AUTO-SCALING AND ADJUSTMENT PLATFORM FOR CLOUD-BASED SYSTEMS

For customers of cloud-computing platforms it is important to minimize the infrastructure footprint and associated costs while providing required levels of Quality of Service (QoS) and Quality of Experience (QoE) dictated by the Service Level Agreement (SLA). To assist with that cloud service providers are offering: (1) horizontal resource scaling through provisioning and destruction of virtual machines and containers, (2) vertical scaling through changing the capacity of individual cloud nodes. Existing scaling solutions mostly concentrate on low-level metrics like CPU load and memory consumption which doesn’t always correlate with the level of SLA conformity. Such technical measures should be preprocessed and viewed from a higher level of abstraction. Application level metrics should also be considered when deciding upon scaling the cloud-based solution. Existing scaling platforms are mostly proprietary technologies owned by cloud service providers themselves or by third parties and offered as Software as a Service. Enterprise applications could span infrastructures of multiple public and private clouds, dictating that the auto-scaling solution should not be isolated inside a single cloud infrastructure. The goal of this paper is to address the challenges above by presenting the architecture of Auto-scaling and Adjustment Platform for Cloud-based Systems (ASAPCS). It is based on open-source technologies and supports integration of various low and high level performance metrics, providing higher levels of abstraction for design of scaling algorithms. ASAPCS can be used with any cloud service provider and guarantees that move from one cloud platform to another will not result in complete redesign of the scaling algorithm. ASAPCS itself is horizontally scalable and can process large amounts of real-time data which is particularly important for applications developed following the microservices architectural style. ASAPCS approaches the scaling problem in a nonstandard way by considering real-time adjustments of the application logic to be part of the scalability strategy if it can result in performance improvements

ON INTEGRATION OF EVOLVING INFRASTRUCTURE TOPOLOGY GRAPHS AND METRIC DATA STREAMS IN INFORMATION TECHNOLOGY INFRASTRUCTURE MANAGEMENT

Modern cloud-based information technology (IT) infrastructure monitoring context and data are gathered from various systems. Typical monitoring systems provide a set of metrics characterizing the performance and health of a variety of infrastructure components. To understand the dependencies and relations among these measurements, the infrastructure topology can be analysed to provide context to the monitoring metrics. However, the metrics and the topology are updated at different time intervals and providing continuous merging and analysis of both data sets is a challenging task which is rarely addressed in the scientific literature. The paper elaborates a method for integration of infrastructure topology graph and monitoring metric data streams. The method is intended for application in the identification of anomalies in IT infrastructure.

Proceedings of the workshops co-organized with the 13th IFIP WG 8.1 working conference on the Practice of Enterprise Modelling (PoEM 2020)

Workshops co-organized with the 13th IFIP WG 8.1 working conference on the Practice of Enterprise Modellin

Capability driven development: an approach to designing digital enterprises

The final publication is available at Springer via http://dx.doi.org/10.1007/s12599-014-0362-0[EN] The need for organizations to operate in changing environments is addressed by proposing an approach that integrates organizational development with information system (IS) development taking into account changes in the application context of the solution. This is referred to as Capability Driven Development (CDD). A meta-model representing business and IS designs consisting of goals, key performance indicators, capabilities, context and capability delivery patterns, is being proposed. The use of the meta-model is validated in three industrial case studies as part of an ongoing collaboration project, whereas one case is presented in the paper. Issues related to the use of the CDD approach, namely, CDD methodology and tool support are also discussed.This work has been partially supported by the EU-FP7 funded project no: 611351 CaaS - Capability as a Service in Digital Enterprises.Berzisa, S.; Bravos, G.; Cardona Gonzalez, T.; Czubayko, U.; España, S.; Grabis, J.; Henkel, M.... (2015). Capability driven development: an approach to designing digital enterprises. Business and Information Systems Engineering. 57(1):15-25. https://doi.org/10.1007/s12599-014-0362-0S1525571ArchiMate (2013) An enterprise modeling language from the Open Group. http://www.opengroup.org/archimate/ . Accessed 3 Dec 2014Asadi M, Ramsin R (2008) MDA-based methodologies: an analytical survey. In: Proceedings Model driven architecture – foundations and applications (ECMDA-FA 2008), LNCS 5095, pp 419–431Barney JB (1991) Firm resources and sustained competitive advantage. 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Globālās pozicionēšanas datu integrēšana uzņēmuma informācijas sistēmā

Rakstā ir apkopoti maģistra darbā veikto pētījumu rezultāti. Darbā tika apskatītas GPS datu izmantošanas iespējas uzņēmumā un iespējamās lietojumprogrammu integrācijas tehnoloģijas un paņēmieni, ar kuru palīdzību varētu realizēt GPS/GIS sistēmu sasaisti ar uzņēmumā esošajām sistēmām, kā arī tika izstrādāts praktisks piemērs GPS/GIS sistēmas integrēšanai uzņēmuma informācijas sistēmā. Tika definētas prasības funkcionālajam GPS/GIS adapterim un darba rezultātā tika iegūta funkcionālā GPS/GIS adaptera arhitektūra un izstrādāts adaptera prototips

