On the Behaviour of General-Purpose Applications on Cloud Storages

Managing data over cloud infrastructures raises novel challenges with respect to existing and well studied approaches such as ACID and long running transactions. One of the main requirements is to provide availability and partition tolerance in a scenario with replicas and distributed control. This comes at the price of a weaker consistency, usually called eventual consistency. These weak memory models have proved to be suitable in a number of scenarios, such as the analysis of large data with Map-Reduce. However, due to the widespread availability of cloud infrastructures, weak storages are used not only by specialised applications but also by general purpose applications. We provide a formal approach, based on process calculi, to reason about the behaviour of programs that rely on cloud stores. For instance, one can check that the composition of a process with a cloud store ensures `strong' properties through a wise usage of asynchronous message-passing

Contemporary geomorphological activity throughout the proglacial area of an alpine catchment

Quantification of contemporary geomorphological activity is a fundamental prerequisite for predicting the effects of future earth surface process and landscape development changes. However, there is a lack of high-resolution spatial and temporal data on geomorphological activity within alpine catchments, which are especially sensitive to climate change, human impacts and which are amongst the most dynamic landscapes on Earth. This study used data from repeated laser scanning to identify and quantify the distribution of contemporary sediment sources and the intensity of geomorphological activity within the lower part of a glaciated alpine catchment; Ödenwinkelkees, central Austria. Spatially, geomorphological activity was discriminated by substrate class. Activity decreased in both areal extent and intensity with distance from the glacier, becoming progressively more restricted to the fluvially-dominated valley floor. Temporally, geomorphological activity was identified on annual, seasonal, weekly and daily timescales. Activity became more extensive with increasing study duration but more intense over shorter timescales, thereby demonstrating the importance of temporary storage of sediment within the catchment. The mean volume of material moved within the proglacial zone was 4400m.yr, which suggests a net surface lowering of 34mm.yr in this part of the catchment. We extrapolate a minimum of 4.8mm.yr net surface lowering across the whole catchment. These surface lowering values are approximately twice those calculated elsewhere from contemporary measurements of suspended sediment flux, and of rates calculated from the geological record, perhaps because we measure total geomorphological activity within the catchment rather than overall efflux of material. Repeated geomorphological surveying therefore appears to mitigate the problems of hydrological studies underestimating sediment fluxes on decadal-annual time-scales. Further development of the approach outlined in this study will enable the quantification of geomorphological activity, alpine terrain stability and persistence of landforms

Measuring and Querying Process Performance in Supply Chains: An Approach for Mining Big-Data Cloud Storages

AbstractSurvival in today's global environment means continuously improving processes, identifying and eliminating inefficiencies wherever they occur. With so many companies operating as part or all of complex distributed supply chain, gathering, collating and analyzing the necessary data to identify such improvement opportunities is extremely complex and costly. Although few solutions exist to correlate the data, it continues to be generated in vast quantities, rendering the use of highly scalable, cloud-based solutions for process analysis a necessity. In this paper we present an overview of an analytical framework for business activity monitoring and analysis, which has been realized using extremely scalable, cloud-based technologies. It provides a low-latency solution for entire supply chains or individual nodes in such chains to query process data stores in order to deliver business insight. A custom query language has been implemented which allows business analysts to design custom queries on processes and activities based on a standard set of process metrics. Ongoing developments are focused on testing and improving the scalability and latency of the system, as well as extending the query engine to increase its flexibility and performance

