874 resultados para Distributed data access
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Real-time embedded applications require to process large amounts of data within small time windows. Parallelize and distribute workloads adaptively is suitable solution for computational demanding applications. The purpose of the Parallel Real-Time Framework for distributed adaptive embedded systems is to guarantee local and distributed processing of real-time applications. This work identifies some promising research directions for parallel/distributed real-time embedded applications.
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Embedded real-time applications increasingly present high computation requirements, which need to be completed within specific deadlines, but that present highly variable patterns, depending on the set of data available in a determined instant. The current trend to provide parallel processing in the embedded domain allows providing higher processing power; however, it does not address the variability in the processing pattern. Dimensioning each device for its worst-case scenario implies lower average utilization, and increased available, but unusable, processing in the overall system. A solution for this problem is to extend the parallel execution of the applications, allowing networked nodes to distribute the workload, on peak situations, to neighbour nodes. In this context, this report proposes a framework to develop parallel and distributed real-time embedded applications, transparently using OpenMP and Message Passing Interface (MPI), within a programming model based on OpenMP. The technical report also devises an integrated timing model, which enables the structured reasoning on the timing behaviour of these hybrid architectures.
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This paper addresses sensor network applications which need to obtain an accurate image of physical phenomena and do so with a high sampling rate in both time and space. We present a fast and scalable approach for obtaining an approximate representation of all sensor readings at high sampling rate for quickly reacting to critical events in a physical environment. This approach is an improvement on previous work in that after the new approach has undergone a startup phase then the new approach can use a very small sampling period.
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OBJECTIVE : To analyze the main predictors of access to medicines for persons who experienced acute health conditions. METHODS : This was a cross-sectional analytic study, based on data from household surveys. We examined the predictors of: (1) seeking care for acute illness in the formal health care system and (2) obtaining all medicines sought for the acute condition. RESULTS : The significant predictors of seeking health care for acute illnesses were urban geographic location, head of household with secondary school education or above, age under 15, severity of illness perceived by the respondent, and having health insurance. The most important predictor of obtaining full access to medicines was seeking care in the formal health care system. People who sought care in the formal system were three times more likely to receive all the medicines sought (OR 3.0, 95%CI 2.3;4.0). For those who sought care in the formal health system, the strongest predictors of full access to medicines were seeking care in the private sector, having secondary school education or above, and positive perceptions of quality of health care and medicines in public sector health facilities. For patients who did not seek care in the formal health system, full access to medicines was more likely in Honduras or Nicaragua than in Guatemala. Urban geographic location, higher economic status, and male gender were also significant predictors. CONCLUSIONS : A substantial part of the population in these three countries sought and obtained medicines outside of the formal health care system, which may compromise quality of care and pose a risk to patients. Determinants of full access to medicines inside and outside the formal health care system differ, and thus may require different strategies to improve access to medicines.
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Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared band-limited digital communication network. However, the use of a shared communication network, in contrast to using several dedicated independent connections, introduces new challenges which are even more acute in large scale and dense networked control systems. In this paper we investigate a recently introduced technique of gathering information from a dense sensor network to be used in networked control applications. Obtaining efficiently an approximate interpolation of the sensed data is exploited as offering a good tradeoff between accuracy in the measurement of the input signals and the delay to the actuation. These are important aspects to take into account for the quality of control. We introduce a variation to the state-of-the-art algorithms which we prove to perform relatively better because it takes into account the changes over time of the input signal within the process of obtaining an approximate interpolation.
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We focus on large-scale and dense deeply embedded systems where, due to the large amount of information generated by all nodes, even simple aggregate computations such as the minimum value (MIN) of the sensor readings become notoriously expensive to obtain. Recent research has exploited a dominance-based medium access control(MAC) protocol, the CAN bus, for computing aggregated quantities in wired systems. For example, MIN can be computed efficiently and an interpolation function which approximates sensor data in an area can be obtained efficiently as well. Dominance-based MAC protocols have recently been proposed for wireless channels and these protocols can be expected to be used for achieving highly scalable aggregate computations in wireless systems. But no experimental demonstration is currently available in the research literature. In this paper, we demonstrate that highly scalable aggregate computations in wireless networks are possible. We do so by (i) building a new wireless hardware platform with appropriate characteristics for making dominance-based MAC protocols efficient, (ii) implementing dominance-based MAC protocols on this platform, (iii) implementing distributed algorithms for aggregate computations (MIN, MAX, Interpolation) using the new implementation of the dominance-based MAC protocol and (iv) performing experiments to prove that such highly scalable aggregate computations in wireless networks are possible.
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Hexagonal wireless sensor network refers to a network topology where a subset of nodes have six peer neighbors. These nodes form a backbone for multi-hop communications. In a previous work, we proposed the use of hexagonal topology in wireless sensor networks and discussed its properties in relation to real-time (bounded latency) multi-hop communications in large-scale deployments. In that work, we did not consider the problem of hexagonal topology formation in practice - which is the subject of this research. In this paper, we present a decentralized algorithm that forms the hexagonal topology backbone in an arbitrary but sufficiently dense network deployment. We implemented a prototype of our algorithm in NesC for TinyOS based platforms. We present data from field tests of our implementation, collected using a deployment of fifty wireless sensor nodes.
