Semantic Support for Log Analysis of Safety-Critical Embedded Systems

Testing is a relevant activity for the development life-cycle of Safety Critical Embedded systems. In particular, much effort is spent for analysis and classification of test logs from SCADA subsystems, especially when failures occur. The human expertise is needful to understand the reasons of failures, for tracing back the errors, as well as to understand which requirements are affected by errors and which ones will be affected by eventual changes in the system design. Semantic techniques and full text search are used to support human experts for the analysis and classification of test logs, in order to speedup and improve the diagnosis phase. Moreover, retrieval of tests and requirements, which can be related to the current failure, is supported in order to allow the discovery of available alternatives and solutions for a better and faster investigation of the problem.Comment: EDCC-2014, BIG4CIP-2014, Embedded systems, testing, semantic discovery, ontology, big dat

How blockchain impacts cloud-based system performance: a case study for a groupware communication application

This paper examines the performance trade-off when implementing a blockchain architecture for a cloud-based groupware communication application. We measure the additional cloud-based resources and performance costs of the overhead required to implement a groupware collaboration system over a blockchain architecture. To evaluate our groupware application, we develop measuring instruments for testing scalability and performance of computer systems deployed as cloud computing applications. While some details of our groupware collaboration application have been published in earlier work, in this paper we reflect on a generalized measuring method for blockchain-enabled applications which may in turn lead to a general methodology for testing cloud-based system performance and scalability using blockchain. Response time and transaction throughput metrics are collected for the blockchain implementation against the non-blockchain implementation and some conclusions are drawn about the additional resources that a blockchain architecture for a groupware collaboration application impose

Assessing the vulnerabilities and securing MongoDB and Cassandra databases

Due to the increasing amounts and the different kinds of data that need to be stored in the databases, companies, and organizations are rapidly adopting NoSQL databases to compete. These databases were not designed with security as a priority. NoSQL open-source software was primarily developed to handle unstructured data for the purpose of business intelligence and decision support. Over the years, security features have been added to these databases but they are not as robust as they should be, and there is a scope for improvement as the sophistication of the hackers has been increasing. Moreover, the schema-less design of these databases makes it more difficult to implement traditional RDBMS like security features in these databases. Two popular NoSQL databases are MongoDB and Apache Cassandra. Although there is a lot of research related to security vulnerabilities and suggestions to improve the security of NoSQL databases, this research focusses specifically on MongoDB and Cassandra databases. This study aims to identify and analyze all the security vulnerabilities that MongoDB and Cassandra databases have that are specific to them and come up with a step-by-step guide that can help organizations to secure their data stored in these databases. This is very important because the design and vulnerabilities of each NoSQL database are different from one another and hence require security recommendations that are specific to them

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Back-end reference architecture for smart water meter data gathering service

Abstract. The Finnish waterworks industry is on the brink of digitalization. Currently, many of them have started to convert their water meters to smart water meters. However, there is yet no suitable solution for gathering the IoT data from these smart water meters. To answer their arising needs, many pilots and workshops have been conducted. Those pilots have yielded some basic ground rules for their use cases. In this study, those ground rules have been gathered as a set of requirement categories. The categories are studied and analyzed in order to establish a reference architecture for IoT data-gathering systems suitable for waterworks. Using the requirements and the reference architecture, an information system, Dataservice, was implemented by Vesitieto Oy. The system gathers the IoT data and visualizes it to waterworks’ employees. The System was deployed in Microsoft’s cloud service, but other cloud vendors were examined as well. The system has a two-folded database system, the data required by the system, like users and user groups, are held in the SQL database. The IoT-data is held in a NoSQL database. The selected NoSQL database provider was MongoDB as it could be integrated with the cloud provider.Etäluettavien vesimittareiden datapalvelun viitearkkitehtuuri. Tiivistelmä. Suomen vesihuolto on digitalisaation partaalla. Tällä hetkellä monet vesilaitokset ovat alkaneet vaihtaa vanhoja analogisia vesimittareitaan älykkäiksi vesimittareiksi. Vesihuoltolaitokset eivät kuitenkaan ole löytäneet kaikille sopivaa ratkaisua IoT-tiedon keräämiseen älykkäistä vesimittareista. Vastatakseen vesilaitosten tarpeisiin, monia pilotteja ja työpajoja on järjestetty eri yhteistyökumppaneiden kanssa. Näistä eri piloteista on muodostunut käsitys siitä, kuinka vesimittareiden digitalisaatio voidaan ratkaista vesilaitoksilla. Tässä tutkimuksessa eri laitosten väliset perussäännöt on koottu ohjelmistovaatimusluokiksi. Näitä luokkia tutkitaan ja analysoidaan vesilaitoksille sopivan IoT-tiedonkeruujärjestelmän viitearkkitehtuurin luomiseksi. Vaatimuksia ja viitearkkitehtuuria hyödyntäen Vesitieto Oy toteutti tietojärjestelmän nimeltään ”Dataservice”. Järjestelmä kerää IoT-tiedot ja visualisoi ne vesilaitosten työntekijöille. Järjestelmä otettiin käyttöön Microsoftin pilvipalvelussa, mutta myös muita pilvipalvelun palveluntarjoajia tutkittiin. Järjestelmässä on kaksiportainen tietokantajärjestelmä. Järjestelmän tarvitsemat tiedot kuten käyttäjät sekä käyttäjäryhmät pidetään SQLtietokannassa ja IoT-tiedot pidetään NoSQL-tietokannassa. Valittu NoSQL tietokantajärjestelmä oli MongoDB, koska se voitiin integroida pilvipalveluntarjoajan kanssa

Designing a Modern Software Engineering Training Program with Cloud Computing

The software engineering industry is trending towards cloud computing. For our project, we assessed the various tools and practices used in modern software development. The main goals of this project were to create a reference model for developing cloud-based applications, to program a functional cloud-based prototype, and to develop an accompanying training manual. These materials will be incorporated into the software engineering courses at WPI, namely CS 3733 and CS 509