Business on demand and its mobile solution - study with SAP ByDesign

Business On-Demand solutions are widely used by SMEs in the world today. When I started working in SAP, SAP had just launched its first version mobile solutions for Business On-Demand solutions. SAP ByDesign mobile solution is great, but I believe we could do something even better on mobile phones. My job is focusing on mobile application development. Therefore, I have lots of thoughts about how we could make the mobile solutions better serve desktop solutions and how to distinguish the mobile solutions. Finally I decide to have a further research into this area. The purpose of this thesis is trying to find out how to improve the mobile solutions for Business On-Demand, find out its benefit and limits, and distinguish SaaS mobile solutions from desktop ones. In order to conduct this research, I had some online literature search to find out the Business On-Demand market and major players in this area. I compare the materials from public internet with the ones that are used internally in SAP. I had some interviews with SAP solution manager and SAP‟s potential customers. I finally made some pro-posals for mobile SaaS solutions which I believe will make the solutions better present and much helpful to the customers.

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Pysäköintihallien pakokaasupäästöjen mittaaminen ja ilmanvaihdon ohj

Henkilöautojen pakokaasut sisältävät satoja eri yhdisteitä, joista monet ovat ihmisen terveydelle haitallisia. Pysäköintihallien ilmanlaatua on tähän asti mitattu pääasiassa hiilimonoksidiantureilla, jolloin ilmanvaihtokoneita on voitu käyttää tarvepohjaisesti. Parantunut pakokaasujen puhdistustekniikka on vähentänyt perinteisesti haitallisimmaksi koettujen hiilimonoksidin ja typenoksidien määräpakokaasuissa. Tästä johtuen hiilidioksidin määrä pysäköintihallissa voi kohota haitalliselle tasolle ennen kuin hiilimonoksidianturit reagoivat tilanteeseen. Tässä diplomityössä tarkasteltiin pysäköintihallien ilmanlaatua ja hiilidioksidiantureiden edellytyksiä toimia ilmanvaihdon ohjauksessa. Hiilimonoksidi- ja hiilidioksidipitoisuuksia mitattiin Kampin ja Koskikeskuksen pysäköintihalleissa. Tuloksissa esitetään hiilimonoksidin ja hiilidioksidin riippuvuus ilmanvaihdon tehosta ja pysäköintihallin liikenteen määrästä. Johtopäätöksissä on kuvattu ehdotus hiilidioksidiantureiden käytöstä pysäköintihallien ilmanvaihdon ohjauksessa.

Researching Manufacturing Planning and Control system and Master Scheduling in a manufacturing firm.

The objective of this thesis is to research Manufacturing Planning and Control (MPC) system and Master Scheduling (MS) in a manufacturing firm. The study is conducted at Ensto Finland Corporation, which operates on a field of electrical systems and supplies. The paper consists of theoretical and empirical parts. The empirical part is based on weekly operating at Ensto and includes inter-firm material analysis, learning and meetings. Master Scheduling is an important module of an MPC system, since it is beneficial on transforming strategic production plans based on demand forecasting into operational schedules. Furthermore, capacity planning tools can remarkably contribute to production planning: by Rough-Cut Capacity Planning (RCCP) tool, a MS plan can be critically analyzed in terms of available key resources in real manufacturing environment. Currently, there are remarkable inefficiencies when it comes to Ensto’s practices: the system is not able to take into consideration seasonal demand and react on market changes on time; This can cause significant lost sales. However, these inefficiencies could be eliminated through the appropriate utilization of MS and RCCP tools. To utilize MS and RCCP tools in Ensto’s production environment, further testing in real production environment is required. Moreover, data accuracy, appropriate commitment to adapting and learning the new tools, and continuous developing of functions closely related to MS, such as sales forecasting, need to be ensured.

