Clustering Techniques : A solution for e-business

The purpose of this thesis was to provide the best clustering solution for the Archipelago web site project which would have been part of the Central Baltic Intereg IV programme 2007-2013. The entire program is a merger between the central Baltic regions of Finland, including the Åland Islands, Sweden and Estonia. A literature review of articles and research on various clustering techniques for the different sections of the project led to the findings of this document. Clustering was needed for web servers and the underlying database implementation. Additionally, the operating system used for all servers in both sections was required to present the best clustering solution. Implementing OSI layer 7 clustering for the web server cluster, MySQL database clustering and using Linux operating system would have provided the best solution for the Archipelago website. This implementation would have provided unlimited scalability, availability and high performance for the web site. Also, it is the most cost effective solution because it would utilize the commodity hardware

Using Actors to Build a Parallel DBMS

In this paper, we present the design and the architecture of a parallel main memory database management system. We focus on concurrency control scheme and recovery. Our prototype is based on the concept of “database actors”, an object-oriented data model well suited for parallelmanipulations. The storage sub system is built upon distributed Ram-files using SDDS (Scalable Distributed Data Structures) techniques. A nested transaction model is proposed and used to handle concurrency access and recovery. We have also proposed novel approach, based on wait-die, to implement a distributed deadlock prevention technique for our model of nested transactions

Distributed trustworthy sensor data management architecture

Abstract. Growth in Internet of Things (IoT) market has led to larger data volumes generated by massive amount of smart sensors and devices. This data flow must be managed and stored by some data management service. Storing data to the cloud results high latency and need to transfer large amount of data over the Internet. Edge computing operates physically closer to the user than cloud, offering lower latency and reducing data transmission over the network. Going one step forward and storing data locally to the IoT device results smaller latency than cloud and edge computing. Utilizing isolation technique like virtualization enables easy to deploy environment to setup the needed software functionalities. Container technology works well on lightweight hardware as it offers good performance and small overhead. Containers are used to manage server-side services and to give clean environment for each test run. In this thesis two data management platforms, Apache Kafka and MySQL-based MariaDB are tested on a IoT platform. Key performance parameters considered for these platforms are latency and data throughput while also collecting system resource usage data. Variable amount of users and payload sizes are tested and results are presented in graphs. Kafka performed similarly to the SQL-based solution with small differences.Hajautettu luotettava anturidatan hallintajärjestelmä. Tiivistelmä. IoT-markkinoiden kasvu on johtanut suurempien datamäärien luontiin IoT-laitteiden toimesta. Tuo datavirta täytyy hallita and varastoida datan käsittelypalvelun toimesta. Datan tallennus pilvipalveluihin tuottaa suuren latenssin ja tarpeen suurien datamäärien siirrolle Internetin yli. Fyysisesti lähempänä loppukäyttäjää oleva reunapalvelu tarjoaa pienemmän latenssin ja vähentää siirrettävän datan määrää verkon yli. Kun palvelu tuodaan vielä askel lähemmäksi, päästään paikalliseen palveluun, mikä saavuttaa vielä pienemmän latenssin kuin pilvi- ja reunapalvelut. Virtualisointitekniikka mahdollistaa helposti jaettavan ympäristön käyttöönottoa, mikä mahdollistaa tarvittavien ohjelmiston toimintojen asennuksen. Virtualisointitekniikoista kontit nousivat muiden edelle, koska IoT-laitteet omaavat suhteellisesti vähän muistia ja laskentatehoa. Kontteja käytetään palvelinpuolen palveluiden hallintaan sekä tarjoamaan puhtaan vakioidun ympäristön jokaiselle testikierrokselle. Tämä diplomityö käsittelee kahden tiedonhallinta-alustan: Apache Kafka ja MySQL pohjaisen MariaDB-tietokannan suorituskykyeroja IoT-alustan päällä. Kerätyt suorituskykymittaukset ovat latenssi ja tiedonsiirtonopeus mitaten samalla järjestelmän resurssien käyttöasteita. Vaihtelevia määriä käyttäjiä ja hyötykuormia testataan ja tulokset esitetään graafeissa. Kafka suoriutui yhtä hyvin kuin SQL ohjelmisto näissä testeissä, mutta pieniä eroja näiden välillä havaittiin

Database Paradigms for Recordings Management

The relational database has long been considered the de facto standard for managing data in software applications. Today, a need for more scalable, flexible and distributed software solutions has led to the development of NoSQL database technologies that aim to replace the relational database in applications where such features are needed. In this thesis we have investigated the potential benefits of replacing SQLite, the database used by Axis Communications to manage recordings in their camera products, with a “Not only SQL” (NoSQL) database in an embedded camera system. To evaluate performance, test cases to measure execution times and resource consumption for database operations, based on important functionality in Axis’ storage solution, were designed. In the end the Embedded JSON Database Engine (EJDB) document database was identified. EJDB was found to be more efficient than SQLite at creating, updating and removing records. It was, however, less efficient when perform- ing queries based on conditional operators

Automated Dynamic Firmware Analysis at Scale: A Case Study on Embedded Web Interfaces

Embedded devices are becoming more widespread, interconnected, and web-enabled than ever. However, recent studies showed that these devices are far from being secure. Moreover, many embedded systems rely on web interfaces for user interaction or administration. Unfortunately, web security is known to be difficult, and therefore the web interfaces of embedded systems represent a considerable attack surface. In this paper, we present the first fully automated framework that applies dynamic firmware analysis techniques to achieve, in a scalable manner, automated vulnerability discovery within embedded firmware images. We apply our framework to study the security of embedded web interfaces running in Commercial Off-The-Shelf (COTS) embedded devices, such as routers, DSL/cable modems, VoIP phones, IP/CCTV cameras. We introduce a methodology and implement a scalable framework for discovery of vulnerabilities in embedded web interfaces regardless of the vendor, device, or architecture. To achieve this goal, our framework performs full system emulation to achieve the execution of firmware images in a software-only environment, i.e., without involving any physical embedded devices. Then, we analyze the web interfaces within the firmware using both static and dynamic tools. We also present some interesting case-studies, and discuss the main challenges associated with the dynamic analysis of firmware images and their web interfaces and network services. The observations we make in this paper shed light on an important aspect of embedded devices which was not previously studied at a large scale. We validate our framework by testing it on 1925 firmware images from 54 different vendors. We discover important vulnerabilities in 185 firmware images, affecting nearly a quarter of vendors in our dataset. These experimental results demonstrate the effectiveness of our approach