Development of an Ecology-Oriented Software-Defined Networking Framework

ICT contributed to about 0.83 GtCO2 emissions where the 37% comes from the telecoms infrastructures. At the same time, the increasing cost of energy has been hindering the industry in providing more affordable services for the users. One of the sources of these problems is said to be the rigidity of the current network infrastructures which limits innovations in the network. SDN (Software Defined Network) has emerged as one of the prominent solutions with its idea of abstraction, visibility, and programmability in the network. Nevertheless, there are still significant efforts needed to actually utilize it to create a more energy and environmentally friendly network. In this paper, we suggested and developed a platform for developing ecology-related SDN applications. The main approach we take in realizing this goal is by maximizing the abstractions provided by OpenFlow and to expose RESTful interfaces to modules which enable energy saving in the network. While OpenFlow is made to be the standard for SDN protocol, there are still some mechanisms not defined in its specification such as settings related to Quality of Service (QoS). To solve this, we created REST interfaces for setting of QoS in the switches which can maximize network utilization. We also created a module for minimizing the required network resources in delivering packets across the network. This is achieved by utilizing redundant links when it is needed, but disabling them when the load in the network decreases. The usage of multi paths in a network is also evaluated for its benefit in terms of transfer rate improvement and energy savings. Hopefully, the developed framework can be beneficial for developers in creating applications for supporting environmentally friendly network infrastructures.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Embedded Service Bus for Internet of Things Interoperability

Internet of Things (IoT) technologies are developing rapidly, and therefore there exist several standards of interconnection protocols and platforms. The existence of heterogeneous protocols and platforms has become a critical challenge for IoT system developers. To mitigate this challenge, few alliances and organizations have taken the initiative to build a framework that helps to integrate application silos. Some of these frameworks focus only on a specific domain like home automation. However, the resource constraints in the large proportion of connected devices make it difficult to build an interoperable system using such frameworks. Therefore, a general purpose, lightweight interoperability framework that can be used for a range of devices is required. To tackle the heterogeneous nature, this work introduces an embedded, distributed and lightweight service bus, Lightweight IoT Service bus Architecture (LISA), which fits inside the network stack of a small real-time operating system for constrained nodes. LISA provides a uniform application programming interface for an IoT system on a range of devices with variable resource constraints. It hides platform and protocol variations underneath it, thus facilitating interoperability in IoT implementations. LISA is inspired by the Network on Terminal Architecture, a service centric open architecture by Nokia Research Center. Unlike many other interoperability frameworks, LISA is designed specifically for resource constrained nodes and it provides essential features of a service bus for easy service oriented architecture implementation. The presented architecture utilizes an intermediate computing layer, a Fog layer, between the small nodes and the cloud, thereby facilitating the federation of constrained nodes into subnetworks. As a result of a modular and distributed design, the part of LISA running in the Fog layer handles the heavy lifting to assist the lightweight portion of LISA inside the resource constrained nodes. Furthermore, LISA introduces a new networking paradigm, Node Centric Networking, to route messages across protocol boundaries to facilitate interoperability. This thesis presents a concept implementation of the architecture and creates a foundation for future extension towards a comprehensive interoperability framework for IoT.

Digitalisaatio ja kuljettajakoulutusyrittäjyys

Digitalisaation myötä myös liikenteestä tulee yhä älykkäämpää. Valtiovalta purkaa sääntelyä ja sallii digitaalisten menetelmien laajempaa käyttöä. Kuljettajakoulutusta pidetään toimialana kuitenkin hyvin konventionaalisena. Diplomityön tarkoituksena on tutkia, mitä digitalisaatio tarkoittaa kuljettajakoulutusyritysten liiketoimintamalleille. Empiiristä aineistoa saatiin teemahaastatteluin ja aineistoa analysoitiin laadullisin menetelmin. Työssä esitellään alan vahvuudet, heikkoudet, mahdollisuudet ja uhat sekä tulevaisuuden skenaariot. Digitalisaatio aiheuttaa merkittäviä muutoksia kuljettajakoulutusalan yrityksille. Auto ei ole enää entisenlainen statussymboli eikä rahan käytön kohde. Digitaaliajan ihmiset eivät aina kaipaa fyysistä liikkumista, kun vielä kivijalkakaupatkin vähenevät. Ajokorttia ei useinkaan koeta välttämättömäksi aikuistumisriitiksi. Uusi teknologia voi kuitenkin radikaalisti parantaa alan yritysten suorituskykyä: palvelut muuttuvat ajasta ja paikasta riippumattomiksi sekä skaalautuviksi. Kuluttajien kannalta digitalisaatio puolestaan parantaa asiakaslähtöisyyttä. Alan liiketoimintamallien kehittymiseen vaikuttaa neljä taustavoimaa: digitalisaatio, perinteet, sääntely ja yrittäjyys. Liiketoimintamalli sisältää opetukselliset ydintoiminnot, sisäiset prosessit, liiketoiminnan tukitoiminnot ja arvoehdotuksen asiakkaalle. Liiketoiminnan kehittäminen vastaamaan digitalisaation vaatimuksia edellyttää proaktiivista innovaatiostrategiaa. Siihen perustuvien innovaatiomenetelmien avulla yritys voi kehittää liiketoimintamalliaan digitalisaation tarjoamien ja tiedon asymmetriasta kumpuavien mahdollisuuksien hyödyntämiseksi.