When to Utilize Software as a Service

Cloud computing enables on-demand network access to shared resources (e.g., computation, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort. Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers. Software as a service (SaaS) is part of cloud computing. It is one of the cloud service models. SaaS is software deployed as a hosted service and accessed over the Internet. In SaaS, the consumer uses the provider‘s applications running in the cloud. SaaS separates the possession and ownership of software from its use. The applications can be accessed from any device through a thin client interface. A typical SaaS application is used with a web browser based on monthly pricing. In this thesis, the characteristics of cloud computing and SaaS are presented. Also, a few implementation platforms for SaaS are discussed. Then, four different SaaS implementation cases and one transformation case are deliberated. The pros and cons of SaaS are studied. This is done based on literature references and analysis of the SaaS implementations and the transformation case. The analysis is done both from the customer‘s and service provider‘s point of view. In addition, the pros and cons of on-premises software are listed. The purpose of this thesis is to find when SaaS should be utilized and when it is better to choose a traditional on-premises software. The qualities of SaaS bring many benefits both for the customer as well as the provider. A customer should utilize SaaS when it provides cost savings, ease, and scalability over on-premises software. SaaS is reasonable when the customer does not need tailoring, but he only needs a simple, general-purpose service, and the application supports customer‘s core business. A provider should utilize SaaS when it offers cost savings, scalability, faster development, and wider customer base over on-premises software. It is wise to choose SaaS when the application is cheap, aimed at mass market, needs frequent updating, needs high performance computing, needs storing large amounts of data, or there is some other direct value from the cloud infrastructure.

Kysynnän ennakointiprosessin kehittäminen leipomoyrityksessä

Tämän työn tarkoituksena on kehittää lyhyen tähtäimen kysynnän ennakointiprosessia VAASAN Oy:ssä, jossa osa tuotteista valmistetaan kysyntäennakoiden perusteella. Valmistettavien tuotteiden luonteesta johtuva varastointimahdollisuuden puuttuminen, korkea toimitusvarmuustavoite sekä tarvittavien ennakoiden suuri määrä asettavat suuret haasteet kysynnän ennakointiprosessille. Työn teoriaosuudessa käsitellään kysynnän ennustamisen tarvetta, ennusteiden käyttökohteita sekä kysynnän ennustamismenetelmiä. Pelkällä kysynnän ennustamisella ei kuitenkaan päästä toimitusketjun kannalta optimaaliseen lopputulokseen, vaan siihen tarvitaan kokonaisvaltaista kysynnän hallintaa. Se on prosessi, jonka tavoitteena on tasapainottaa toimitusketjun kyvykkyydet ja asiakkaiden vaatimukset keskenään mahdollisimman tehokkaasti. Työssä tutkittiin yrityksessä kolmen kuukauden aikana eksponentiaalisen tasoituksen menetelmällä laadittuja ennakoita sekä ennakoijien tekemiä muutoksia niihin. Tutkimuksen perusteella optimaalinen eksponentiaalisen tasoituksen alfa-kerroin on 0,6. Ennakoijien tilastollisiin ennakoihin tekemät muutokset paransivat ennakoiden tarkkuutta ja ne olivat erityisen tehokkaita toimituspuutteiden minimoimisessa. Lisäksi työn tuloksena ennakoijien käyttöön saatiin monia päivittäisiä rutiineja helpottavia ja automatisoivia työkaluja.

Tien avaus tarinoivaan etnografiseen representaatioon

Kirjallisuusarvostelu

Kysyntä-toimitusketjun synkronointi epävarman kysynnän ja tarjonnan toimintaympäristössä

