Simulation and analysis of network traffic for efficient and reliable information transfer

With the growing commercial importance of the Internet and the development of new real-time, connection-oriented services like IP-telephony and electronic commerce resilience is becoming a key issue in the design of TP-based networks. Two emerging technologies, which can accomplish the task of efficient information transfer, are Multiprotocol Label Switching (MPLS) and Differentiated Services. A main benefit of MPLS is the ability to introduce traffic-engineering concepts due to its connection-oriented characteristic. With MPLS it is possible to assign different paths for packets through the network. Differentiated services divides traffic into different classes and treat them differently, especially when there is a shortage of network resources. In this thesis, a framework was proposed to integrate the above two technologies and its performance in providing load balancing and improving QoS was evaluated. Simulation and analysis of this framework demonstrated that the combination of MPLS and Differentiated services is a powerful tool for QoS provisioning in IP networks.

Escalonando uma aplicação paralela com demanda variável em ambiente de nuvem

This study proposes a solution responsible for scheduling data processing with variable demand in cloud environments. The system built check specific variables to the business context of a company incubated at Digital Metropole Institute of UFRN. Such a system generates an identification strategy machinery designs available in a cloud environment, focusing on processing performance, using data load balancing strategies and activities of parallelism in the software execution flow. The goal is to meet the seasonal demand within a standard time limit set by the company, controlling operating costs by using cloud services in the IaaS layer.

Analisi del ruolo del porto di Ravenna nell’import/export di prodotti ortofrutticoli

L'elaborato tratta il ruolo del porto di Ravenna nell'import/export di prodotti ortofrutticoli. Dopo una accurata analisi dei dati, lo studio delle rotte marittime e l'uso di Dbms per gestire un database complesso, si propone un modello di programmazione lineare intera su un problema di ship routing, ship scheduling e full ship-load balancing. L'obiettivo è di massimizzare il profitto derivante da un prezzo di vendita e soggetto ai vari costi della logistica. Il modello sceglie la rotta ottimale da effettuare, in termini di ordine di visita dei vari porti che hanno un import e un export dei prodotti studiati. Inoltre, è in grado di gestire lo scorrere del tempo, fornendo come soluzione il giorno ottimale di visita dei vari porti considerati. Infine, trova la ripartizione ottima del numero di container a bordo della nave per ogni tipologia di prodotto.

Dynamic Workload Parallelization and System Calibration on Single-Chip Cloud Computer

Many-core systems are emerging from the need of more computational power and power efficiency. However there are many issues which still revolve around the many-core systems. These systems need specialized software before they can be fully utilized and the hardware itself may differ from the conventional computational systems. To gain efficiency from many-core system, programs need to be parallelized. In many-core systems the cores are small and less powerful than cores used in traditional computing, so running a conventional program is not an efficient option. Also in Network-on-Chip based processors the network might get congested and the cores might work at different speeds. In this thesis is, a dynamic load balancing method is proposed and tested on Intel 48-core Single-Chip Cloud Computer by parallelizing a fault simulator. The maximum speedup is difficult to obtain due to severe bottlenecks in the system. In order to exploit all the available parallelism of the Single-Chip Cloud Computer, a runtime approach capable of dynamically balancing the load during the fault simulation process is used. The proposed dynamic fault simulation approach on the Single-Chip Cloud Computer shows up to 45X speedup compared to a serial fault simulation approach. Many-core systems can draw enormous amounts of power, and if this power is not controlled properly, the system might get damaged. One way to manage power is to set power budget for the system. But if this power is drawn by just few cores of the many, these few cores get extremely hot and might get damaged. Due to increase in power density multiple thermal sensors are deployed on the chip area to provide realtime temperature feedback for thermal management techniques. Thermal sensor accuracy is extremely prone to intra-die process variation and aging phenomena. These factors lead to a situation where thermal sensor values drift from the nominal values. This necessitates efficient calibration techniques to be applied before the sensor values are used. In addition, in modern many-core systems cores have support for dynamic voltage and frequency scaling. Thermal sensors located on cores are sensitive to the core's current voltage level, meaning that dedicated calibration is needed for each voltage level. In this thesis a general-purpose software-based auto-calibration approach is also proposed for thermal sensors to calibrate thermal sensors on different range of voltages.

DRAMA: Dynamic re-allocation of meshes for parallel finite element applications

In many areas of simulation, a crucial component for efficient numerical computations is the use of solution-driven adaptive features: locally adapted meshing or re-meshing; dynamically changing computational tasks. The full advantages of high performance computing (HPC) technology will thus only be able to be exploited when efficient parallel adaptive solvers can be realised. The resulting requirement for HPC software is for dynamic load balancing, which for many mesh-based applications means dynamic mesh re-partitioning. The DRAMA project has been initiated to address this issue, with a particular focus being the requirements of industrial Finite Element codes, but codes using Finite Volume formulations will also be able to make use of the project results.

