Sharing large data collections between mobile peers

New directions in the provision of end-user computing experiences mean that we need to determine the best way to share data between small mobile computing devices. Partitioning large structures so that they can be shared efficiently provides a basis for data-intensive applications on such platforms. In conjunction with such an approach, dictionary-based compression techniques provide additional benefits and help to prolong battery life

Efficient data representation for XML in peer-based systems

Purpose - New directions in the provision of end-user computing experiences mean that the best way to share data between small mobile computing devices needs to be determined. Partitioning large structures so that they can be shared efficiently provides a basis for data-intensive applications on such platforms. The partitioned structure can be compressed using dictionary-based approaches and then directly queried without firstly decompressing the whole structure. Design/methodology/approach - The paper describes an architecture for partitioning XML into structural and dictionary elements and the subsequent manipulation of the dictionary elements to make the best use of available space. Findings - The results indicate that considerable savings are available by removing duplicate dictionaries. The paper also identifies the most effective strategy for defining dictionary scope. Research limitations/implications - This evaluation is based on a range of benchmark XML structures and the approach to minimising dictionary size shows benefit in the majority of these. Where structures are small and regular, the benefits of efficient dictionary representation are lost. The authors' future research now focuses on heuristics for further partitioning of structural elements. Practical implications - Mobile applications that need access to large data collections will benefit from the findings of this research. Traditional client/server architectures are not suited to dealing with high volume demands from a multitude of small mobile devices. Peer data sharing provides a more scalable solution and the experiments that the paper describes demonstrate the most effective way of sharing data in this context. Social implications - Many services are available via smartphone devices but users are wary of exploiting the full potential because of the need to conserve battery power. The approach mitigates this challenge and consequently expands the potential for users to benefit from mobile information systems. This will have impact in areas such as advertising, entertainment and education but will depend on the acceptability of file sharing being extended from the desktop to the mobile environment. Originality/value - The original work characterises the most effective way of sharing large data sets between small mobile devices. This will save battery power on devices such as smartphones, thus providing benefits to users of such devices

Architecture development of a real-time inferential calculation software and generalization for multi-product distillation columns

Prosessiteollisuudessa tärkeä edellytys kilpailukyvylle on valmistettujen tuotteiden tasainen laatu. Sen vuoksi tuotelaatua kuvaavaa tietoa on oltava jatkuvasti saatavilla, jotta prosesseja voidaan ohjata optimaalisesti ylätason säätimien avulla. Tämä diplomityö käsittelee reaaliaikaista laskentaohjelmistoa, joka on tarkoitettu monituotetislauksen säätöön, operointiin ja reaaliaikaiseen optimointiin vaadittavien laskentojen suoritukseen. Työn tavoitteena on laatia laskentaohjelmistolle uudistettu arkkitehtuuri, joka mahdollistaa helpomman ja nopeamman laskentojen konfiguroinnin sekä yleistää reaaliaikaiset laskennat erilaisille, toisistaan huomattavan paljon eroaville öljy- ja petrokemian teollisuuden monituotekolonneille. Kirjallisuusosassa tarkasteltiin monituotetislauksen ilmiöitä sekä yleisten, reaaliaikaisesti määritettävien laskennallisten suureiden ennustamiseen liittyviä sovelluksia. Sen lisäksi esiteltiin ja arvioitiin kaupallisia, tislauskolonnien laskennallisten suureiden ennustamiseen soveltuvia soft sensor -ohjelmistoja. Kokeellisessa osassa laskentaohjelmistolle suunniteltiin ja toteutettiin uudistettu ohjelmistoarkkitehtuuri sisältäen monituotekolonnia mallintavan kirjaston, graafisen konfigurointityökalun sekä uudistetun sovelluksen reaaliaikaisten laskentojen suorittamiseen. Lisäksi laskennan algoritmeja uudistettiin siten, että laskenta on yleistetty öljynjalostus- ja petrokemian teollisuuden monituotekolonneille kolonnin rakenteesta, instrumentaatiosta ja lähtötiedoista riippumatta. Uudistetun ratkaisun toiminta testattiin kaupallisia prosessisimulaattoreita ja herkkyysanalyysia hyödyntäen. Laskennan konfiguroinnin todettiin olevan helpompaa, nopeampaa ja suoritettavissa lähdekoodia muokkaamatta monimutkaisillekin monituotekolonneille. Ratkaisu todettiin myös edellistä vikasietoisemmaksi, operaattorille informatiivisemmaksi sekä yhteensopivammaksi modernien automaatio- ja informaatioteknisten järjestelmien kanssa.Uniform quality of products is a fundamental prerequisite for competitiveness in the process industry. Therefore, real-time information concerning product quality must be available for high-level controllers to achieve optimal control of the production process. This thesis examines a software package for performing real-time inferential calculations required in control, operation and real-time optimization of multi-product distillation columns. The aim is to create a new architecture for the software, enabling easier and faster configuration of real-time calculations and generalizing the calculation procedures to be suitable for different, highly versatile multi-product columns in refining and petrochemical industries. The literature part of this thesis studies the phenomena related to multi-product distillation and industrial applications of predicting real-time inferential key variables. In addition, it presents and evaluates commercial software suitable for developing soft sensors in distillation columns. In the experimental part a new architecture was designed and implemented for the real-time calculation software, including a library module for modeling multi-product columns, a graphical configuration tool and a renewed application for performing the actual real-time calculations. Furthermore, algorithms were redesigned and generalized for multi-product columns in refining and petrochemical industries, regardless of their versatility in column structure, instrumentation and information available. The functionality of the redesigned solution was tested utilizing commercial process simulator software and sensitivity analysis. The configuration of calculations turned out to be easier, faster and implementable without editing the source code of the software even for complex multi-product columns. The solution was also proven to be more fault-tolerant, informative for the operator and compatible with modern automation and information systems