Spatial Data Integration Approach with Application in Facility Location

Complex decision-making problem, require large amount of data, and data gathering is one of the most complex tasks in the modeling process. Web services and XML are among the most promising technologies for retrieving data from distributed data sources over the Internet. However, different standards are used for providing spatial and non-spatial data, and data retrieval quality of service attributes vary substantially. The objective of this paper is to propose a spatial data integration architecture, which supports data retrieval from heterogeneous, distributed data sources and accounts for quality of service requirements. Application of the integration architecture is demonstrated using a facility location decision-making problem, which requires such spatial data as distances, customer densities and location of competitors. Computational studies are conducted to evaluate data retrieval time and to identify hidden characteristics of different data sources

On-demand Data Integration for Decision-making Applications

Decision-making efficiency depends upon timely availability of appropriate data. On-demand data integration from web based data sources provides an attractive solution to data gathering. The two major challenges associate with on-demand data integration are selection of appropriate data services and efficient implementation of the data integration process. In this paper, it is proposed to use service’s business value as a service selection criterion and to elaborate a lightweight method for XML based definition of the integration processes. The business value driven approach implies that services are selected according to their impact on quality of decisions made rather than solely according to their QoS characteristics. The data integration process definition methods partitions the data integration process into atomic data integration tasks, thus allowing for high level of data retrieval parallelization, accommodating data interdependencies and enabling error recoverability without delaying the whole data integration process. The data integration methods are evaluated using a case study, which investigates on-line decision making at a taxi company

Pieprasījuma datu integrācijas risinājumi attāliem datu avotiem

Lēmumpieņemšanas problēmu risināšanā bieži ir nepieciešams liels sākotnējo datu apjoms no dažādiem datu avotiem. Datu noliktavas ir tradicionālais datu integrācijas risinājums, ko izmanto, lai iegūtu un apkopotu vajadzīgos datus. Ja datu avoti atrodas ārpus uzņēmuma robežām, tad datu noliktavā tiek saglabāta pilna ārējo datu kopa. Datu glabāšanai ir nepieciešama sarežģīta infrastruktūra un jānodrošina regulāra datu atjaunošana. Alternatīva lokālām ārējo avotu datu kopijām ir datu servisu jeb tīmekļa pakalpju izmantošana, izgūstot tikai konkrētajai lēmumpieņemšanas problēmai vajadzīgos datus tad, kad tas ir nepieciešams. Šajā gadījumā aktuāla ir datu integrācijas procesa efektivitāte, piekļuves nodrošināšana heterogēnām pakalpēm (t.i., servisiem, kuru izstrādē izmantoti atšķirīgi standarti, atšķiras to komunikācijas protokoli, datu modeļi), datu transformēšana un dažādo datu kopu integrēšana. Promocijas darba mērķis ir izstrādāt pieprasījuma datu integrācijas risinājumus, kas nodrošinātu datu izgūšanu no attāliem, heterogēniem datu avotiem un transformētu datus nepieciešamajā formā. Darbā ir izstrādāts attālu avotu pieprasījuma datu integrācijas sistēmas modelis, definētas prasības un, balstoties uz tām, izstrādāta attālu avotu pieprasījuma datu integrācijas sistēmas tehniskā arhitektūra un metodes datu integrācijas procesa efektivitātes paaugstināšanai, izveidots sistēmas prototips. Arhitektūrā iekļautie risinājumi ir praktiski novērtēti. Galvenie ieguvumi ir datu integrācijas procesa paātrināšana un vieglāk uzturams, modificējams datu integrācijas risinājums. Tiek nodrošināta datu izgūšana no heterogēnām, attālām tīmekļa pakalpēm, tīmekļa pakalpju aizstāšana izmaiņu un atteikumu gadījumā, slodzes līdzsvarošana starp funkcionāli līdzvērtīgām tīmekļa pakalpēm, sarežģītu datu integrācijas uzdevumu savstarpējo atkarību ievērošana un datu integrācijas uzdevumu paralelizācija. Pētījuma zinātnisko ieguldījumu veido: 1.Jaunas attālu avotu datu integrācijas metodes izstrāde, kas balstās uz abstrakcijas izmantošanu tīmekļa pakalpju metožu līmenī un datu integrācijas procesa nodalīšanu no tīmekļa pakalpju piekļuves loģikas. 2.Uz nefunkcionālām un funkcionālām prasībām balstīta adaptīva tīmekļa pakalpju izvēles un slodzes līdzsvarošanas algoritma izstrāde. 3.Algoritma, kas nodrošina attālu avotu datu integrācijas procesu veidojošo uzdevumu pareizu un savlaicīgu izpildi, izstrāde. 4.Izstrādāto risinājumu efektivitātes novērtējums. Izstrādātās arhitektūras implementācija ir izmantota objekta izvietošanas un pasažieru pārvadājumu plānošanas problēmu risināšanā. Promocijas darbs satur ievadu, 5 nodaļas, secinājumus, 5 pielikumus, literatūras sarakstu (174 nosaukumi), 75 attēlus un 26 tabulas, kopā 165 lappuses

A Methodology for Integration of Spatial Data in Enterprise Applications

Use of spatial data provided by Global Positioning System (GPS) and Geographical Information Systems (GIS) is important in many decision-making areas, for instance, fleet management and transportation routing. However, efficient decision-making requires using both spatial data and data stored in other enterprise applications. This paper proposes a web-services and executable business process based methodology for integrating GPS, GIS and enterprise applications such as enterprise resource planning systems. Architecture for implementation of the methodology and a sample integrated solution are also presented