IoT-teknologian hyödyntäminen sähköverkko-omaisuuden hallinnassa

Objective of this thesis is to define and assess changes in energy sector, which will directly or indirectly affect distribution grid operation and management in Finland, and to determine measurable events or variables, which enable identification and monitoring of the recognized changes. Based on assessment of the upcoming changes, possibilities for utilizing IoT technologies in management and monitoring applications of the identified changes, are assessed. In the assessment of upcoming changes, total of eight subjects were covered and microgeneration, electric vehicles and heat pumps were identified to be the most probable changes to realistically penetrate Finnish energy sector within a time scope of approximately 10 years. However, none of the assessed, changes, were found to have significant and wide-scale effects in terms of performance of Finnish distribution networks. For utilization of IoT technologies in distribution networks one application for operational grid monitoring of power quality problems derived from residential photovoltaic generation, and three cases for IoT based asset health and condition monitoring were assessed. Furthermore, requirements and architecture for data storage and analysis platform of IoT based system were discussed. From the evaluated applications condition monitoring scheme of circuit breakers was determined to be the most promising alternative.Diplomityön tavoitteena on määritellä ja arvioida energiasektoriin vaikuttavien tulevien muutosten suoria tai epäsuoria vaikutuksia jakeluverkon toimintaan ja hallintaan. Havaittujen muutosten vaikutuksista on tarkoitus tunnistaa mitattavia ilmiöitä tai suureita, jotka mahdollistavat muutosten tunnistamisen sekä seurannan. Muutosanalyysiin pohjautuen tavoitteena on tunnistaa ja arvioida mahdollisuuksia IoT-teknologian hyödyntämiseksi havaittujen muutosten aiheuttamien ongelmakohtien tai mahdollisuuksien tunnistamisessa, seurannassa sekä hallinnassa. Energiasektoriin vaikuttavien muutosten analyysissä arvoitiin kokonaisuudessaan kahdeksaa eri aihealuetta ja lopputuloksena pientuotannon, sähköautojen sekä lämpöpumppujen todettiin olevan todennäköisimmät teknologiat, jotka yleistyvät merkittävissä määrin suomalaisessa sähköverkossa seuraavan kymmenen vuoden aikana. Minkään käsitellyn muutoskohdan ei kuitenkaan todettu aiheuttavan laajamittaisia ja merkittäviä ongelmia jakeluverkon toimintaan. IoT-teknologian hyödyntämiseen jakeluverkkotoiminnassa käsiteltiin yhtä verkon käyttöön ja sähkön laatuun liittyvää sovellusta, jonka avulla hajautetun pienaurinkotuotannon vaikutuksia pystytään seuraamaan, sekä lisäksi kolmeen eri verkkokomponenttiin kohdistuvaa jatkuvan kunnon seurannan sovellusta. Tämän lisäksi IoT-järjestelmän toteuttamiseksi vaadittavalle analyysi- ja tietojärjestelmäalustalle määriteltiin rakenteellisia ja toiminnallisia tarpeita. Työssä käsitellyistä IoT-sovelluksista lupaavimmaksi todettiin katkaisijoihin kohdistuva jatkuvan kunnonhallinnan sovellus

A novel energy management framework incorporating multi-carrier energy hub for smart city

The development of advanced and intelligent measurement instruments in recent years has increased the intelligence of modern energy systems, especially power systems. Besides, with the advancement of energy conversion technologies, these systems benefit from multi-carrier energy resources. Accordingly, this paper presents a model of smart city which considers various components, including smart transportation system (STS), microgrid (MG), and smart energy hub (SEH) with the ability of energy transformation. The proposed model addresses the islanded operation of a smart city that makes it a smart island. This island deploys the energy carriers of electricity, heat, gas and water as well. In addition, STS includes electric vehicle (EV) parking lots as well as metro system (MS) that can interactively exchange energy. More precisely, the different components of the smart island are modelled on the assumption of energy interdependency. In the proposed model, the water supply unit in SEH is provided which can be effective in reducing the cost of components by supplying water to them. In order to exchange energy within STS, metro stations have been optimally allocated using intelligent water drops (IWD) optimization method. In addition to smart island modelling, this paper quantifies the uncertainties within STS and MG using cloud theory. Eventually, the proposed model is simulated to ensure its effectiveness and accuracy.© 2022 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.fi=vertaisarvioitu|en=peerReviewed

Mobile Autonomous Sensing Unit (MASU): a framework that supports distributed pervasive data sensing

Pervasive data sensing is a major issue that transverses various research areas and application domains. It allows identifying people’s behaviour and patterns without overwhelming the monitored persons. Although there are many pervasive data sensing applications, they are typically focused on addressing specific problems in a single application domain, making them difficult to generalize or reuse. On the other hand, the platforms for supporting pervasive data sensing impose restrictions to the devices and operational environments that make them unsuitable for monitoring loosely-coupled or fully distributed work. In order to help address this challenge this paper present a framework that supports distributed pervasive data sensing in a generic way. Developers can use this framework to facilitate the implementations of their applications, thus reducing complexity and effort in such an activity. The framework was evaluated using simulations and also through an empirical test, and the obtained results indicate that it is useful to support such a sensing activity in loosely-coupled or fully distributed work scenarios.Peer ReviewedPostprint (published version