Kysynnän ja tarjonnan epävarmuudet ovat nykyisin arkipäivää useilla toimialoilla. Elämme epävarmuuden suhteen ennen näkemättömiä aikoja, minkä on arvioitu jatkuvan myös tulevaisuudessa. Yritysten tilauskannat ovat lyhyitä, ja tilaukset viivästyvät tai peruuntuvat kokonaan. Toisaalta tarjonnan epävarmuudet aiheuttavat asiakasyrityksille haasteita esimerkiksi toimitusmyöhästymisten muodossa. Tuotannon ollessa hajaantunut verkostoihin yksittäisten yritysten toiminta ja päätökset vaikuttavat toisten verkostoyritysten toimintaan. Tämän takia epävarmuuden aiheuttamista muutoksista ja poikkeamista tulisi tiedottaa kumppaniyrityksiä, jotta kaikki pysyisivät samalla kellotaajuudella. Operatiivisen ja taktisen tiedon jakaminen on nykyisissä toimitusketjuissa jo arkipäivää, mutta yritysten välisistä rajapinnoista löytyy edelleen kehitettävää. Riittävästä ei kiinnitetä huomiota vastaanottajan kykyyn ja tapaan hyödyntää informaatiota – varsinkaan muutostilanteissa. Ajan/nopeuden ollessa yhä tärkeämpi kilpailutekijä informaation ajoituksella on kriittinen merkitys kysyntä-toimitusketjujen kokonaissuorituskykyyn. Toisin sanoen, millä ajanhetkellä tietoa tulisi jakaa, jotta kumppani pystyisi hyödyntämään saamaansa tietoa mahdollisimman hyvin. Kysyntä-toimitusketjun synkronoinnilla tarkoitetaan tässä väitöstutkimuksessa nimenomaan aikatekijään keskittymistä yritysten välisessä päätöksenteossa ja informaation jakamisessa toimitusketjun kokonaissuorituskyvyn parantamiseksi. Tutkimus kytkeytyy toimitusketjukoordinoinnin tieteelliseen keskusteluun. Koordinointiteorian keskeinen osa ovat riippuvuussuhteet, joita johdetaan koordinointimekanismien avulla. Kysyntätoimitusketjun synkronointia on mallinnettu aikaisemmin VOP-OPP-mallin (Value Offering Point – Order Penetration Point) ja sen johdannaisten avulla. Näissä malleissa asiakasyrityksen kysyntäketju ja toimittajayrityksen toimitusketju ovat keskinäisessä riippuvuussuhteessa, jota johdetaan päätöksenteon synkronoinnin ja informaation jakamisen koordinointimekanismeilla. VOP-OPP-malli johdannaisineen eivät kuitenkaan huomioi epävarman toimintaympäristön vaikutuksia synkronointiin. Näissä malleissa informaation ainoana laatudimensiona tarkasteltava aikatekijä on liian kapea-alainen näkökulma synkronointiin epävarmassa ympäristössä. Lisäksi nämä mallit keskittyvät vain yksisuuntaiseen, kysyntälähtöiseen, synkronointiin jättäen huomioimatta tarjontalähtöisen synkronoinnin. Aikatekijä- ja kokonaissuorituskykypainotustensa takia VOP-OPP-malli tarjosi kuitenkin hyvän lähtöfilosofian uusien synkronointimallien kehittämiseen. Väitöstutkimus toteutettiin hypoteettis-deduktiivisena tapaustutkimuksena, jossa ensin luotiin kirjallisuuden perusteella uudet teoreettiset synkronointimalliehdotukset. Tämän jälkeen ehdotusten toimivuutta arvioitiin käytännön kysyntä-toimitusketjuissa. Tutkimuksen uutuusarvo liittyy kysyntä-toimitusketjun synkronoinnin keskeisten piirteiden systeemiseen mallintamiseen epävarmassa toimintaympäristössä. Kontribuutiona esitetään kysyntä-toimitusketjun synkronoinnin moniulotteinen kokonaismalli, joka sisältää koordinointimekanismeina päätöksenteon synkronoinnin, informaation läpinäkyvyyden sekä asiakas- ja toimittajapään joustot. Tiedon vaihtoa mallissa tarkastellaan kaksisuuntaisesti – kysyntä- ja tarjontalähtöisesti. Informaation laatudimensioina mallissa ovat informaation ajoitus, luotettavuus ja tarkkuus. Kokonaismalli sisältää kolme alimallia: Demand Visibility Point – Demand Penetration Point (DVP-DPP) on kysyntälähtöisen synkronoinnin malli, Supply Visibility Point – Supply Information Penetration Point (SVP-SIPP) on tarjontalähtöisen synkronoinnin malli ja Integroitu DVP-DPP - SVP-SIPP-malli kytkee edellä mainitut mallit toisiinsa. Näissä alimalleissa informaation eri luokkia ovat tilausta edeltävä, tilaukseen liittyvä, tilauksen jälkeinen ja sovitun toimitusajankohdan jälkeinen kysyntä- ja tarjontatieto. Käytännön hyödyntämisen näkökulmasta mallit toimivat ns. mentaalitason koordinointimekanismeina, joiden tarkoitus on herättää toimitusketjukumppanit tavoittelemaan kokonaissuorituskyvyn parantamista oman edun tavoittelemisen sijasta. Tutkimuksen päärajoitteena on sen keskittyminen ainoastaan kahdenvälisiin yhteistyösuhteisiin, mikä tarjoaa nykyisessä verkostoituneessa toimintaympäristössä varsin kapean kuvan käytännön synkronointihaasteisiin.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

