлагается новый фреймворк распределенной динамической вычислительной системы туманных вычислений на основе микросервисного архитектурного подхода к реализации, развертыванию и миграции программного обеспечения предоставляемых услуг. Исследуется типовая архитектура микросервисного подхода и ее имплементация в туманные вычисления, а также рассматриваются два алгоритма: алгоритм K-средних для нахождения центра пользовательской нагрузки и алгоритм роевой оптимизации для определения устройства тумана с необходимыми характеристиками для последующей миграции микросервиса. One of the directions of 5G and 2030 communications networks development is the network-integrated distributed structures, such as edge computing (MEC) and Fog computing, which are designed to decentralize the computing part of networks. In this regard, it is necessary to investigate and determine the principles of providing services based on a distributed computing infrastructure, including in conditions of limited resources of individual components (Fog devices). This article proposes a new framework for a distributed dynamic computing system of fog computing based on a microservice architectural approach to the implementation, deployment, and software migration of the services. The article examines the typical architecture of the microservice approach and its implementation in fog computing, and also investigates two algorithms: K-means for finding the center of user load, swarm optimization (PSO) to determine the fog device with the necessary characteristics for the subsequent migration of the microservice.

Software migration of the CMS ECAL Detector Control System during the CERN Large Hadron Collider Long Shutdown II

During the second long shutdown (LS2) of the CERN Large Hadron Collider (LHC), the Detector Control System (DCS) of the Compact Muon Solenoid (CMS) Electromagnetic Calorimeter (ECAL) is undergoing a large software upgrade at various levels. The ECAL DCS supervisory system has been reviewed and extended to migrate the underlying software toolkits and platform technologies to the latest versions. The resulting software will run on top of a new computing infrastructure, using the WinCC Open Architecture (OA) version 3.16 and newly developed communication drivers for some of the hardware. The ECAL DCS has been configured and managed from a different control version system and stored with more modern encoding and file formats. A new set of development guidelines has been prepared for this purpose, including conventions and recommendations from the CMS Central DCS and CERN Joint Controls Project (JCOP) framework groups. The large list of modifications also motivated the revision and reorganization of the software architecture, which is needed to resolve and satisfy additional software dependencies. Many modifications also aimed to improve the installation process, anticipating in some cases works for the next long shutdown upgrade.