Towards a contextual understanding of B2B salespeople's selling competencies – An exploratory study among purchasing decision-makers of internationally-oriented technology firms

ABSTRACT Towards a contextual understanding of B2B salespeople’s selling competencies − an exploratory study among purchasing decision-makers of internationally-oriented technology firms The characteristics of modern selling can be classified as follows: customer retention and loyalty targets, database and knowledge management, customer relationship management, marketing activities, problem solving and system selling, and satisfying needs and creating value. For salespeople to be successful in this environment, they need a wide range of competencies. Salespeople’s selling skills are well documented in seller side literature through quantitative methods, but the knowledge, skills and competencies from the buyer’s perspective are under-researched. The existing research on selling competencies should be broadened and updated through a qualitative research perspective due to the dynamic nature and the contextual dependence of selling competencies. The purpose of the study is to increase understanding of the professional salesperson’s selling competencies from the industrial purchasing decision- makers’ viewpoint within the relationship selling context. In this study, competencies are defined as sales-related knowledge and skills. The scope of the study includes goods, materials and services managed by a company’s purchasing function and used by an organization on a daily basis. The abductive approach and ‘systematic combining’ have been applied as a research strategy. In this research, data were generated through semi- structured, person-to-person interviews and open-ended questions. The study was conducted among purchasing decision-makers in the technology industry in Finland. The branches consisted of the electronics and electro-technical industries and the mechanical engineering and metals industries. A total of 30 companies and one purchasing decision-maker from each company were purposively chosen for the sampling. The sample covers different company sizes based on their revenues, their differing structures – varying from public to family companies –that represent domestic and international ownerships. Before analyzing the data, they were organized by the purchasing orientations of the buyers: the buying, procurement or supply management orientation. Thematic analysis was chosen as the analysis method. After analyzing the data, the results were contrasted with the theory. There was a continuous interaction between the empirical data and the theory. Based on the findings, a total of 19 major knowledge and skills were identified from the buyers’ perspective. The specific knowledge and skills from the viewpoint of customers’ prevalent purchasing orientations were divided into two categories, generic and contextual. The generic knowledge and skills apply to all purchasing orientations, and the contextual knowledge and skills depend on customers’ prevalent purchasing orientations. Generic knowledge and skills relate to price setting, negotiation, communication and interaction skills, while contextual ones relate to knowledge brokering, ability to present solutions and relationship skills. Buying-oriented buyers value salespeople who are ‘action oriented experts, however at a bit of an arm’s length’, procurement buyers value salespeople who are ‘experts deeply dedicated to the customer and fostering the relationship’ and supply management buyers value salespeople who are ‘corporate-oriented experts’. In addition, the buyer’s perceptions on knowledge and selling skills differ from the seller’s ones. The buyer side emphasizes managing the subject matter, consisting of the expertise, understanding the customers’ business and needs, creating a customized solution and creating value, reliability and an ability to build long-term relationships, while the seller side emphasizes communica- tion, interaction and salesmanship skills. The study integrates the selling skills of the current three-component model− technical knowledge, salesmanship skills, interpersonal skills− and relationship skills and purchasing orientations, into a selling competency model. The findings deepen and update the content of these knowledges and skills in the B2B setting and create new insights into them from the buyer’s perspective, and thus the study increases contextual understanding of selling competencies. It generates new knowledge of the salesperson’s competencies for the relationship selling and personal selling and sales management literature. It also adds knowledge of the buying orientations to the buying behavior literature. The findings challenge sales management to perceive salespeople’s selling skills both from a contingency and competence perspective. The study has several managerial implications: it increases understanding of what the critical selling knowledge and skills from the buyer’s point of view are, understanding of how salespeople effectively implement the relationship marketing concept, sales management’s knowledge of how to manage the sales process more effectively and efficiently, and the knowledge of how sales management should develop a salesperson’s selling competencies when managing and developing the sales force. Keywords: selling competencies, knowledge, selling skills, relationship skills, purchasing orientations, B2B selling, abductive approach, technology firms

Open source solutions for multiplatform graphics programming

New emerging technologies in the recent decade have brought new options to cross platform computer graphics development. This master thesis took a look for cross platform 3D graphics development possibilities. All platform dependent and non real time solutions were excluded. WebGL and two different OpenGL based solutions were assessed via demo application by using most recent development tools. In the results pros and cons of the each solutions were noted.