The Investigation of Efficiency of Physical Phenomena Modelling Using Differential Equations on Distributed Systems

This work is dedicated to development of mathematical modelling software. In this dissertation numerical methods and algorithms are investigated in software making context. While applying a numerical method it is important to take into account the limited computer resources, the architecture of these resources and how do methods affect software robustness. Three main aspects of this investigation are that software implementation must be efficient, robust and be able to utilize specific hardware resources. The hardware specificity in this work is related to distributed computations of different types: single CPU with multiple cores, multiple CPUs with multiple cores and highly parallel multithreaded GPU device. The investigation is done in three directions: GPU usage for 3D FDTD calculations, FVM method usage to implement efficient calculations of a very specific heat transferring problem, and development of special techniques for software for specific bacteria self organization problem when the results are sensitive to numerical methods, initial data and even computer round-off errors. All these directions are dedicated to create correct technological components that make a software implementation robust and efficient. The time prediction model for 3D FDTD calculations is proposed, which lets to evaluate the efficiency of different GPUs. A reasonable speedup with GPU comparing to CPU is obtained. For FVM implementation the OpenFOAM open source software is selected as a basis for implementation of calculations and a few algorithms and their modifications to solve efficiency issues are proposed. The FVM parallel solver is implemented and analyzed, it is adapted to heterogeneous cluster Vilkas. To create robust software for simulation of bacteria self organization mathematically robust methods are applied and results are analyzed, the algorithm is modified for parallel computations

Peer to Peer Information Retrieval: An Overview

Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom

Scalable, Data- intensive Network Computation

To enable groups of collaborating researchers at different locations to effectively share large datasets and investigate their spontaneous hypotheses on the fly, we are interested in de- veloping a distributed system that can be easily leveraged by a variety of data intensive applications. The system is composed of (i) a number of best effort logistical depots to en- able large-scale data sharing and in-network data processing, (ii) a set of end-to-end tools to effectively aggregate, manage and schedule a large number of network computations with attendant data movements, and (iii) a Distributed Hash Table (DHT) on top of the generic depot services for scalable data management. The logistical depot is extended by following the end-to-end principles and is modeled with a closed queuing network model. Its performance characteristics are studied by solving the steady state distributions of the model using local balance equations. The modeling results confirm that the wide area network is the performance bottleneck and running concurrent jobs can increase resource utilization and system throughput. As a novel contribution, techniques to effectively support resource demanding data- intensive applications using the ¯ne-grained depot services are developed. These techniques include instruction level scheduling of operations, dynamic co-scheduling of computation and replication, and adaptive workload control. Experiments in volume visualization have proved the effectiveness of these techniques. Due to the unique characteristic of data- intensive applications and our co-scheduling algorithm, a DHT is implemented on top of the basic storage and computation services. It demonstrates the potential of the Logistical Networking infrastructure to serve as a service creation platform