A Template for Cloud Technology Deployment in an Energy Trading Environment

Nykyaikaiset pilvipalvelut tarjoavat suurille yrityksille mahdollisuuden tehostaa laskennallista tietojenkäsittelyä. Pilvipalveluiden käyttöönotto tuo mukanaan kuitenkin esimerkiksi useita tietoturvakysymyksiä, joiden vuoksi käyttöönoton tulee olla tarkasti suunniteltua. Tämä tutkimus esittelee kirjallisuuskatsaukseen perustuvan, asteittaisen suunnitelman pilvipalveluiden käyttöönotolle energialiiketoimintaympäristössä. Kohdeyrityksen sisäiset haastattelut ja katsaus nykyisiin energiateollisuuden pilviratkaisuihin muodostavat kokonaiskuvan käyttöönoton haasteista ja mahdollisuuksista. Tutkimuksen päätavoitteena on esittää ratkaisut tyypillisiin pilvipalvelun käyttöönotossa esiintyviin ongelmiin käyttöönottomallin avulla. Tutkimuksessa rakennettu käyttöönottomalli testattiin esimerkkitapauksen avulla ja malli todettiin toimivaksi. Ulkoisten palveluiden herättämien tietoturvakysymysten takia käyttöönoton ensimmäiset osiot, kuten lopputuotteen määrittely ja huolellinen suunnittelu, ovat koko käyttöönottoprosessin ydin. Lisäksi pilvipalveluiden käyttöönotto vaatii nykyiseltä käyttöympäristöltä uusia teknisiä ja hallinnollisia taitoja. Tutkimuksen tulokset osoittavat pilvipalveluiden monipuolisen hyödyn erityisesti laskentatehon tarpeen vaihdellessa. Käyttöönottomallin rinnalle luotu kustannusvertailu tukee kirjallisuuskatsauksessa esille tuotuja hyötyjä ja tarjoaa kohdeyritykselle perusteen tutkimuksen eteenpäin viemiselle.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Benchmark of routing protocols regarding green considerations

In Mobile Ad-hoc Networks (MANET) the participating nodes have several roles such as sender, receiver and router. Hence there is a lot of energy consumed by the nodes for the normal working of the network since each node has many different roles. Also in MANET the nodes keep moving constantly and this in turn consumes a lot of energy. Since battery capacity of these nodes is limited it fails to fulfil the high demand of energy. The scarcity of energy makes the energy conservation in mobile ad-hoc networks an important concern. There is several research carried out on the energy consumption of mobile ad-hoc networks these days. Some of this research suggests sleep mode, transmission power control, load balancing etc. In this thesis, we are comparing various proposed energy efficient models for some of the ad-hoc protocols. We compare different energy efficient models for Optimised Linked State Algorithm (OLSR) and Ad-hoc On Demand Distance Vector (AODV). The routing protocols are compared for different parameters such as average remaining energy, number of nodes alive, payload data received and performance with different mobility speed. The simulation results helps in benchmarking the various energy efficient routing models for OLSR and AODV protocols. The benchmarking of the routing protocols can be based on many factors but this thesis concentrates on benchmarking the MANET routing protocols mainly based on the energy efficiency and increased network lifetime.

BotCloud Detection System

Leveraging cloud services, companies and organizations can significantly improve their efficiency, as well as building novel business opportunities. Cloud computing offers various advantages to companies while having some risks for them too. Advantages offered by service providers are mostly about efficiency and reliability while risks of cloud computing are mostly about security problems. Problems with security of the cloud still demand significant attention in order to tackle the potential problems. Security problems in the cloud as security problems in any area of computing, can not be fully tackled. However creating novel and new solutions can be used by service providers to mitigate the potential threats to a large extent. Looking at the security problem from a very high perspective, there are two focus directions. Security problems that threaten service user’s security and privacy are at one side. On the other hand, security problems that threaten service provider’s security and privacy are on the other side. Both kinds of threats should mostly be detected and mitigated by service providers. Looking a bit closer to the problem, mitigating security problems that target providers can protect both service provider and the user. However, the focus of research community mostly is to provide solutions to protect cloud users. A significant research effort has been put in protecting cloud tenants against external attacks. However, attacks that are originated from elastic, on-demand and legitimate cloud resources should still be considered seriously. The cloud-based botnet or botcloud is one of the prevalent cases of cloud resource misuses. Unfortunately, some of the cloud’s essential characteristics enable criminals to form reliable and low cost botclouds in a short time. In this paper, we present a system that helps to detect distributed infected Virtual Machines (VMs) acting as elements of botclouds. Based on a set of botnet related system level symptoms, our system groups VMs. Grouping VMs helps to separate infected VMs from others and narrows down the target group under inspection. Our system takes advantages of Virtual Machine Introspection (VMI) and data mining techniques.