Distributed Latency-Energy Minimization and interference avoidance in TDMA Wireless Sensor Networks

This paper presents Latency-Energy Minimization Medium Access (LEMMA), a new TDMA-based MAC protocol for Wireless Sensor Networks (WSNs), specially suited to extend the lifetime of networks supporting alarm-driven, delay-sensitive applications characterized by convergecast traffic patterns and sporadic traffic generation. Its cascading time-slot assignment scheme conciliates low end-to-end latency with a low duty-cycle, while supporting multi-sink WSN topologies. Unlike most of the current solutions, LEMMA’s time-slot allocation protocol makes decisions based on the interference actually experienced by the nodes, instead of following the simple but potentially ineffective n-hop approach. Simulation results are presented to demonstrate the ineffectiveness of the n-hop time-slot allocation in comparison with LEMMA, as well as to evaluate the performance of LEMMA against L-MAC, T-MAC and Low Power Listening. The results show that under the target scenario conditions, LEMMA presents lower interference between assigned time-slots and lower end-to-end latency, while matching its best contender in terms of energy-efficiency.     

Physical and mechanical characterization of phyllites and metagreywackes in central Portugal

This work defines the physical and mechanical characteristics of phyllites and metagreywackes belonging to a schist–greywacke complex in central Portugal. The index properties, point load strength, uniaxial compressive strength, slake durability and Schmidt rebound hardness were determined. In general, the metagreywackes gave a higher strength than phyllites with the same weathering degree. Possible correlations and estimation models were established and compared with the equations obtained by different researchers.     

Multiscale Fitting Procedure Using Markov Modulated Poisson Processes

This paper proposes a parameter fitting procedure using Markov Modulated Poisson Processes (MMPPs) that leads to accurate estimates of queuing behavior for network traffic exhibiting long-range dependence behavior. The procedure matches both the autocovariance and marginal distribution of the counting process. A major feature is that the number of states is not fixed a priori, and can be adapted to the particular trace being modeled. The MMPP is constructed as a superposition of L 2-MMPPs and one M-MMPP. The 2-MMPPs are designed to match the autocovariance and the M-MMPP to match the marginal distribution. Each 2-MMPP models a specific time-scale of the data. The procedure starts by approximating the autocovariance by a weighted sum of exponential functions that model the autocovariance of the 2-MMPPs. The autocovariance tail can be adjusted to capture the long-range dependence characteristics of the traffic, up to the time-scales of interest to the system under study. The procedure then fits the M-MMPP parameters in order to match the marginal distribution, within the constraints imposed by the autocovariance matching. The number of states is also determined as part of this step. The final MMPP with M2 ^L states is obtained by superposing the L 2-MMPPs and the M-MMPP. We apply the inference procedure to traffic traces exhibiting long-range dependence and evaluate its queuing behavior through simulation. Very good results are obtained, both in terms of queuing behavior and number of states, for the traces used, which include the well-known Bellcore traces.     

Transmission Fiber Chromatic Dispersion Dependence on Temperature: Implications on 40 Gb/s Performance

In this letter, we will evaluate the performance degradation of a 40 km high‐speed (40 Gb/s) optical system, induced by optical fiber variations of the chromatic dispersion induced by temperature changes. The chromatic dispersion temperature sensitivity will be estimated based on the signal quality parameters.     

A data mining approach to classify serum creatinine values in patients undergoing continuous ambulatory peritoneal dialysis

Wireless Networks - Continuous ambulatory peritoneal dialysis (CAPD) is a treatment used by patients in the end-stage of chronic kidney diseases. Those patients need to be monitored using blood...     

SDN-based architecture for providing quality of service to high-performance distributed applications

The specification of quality of service (QoS) requirements in most of the existing networks is still challenging. In part, traditional network environments are limited by their high administrative cost, although software-defined networks (SDNs), a newer network paradigm, simplify the management of the whole network infrastructure. In fact, SDN provides a simple way to effectively develop QoS provisioning mechanisms. In this sense, we explore the SDN model and its flexibility to develop a QoS provisioning architecture. Through the use of our new architecture, network operators are able to specify QoS levels in a simple way. Each individual data flow can be addressed, and the architecture we propose also negotiates the QoS requirements between the network controller and applications. On the other hand, the network controller continuously monitors the network environment. Then, it allocates network elements resources and prioritizes traffic, adjusting the network performance. We evaluate the feasibility of our QoS provisioning mechanism by presenting three experimental setups under realistic scenarios. For example, for a given scenario where we evaluate file transfers, our results indicate that the additional SDN modules present negligible overhead. Moreover, for a given setup, we observe a reduction of up to 82% in the file transfer times.     

Classification and evaluation of IoT brokers: A methodology

Since the term Internet of Things (IoT) was coined by Kevin Ashton in 1999, a number of middleware platforms have been developed to cope with important challenges such as the integration of different technologies. In this context of heterogeneous technologies, IoT message brokers become critical elements for the proper function of smart systems and wireless sensor networks (WSN) infrastructures. There are several evaluations made on IoT messaging middleware performance. Nevertheless, most of them ignore crucial aspects of the IoT context that also need to be included, such as reliability and other qualitative aspects. Thus, in this article, we propose a methodology for classification and evaluation of IoT brokers to help the scientific community and technology industry on evaluating them according to their interests, without leaving out important aspects for the context of smart environments. Our methodology bases its qualitative evaluations on the ISO/IEC 25000 (SQuaRE) set of standards and its quantitative evaluations on Jain's process for performance evaluation. We developed a case study to illustrate our proposal with 12 different open-source brokers, validating the feasibility of our methodological approach.     

Analysis of high voltage step-up nonisolated DC–DC boost converters

A high voltage step-up nonisolated DC–DC converter based on coupled inductors suitable to photovoltaic (PV) systems applications is proposed in this paper. Considering that numerous approaches exist to extend the voltage conversion ratio of DC–DC converters that do not use transformers, a detailed comparison is also presented among the proposed converter and other popular topologies such as the conventional boost converter and the quadratic boost converter. The qualitative analysis of the coupled-inductor-based topology is developed so that a design procedure can be obtained, from which an experimental prototype is implemented to validate the theoretical assumptions.     

Can multiscale traffic analysis be used to differentiate Internet applications?

An accurate mapping of Internet traffic to applications can be important for a broad range of network management and measurement tasks, including traffic engineering, service differentiation, performance/failure monitoring and security. Traditional mapping approaches have become increasingly inaccurate because many applications use non-default or ephemeral port numbers, use well-known port numbers associated with other applications, change application signatures or use traffic encryption. In this paper we will demonstrate that multiscale traffic analysis based on multi-order wavelet spectrum can be used as a discriminator of Internet applications traffic profiles. By performing clustering analysis over the multiscale wavelet spectrum coefficients that are inferred from the measured traffic, the proposed methodology is able to efficiently differentiate different IP applications without using any payload information. This characteristic will allow the differentiation of traffic flows in unencrypted and encrypted scenarios. In order to compare the differentiating potential of different traffic application data, upload, download and joint upload and download flow statistics are considered to evaluate the identification approach for each selected protocol. Moreover, we also evaluate which timescales and spectrum orders are more relevant for the traffic differentiation. From the analysis of the obtained results we can conclude that the proposed methodology is able to achieve good identification results using a small set of timescales of a single order wavelet spectrum of a general raw traffic statistic.