New Directions in Commercial Secrecy and Encryption Protocols

Secure transmission of bulk data is of interest to many content providers. A commercially-viable distribution of content requires technology to prevent unauthorised access. Encryption tools are powerful, but have a performance cost. Without encryption, intercepted data may be illicitly duplicated and re-sold, or its commercial value diminished because its secrecy is lost. Two technical solutions make it possible to perform bulk transmissions while retaining security without too high a performance overhead. These are: 1. a) hierarchical encryption - the stronger the encryption, the harder it is to break but also the more computationally expensive it is. A hierarchical approach to key exchange means that simple and relatively weak encryption and keys are used to encrypt small chunks of data, for example 10 seconds of video. Each chunk has its own key. New keys for this bottom-level encryption are exchanged using a slightly stronger encryption, for example a whole-video key could govern the exchange of the 10-second chunk keys. At a higher level again, there could be daily or weekly keys, securing the exchange of whole-video keys, and at a yet higher level, a subscriber key could govern the exchange of weekly keys. At higher levels, the encryption becomes stronger but is used less frequently, so that the overall computational cost is minimal. The main observation is that the value of each encrypted item determines the strength of the key used to secure it. 2. b) non-symbolic fragmentation with signal diversity - communications are usually assumed to be sent over a single communications medium, and the data to have been encrypted and/or partitioned in whole-symbol packets. Network and path diversity break up a file or data stream into fragments which are then sent over many different channels, either in the same network or different networks. For example, a message could be transmitted partly over the phone network and partly via satellite. While TCP/IP does a similar thing in sending different packets over different paths, this is done for load-balancing purposes and is invisible to the end application. Network and path diversity deliberately introduce the same principle as a secure communications mechanism - an eavesdropper would need to intercept not just one transmission path but all paths used. Non-symbolic fragmentation of data is also introduced to further confuse any intercepted stream of data. This involves breaking up data into bit strings which are subsequently disordered prior to transmission. Even if all transmissions were intercepted, the cryptanalyst still needs to determine fragment boundaries and correctly order them. These two solutions depart from the usual idea of data encryption. Hierarchical encryption is an extension of the combined encryption of systems such as PGP but with the distinction that the strength of encryption at each level is determined by the "value" of the data being transmitted. Non- symbolic fragmentation suppresses or destroys bit patterns in the transmitted data in what is essentially a bit-level transposition cipher but with unpredictable irregularly-sized fragments. Both technologies have applications outside the commercial and can be used in conjunction with other forms of encryption, being functionally orthogonal.

Controladores repetitivos aplicados a filtros ativos de potência sob variações de carga e de frequência da rede

This work presents the development and modification of techniques to reduce the effects of load variation and mains frequency deviation in repetitive controllers applied to active power filters. To minimize the effects of aperiodic signals resulting from the connection or disconnection of non-linear loads is developed a technique which recognizes linear and nonlinear loads, and operates to reset the controller only when the error due to the transition of considerable value, and the transition is from non-linear to linear load. An algorithm to adapt the gain of the repetitive controller, based on a sigmoid function adaptation, in order to minimize the effects caused by random noise in the measurement system is also used. This work also analyzes the effects of frequency variation and presents the main methods to cope with this situation. Some solutions are the change in the number of samples per period and the variation of the sampling rate. The first has the advantage of using linear design techniques and results in a time invariant system. The second method changes the sampling frequency and leads to a time variant system that demands a difficult analysis of stability. The proposed algorithms were tested using the methods of truncation of the number of samples and the method of changing the sampling rate of the system to compensate possible frequency variations of the grid. Experimental results are presented to validate the proposal.

Pacote de sincronização de réplicas de bases de dados

A replicação de base de dados tem como objectivo a cópia de dados entre bases de dados distribuídas numa rede de computadores. A replicação de dados é importante em várias situações, desde a realização de cópias de segurança da informação, ao balanceamento de carga, à distribuição da informação por vários locais, até à integração de sistemas heterogéneos. A replicação possibilita uma diminuição do tráfego de rede, pois os dados ficam disponíveis localmente possibilitando também o seu acesso no caso de indisponibilidade da rede. Esta dissertação baseia-se na realização de um trabalho que consistiu no desenvolvimento de uma aplicação genérica para a replicação de bases de dados a disponibilizar como open source software. A aplicação desenvolvida possibilita a integração de dados entre vários sistemas, com foco na integração de dados heterogéneos, na fragmentação de dados e também na possibilidade de adaptação a várias situações. ABSTRACT: Data replication is a mechanism to synchronize and integrate data between distributed databases over a computer network. Data replication is an important tool in several situations, such as the creation of backup systems, load balancing between various nodes, distribution of information between various locations, integration of heterogeneous systems. Replication enables a reduction in network traffic, because data remains available locally even in the event of a temporary network failure. This thesis is based on the work carried out to develop an application for database replication to be made accessible as open source software. The application that was built allows for data integration between various systems, with particular focus on, amongst others, the integration of heterogeneous data, the fragmentation of data, replication in cascade, data format changes between replicas, master/slave and multi master synchronization.

Efficient computation algorithm for calculating load contributions to line flows and losses

In a deregulated power system, it is usually required to determine the shares of each load and generation in line flows, to permit fair allocation of transmission costs between the interested parties. The paper presents a new method of determining the contributions of each load to line flows and losses. The method is based on power-flow topology and has the advantage of being the least computationally demanding of similar methods.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning

Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert). Many conventional active learning algorithms focus on refining the decision boundary, at the expense of exploring new regions that the current hypothesis misclassifies. We propose a new active learning algorithm that balances such exploration with refining of the decision boundary by dynamically adjusting the probability to explore at each step. Our experimental results demonstrate improved performance on data sets that require extensive exploration while remaining competitive on data sets that do not. Our algorithm also shows significant tolerance of noise.

An optimization-based algorithm for shunt active filter under distorted supply voltages

When the supply voltages are balanced and sinusoidal, load compensation can give both unity power factor (UPF) and perfect harmonic cancellation (PHC) source currents. But under distorted supply voltages, achieving both UPF and PHC currents are not possible and contradictory to each other. Hence there should be an optimal performance between these two important compensation goals. This paper presents an optimal control algorithm for load compensation under unbalanced and distorted supply voltages. In this algorithm source currents are compensated for reactive, imbalance components and harmonic distortions set by the limits. By satisfying the harmonic distortion limits and power balance, this algorithm gives the source currents which will provide the maximum achievable power factor. The detailed simulation results using MATLAB are presented to support the performance of the proposed optimal control algorithm.