Vartotojų sukuriamų srautų balansavimas heterogeninio korinio ryšio tinkluose

Disertacijoje nagrinėjami heterogeninių korinio ryšio tinklų talpos ir paslaugų kokybės užtikrinimo klausimai, taikant vartotojų srauto balansavimą. Pagrindiniai tyrimo objektai yra vartotojų sukuriamo balso ir duomenų srauto balansavimas tinkle. Srauto balansavimas yra svarbi sritis šių dienų telekomunikacijose, kai perduodamų duomenų srautai auga milžiniškais tempais. Įvairiapusiška ir lanksti vartotojų srauto balansavimo metodika leidžia efektyviai valdyti srautą tinkle, sumažinant tinklo apkrovą ir investicijas. Pagrindinis disertacijos tikslas – ištirti išplėstines vartotojų srautų balansavimo galimybes korinio ryšio sistemose. Darbe siekiama įvertinti srauto balansavimo įtaką tinklo vartotojams bei tinklui. Darbe sprendžiami du pirmieji uždaviniai apima: balso paslaugų vartotojų srauto analizę, pagal vartotojų buvimo vietą, bei balso srauto balansa-vimą, taikant tarpsisteminius srauto balansavimo metodus. Kiti du uždaviniai siejami su vartotojų siunčiamo duomenų srauto augimu, kuris sukelia tinklo ląstelių persipildymą. Duomenų srauto valdymui taikomi paslaugų klasifikavimo pagal QoS ir tarpsluoksnio balansavimo metodai, kurie remiasi mažomis ląstelėmis. Disertaciją sudaro įvadas, trys skyriai, bendrosios išvados, naudotos literatūros ir autoriaus publikacijų disertacijos tema sąrašai, priedai, reziumė anglų kalba. Įvadiniame skyriuje aptariama tiriamoji problema, darbo aktualumas, aprašomas tyrimų objektas, formuluojamas darbo tikslas bei uždaviniai, aprašoma tyrimų metodika, darbo mokslinis naujumas, darbo rezultatų praktinė reikšmė, ginamieji teiginiai. Pabaigoje pristatomos disertacijos tema autoriaus paskelbtos publikacijos bei disertacijos struktūra. Pirmasis skyrius yra skirtas literatūros analizei. Jame aptariama srautų balansavimo samprata bei poreikis. Skyriuje pateikiama išsami srauto balansavimo metodų apžvalga, analizuojami konkretūs balso ir duomenų balansavimo būdai. Antrame skyriuje nagrinėjamas balso srauto pasiskirstymas realus korinio ryšio tinkle pagal surinktus metaduomenis. Skyriuje pateiktos srauto charakteristikos. Iš tinklo veiklos rodiklių nustatyta balso balansavimo įtaka tinklui ir vartotojams. Trečiasis skyrius atskleidžia duomenų srauto QoS prioriteto reikšmę paslaugų kokybei vienodomis ir skirtingomis ryšio kanalo sąlygomis. Tarpsluoksnio srauto balansavimo atveju pateiktas femto zoną reprezentuojantis modelis ir įvertinta ryšio paslaugų vartotojų patiriama paslaugų kokybė femto zonose. Tyrimai atliekami realiomis radijo aplinkos sąlygomis. Disertacijos tema paskelbti 7 moksliniai straipsniai recenzuojamuose mokslo leidiniuose: 4 straipsniai mokslo žurnaluose referuojamuose kitose tarptautinėse duomenų bazėse ir 3 straipsniai konferencijų medžiagose. Di-sertacijos tema perskaityti 7 pranešimai Lietuvos ir užsienio šalių konferencijose

Routing and caching on DHTS

L'obiettivo della tesi e' quello di analizzare i principali meccanismi di caching e routing implementati oggigiorno nelle DHT piu' utilizzate. In particolare, la nostra analisi mostra come tali meccanismi siano sostanzialmente inefficaci nel garantire un adeguato load balancing tra i peers; le principali cause di questo fenomeno sono individuate nella struttura, eccessivamente rigida, adottata dalle DHT e nella mancanza di correlazione tra meccanismi di routing e di caching. Viene quindi proposto un diverso overlay, organizzato in base a una struttura ipercubica, che permetta di adottare un algoritmo di routing piu' flessibile e di sviluppare due meccanismi di caching e routing strettamente interconnessi. In particolare, l'overlay ottenuto riesce a garantire che ogni nodo subisca un carico al piu' costante, con una taglia di cache costante e una complessita' di routing polilogaritmica nel caso peggior

„Redis Cluster“ podėlio sistemos tyrimas, taikant formalius metodus

Šiame straipsnyje yra analizuojamas podėlio sistemos „Redis Cluster“ korektiškumas. Analizuojant sistemą buvo naudojami formalūs metodai – TLA+ specifikavimo kalba buvo sudaryta sistemos formali specifikacija. Specifikacijos modelio tikrinimo metu buvo vertinama, ar yra užtikrinama sistemos savybė, kad už vieną maišos lizdą yra atsakingas tik vienas pagrindinis mazgas ir jo pavaldūs mazgai. Atlikus modelio tikrinimą buvo surastos situacijos, kada ši sistemos savybė nėra užtikrinama. Surastos klaidos buvo atkartotos realioje sistemoje ir šioms klaidoms buvo pateikti galimi sprendimo būdai

