Contribuições em escalonamento e análise de desempenho de redes WirelessHART

Wireless Communication is a trend in the industrial environment nowadays and on this trend, we can highlight the WirelessHART technology. In this situation, it is natural the search for new improvements in the technology and such improvements can be related directly to the routing and scheduling algorithms. In the present thesis, we present a literature review about the main specific solutions for Routing and scheduling for WirelessHART. The thesis also proposes a new scheduling algorithm called Flow Scheduling that intends to improve superframe utilization and flexibility aspects. For validation purposes, we develop a simulation module for the Network Simulator 3 (NS-3) that models aspects like positioning, signal attenuation and energy consumption and provides an link individual error configuration. The module also allows the creation of the scheduling superframe using the Flow and Han Algorithms. In order to validate the new algorithms, we execute a series of comparative tests and evaluate the algorithms performance for link allocation, delay and superframe occupation. In order to validate the physical layer of the simulation module, we statically configure the routing and scheduling aspects and perform reliability and energy consumption tests using various literature topologies and error probabilities.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Estudo e desenvolvimento de algoritmos criptográficos para redes de sensores sem fio, utilizando técnicas de programação genética

Cryptography is the main form to obtain security in any network. Even in networks with great energy consumption restrictions, processing and memory limitations, as the Wireless Sensors Networks (WSN), this is no different. Aiming to improve the cryptography performance, security and the lifetime of these networks, we propose a new cryptographic algorithm developed through the Genetic Programming (GP) techniques. For the development of the cryptographic algorithm’s fitness criteria, established by the genetic GP, nine new cryptographic algorithms were tested: AES, Blowfish, DES, RC6, Skipjack, Twofish, T-DES, XTEA and XXTEA. Starting from these tests, fitness functions was build taking into account the execution time, occupied memory space, maximum deviation, irregular deviation and correlation coefficient. After obtaining the genetic GP, the CRYSEED and CRYSEED2 was created, algorithms for the 8-bits devices, optimized for WSNs, i.e., with low complexity, few memory consumption and good security for sensing and instrumentation applications.

Estudo e desenvolvimento de algoritmos criptográficos para redes de sensores sem fio, utilizando técnicas de programação genética

Cryptography is the main form to obtain security in any network. Even in networks with great energy consumption restrictions, processing and memory limitations, as the Wireless Sensors Networks (WSN), this is no different. Aiming to improve the cryptography performance, security and the lifetime of these networks, we propose a new cryptographic algorithm developed through the Genetic Programming (GP) techniques. For the development of the cryptographic algorithm’s fitness criteria, established by the genetic GP, nine new cryptographic algorithms were tested: AES, Blowfish, DES, RC6, Skipjack, Twofish, T-DES, XTEA and XXTEA. Starting from these tests, fitness functions was build taking into account the execution time, occupied memory space, maximum deviation, irregular deviation and correlation coefficient. After obtaining the genetic GP, the CRYSEED and CRYSEED2 was created, algorithms for the 8-bits devices, optimized for WSNs, i.e., with low complexity, few memory consumption and good security for sensing and instrumentation applications.

Estratégias distribuídas para a coexistência de redes de banda larga sem fio em bandas não-licensiadas

The increasing demand for Internet data traffic in wireless broadband access networks requires both the development of efficient, novel wireless broadband access technologies and the allocation of new spectrum bands for that purpose. The introduction of a great number of small cells in cellular networks allied to the complimentary adoption of Wireless Local Area Network (WLAN) technologies in unlicensed spectrum is one of the most promising concepts to attend this demand. One alternative is the aggregation of Industrial, Science and Medical (ISM) unlicensed spectrum to licensed bands, using wireless networks defined by Institute of Electrical and Electronics Engineers (IEEE) and Third Generation Partnership Project (3GPP). While IEEE 802.11 (Wi-Fi) networks are aggregated to Long Term Evolution (LTE) small cells via LTE / WLAN Aggregation (LWA), in proposals like Unlicensed LTE (LTE-U) and LWA the LTE air interface itself is used for transmission on the unlicensed band. Wi-Fi technology is widespread and operates in the same 5 GHz ISM spectrum bands as the LTE proposals, which may bring performance decrease due to the coexistence of both technologies in the same spectrum bands. Besides, there is the need to improve Wi-Fi operation to support scenarios with a large number of neighbor Overlapping Basic Subscriber Set (OBSS) networks, with a large number of Wi-Fi nodes (i.e. dense deployments). It is long known that the overall Wi-Fi performance falls sharply with the increase of Wi-Fi nodes sharing the channel, therefore there is the need for introducing mechanisms to increase its spectral efficiency. This work is dedicated to the study of coexistence between different wireless broadband access systems operating in the same unlicensed spectrum bands, and how to solve the coexistence problems via distributed coordination mechanisms. The problem of coexistence between different networks (i.e. LTE and Wi-Fi) and the problem of coexistence between different networks of the same technology (i.e. multiple Wi-Fi OBSSs) is analyzed both qualitatively and quantitatively via system-level simulations, and the main issues to be faced are identified from these results. From that, distributed coordination mechanisms are proposed and evaluated via system-level simulations, both for the inter-technology coexistence problem and intra-technology coexistence problem. Results indicate that the proposed solutions provide significant gains when compare to the situation without distributed coordination.