Pragmatic Distribution Based Routing Cluster to Improve Energy Efficient Cluster lifetime for Wireless Sensor Networks

Energy consumed by the  sensor nodes are more sporadic in a sensor networks. A skilled way to bring down energy consumption and extend maximum life-time of any sensor present can be of evenly and unevenly distributed random area networks. Cluster heads are more responsible for the links between the source and destination. Energy consumption are much compare to member nodes of the network. Re-clustering will take place if the connectivity in the distributed network failure occurs in between the cluster networks  that will affects redundancy in the network efficiency. Hence, we propose  pragmatic distribution based routing cluster lifetime using fitness function (PDBRC) prototype  is better than the existing protocol using MATLAB 2021a simulation tool

Managing Population and Workload Imbalance in Structured Overlays

Every day the number of data produced by networked devices increases. The current paradigm is to offload the data produced to data centers to be processed. However as more and more devices are offloading their data do cloud centers, accessing data becomes increasingly more challenging. To combat this problem, systems are bringing data closer to the consumer and distributing network responsibilities among the end devices. We are witnessing a change in networking paradigm, where data storage and computation that was once only handled in the cloud, is being processed by Internet of Things (IoT) and mobile devices, thanks to the ever increasing technological capabilities of these devices. One approach, leverages devices into a structured overlay network. Structured Overlays are a common approach to address the organization and distri- bution of data in peer-to-peer distributed systems. Due to their nature, indexing and searching for elements of the system becomes trivial, thus structured overlays become ideal building blocks of resource location based applications. Such overlays assume that the data is distributed evenly over the peers, and that the popularity of those data items is also evenly balanced. However in many systems, due to many factors outside of the system domain, popularity may behave rather randomly, al- lowing for some nodes to spare more resources looking for the popular items than others. In this work we intend to exploit the properties of cluster-based structured overlays propose to address this problem by improving a structure overlay with the mechanisms to manage the population and workload imbalance and achieve more uniform use of resources. Our approach focus on implementing a Group-Based Distributed Hash Table (DHT) capable of dynamically changing its groups to accommodate the changes in churn in the network. With the conclusion of our work we believe that we have indeed created a network capable of withstanding high levels of churn, while ensuring fairness to all members of the network.Todos os dias aumenta o número de dados produzidos por dispositivos em rede. O pa- radigma atual é descarregar os dados produzidos para centros de dados para serem pro- cessados. No entanto com o aumento do número de dispositivos a descarregar dados para estes centros, o acesso aos dados torna-se cada vez mais desafiante. Para combater este problema, os sistemas estão a aproximar os dados dos consumidores e a distribuir responsabilidades de rede entre os dispositivos. Estamos a assistir a uma mudança no paradigma de redes, onde o armazenamento de dados e a computação que antes eram da responsabilidade dos centros de dados, está a ser processado por dispositivos móveis IoT, graças às crescentes capacidades tecnológicas destes dispositivos. Uma abordagem, junta os dispositivos em redes estruturadas. As redes estruturadas são o meio mais comum de organizar e distribuir dados em redes peer-to-peer. Gradas às suas propriedades, indexar e procurar por elementos torna- se trivial, assim, as redes estruturadas tornam-se o bloco de construção ideal para sistemas de procura de ficheiros. Estas redes assumem que os dados estão distribuídos equitativamente por todos os participantes e que todos esses dados são igualmente procurados. no entanto em muitos sistemas, por factores externos a popularidade tem um comportamento volátil e imprevi- sível sobrecarregando os participantes que guardam os dados mais populares. Este trabalho tenta explorar as propriedades das redes estruturadas em grupo para confrontar o problema, vamos equipar uma destas redes com os mecanismos necessários para coordenar os participantes e a sua carga. A nossa abordagem focasse na implementação de uma DHT baseado em grupos capaz de alterar dinamicamente os grupos para acomodar as mudanças de membros da rede. Com a conclusão de nosso trabalho, acreditamos que criamos uma rede capaz de suportar altos níveis de instabilidade, enquanto garante justiça a todos os membros da rede