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In this paper, we address the problem of sharing a wireless channel among a set of sporadic message streams where a message stream issues transmission requests with real-time deadlines. We propose a collision-free wireless medium access control (MAC) protocol which implements static-priority scheduling, supports a large number of priority levels and is fully distributed. It is an adaptation to a wireless channel of the dominance protocol used in the CAN bus. But, unlike that protocol, our protocol does not require a node having the ability to receive an incoming bit from the channel while transmitting to the channel. The evaluation of the protocol with real embedded computing platforms is presented to show that the proposed protocol is in fact collision-free and prioritized. We measure the response times of our implementation and show that the response-time analysis developed for the protocol offers an upper bound on the response times.
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Consider a network where all nodes share a single broadcast domain such as a wired broadcast network. Nodes take sensor readings but individual sensor readings are not the most important pieces of data in the system. Instead, we are interested in aggregated quantities of the sensor readings such as minimum and maximum values, the number of nodes and the median among a set of sensor readings on different nodes. In this paper we show that a prioritized medium access control (MAC) protocol may advantageously be exploited to efficiently compute aggregated quantities of sensor readings. In this context, we propose a distributed algorithm that has a very low time and message-complexity for computing certain aggregated quantities. Importantly, we show that if every sensor node knows its geographical location, then sensor data can be interpolated with our novel distributed algorithm, and the message-complexity of the algorithm is independent of the number of nodes. Such an interpolation of sensor data can be used to compute any desired function; for example the temperature gradient in a room (e.g., industrial plant) densely populated with sensor nodes, or the gas concentration gradient within a pipeline or traffic tunnel.
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Wireless Sensor Networks (WSNs) are highly distributed systems in which resource allocation (bandwidth, memory) must be performed efficiently to provide a minimum acceptable Quality of Service (QoS) to the regions where critical events occur. In fact, if resources are statically assigned independently from the location and instant of the events, these resources will definitely be misused. In other words, it is more efficient to dynamically grant more resources to sensor nodes affected by critical events, thus providing better network resource management and reducing endto- end delays of event notification and tracking. In this paper, we discuss the use of a WSN management architecture based on the active network management paradigm to provide the real-time tracking and reporting of dynamic events while ensuring efficient resource utilization. The active network management paradigm allows packets to transport not only data, but also program scripts that will be executed in the nodes to dynamically modify the operation of the network. This presumes the use of a runtime execution environment (middleware) in each node to interpret the script. We consider hierarchical (e.g. cluster-tree, two-tiered architecture) WSN topologies since they have been used to improve the timing performance of WSNs as they support deterministic medium access control protocols.
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We present a distributed algorithm for cyber-physical systems to obtain a snapshot of sensor data. The snapshot is an approximate representation of sensor data; it is an interpolation as a function of space coordinates. The new algorithm exploits a prioritized medium access control (MAC) protocol to efficiently transmit information of the sensor data. It scales to a very large number of sensors and it is able to operate in the presence of sensor faults.
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Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems
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The growing heterogeneity of networks, devices and consumption conditions asks for flexible and adaptive video coding solutions. The compression power of the HEVC standard and the benefits of the distributed video coding paradigm allow designing novel scalable coding solutions with improved error robustness and low encoding complexity while still achieving competitive compression efficiency. In this context, this paper proposes a novel scalable video coding scheme using a HEVC Intra compliant base layer and a distributed coding approach in the enhancement layers (EL). This design inherits the HEVC compression efficiency while providing low encoding complexity at the enhancement layers. The temporal correlation is exploited at the decoder to create the EL side information (SI) residue, an estimation of the original residue. The EL encoder sends only the data that cannot be inferred at the decoder, thus exploiting the correlation between the original and SI residues; however, this correlation must be characterized with an accurate correlation model to obtain coding efficiency improvements. Therefore, this paper proposes a correlation modeling solution to be used at both encoder and decoder, without requiring a feedback channel. Experiments results confirm that the proposed scalable coding scheme has lower encoding complexity and provides BD-Rate savings up to 3.43% in comparison with the HEVC Intra scalable extension under development. © 2014 IEEE.
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OBJECTIVE To describe the health status and access to care of forced-return Mexican migrants deported through the Mexico-United States border and to compare it with the situation of voluntary-return migrants. METHODS Secondary data analysis from the Survey on Migration in Mexico’s Northern Border from 2012. This is a continuous survey, designed to describe migration flows between Mexico and the United States, with a mobile-population sampling design. We analyzed indicators of health and access to care among deported migrants, and compare them with voluntary-return migrants. Our analysis sample included 2,680 voluntary-return migrants, and 6,862 deportees. We employ an ordinal multiple logistic regression model, to compare the adjusted odds of having worst self-reported health between the studied groups. RESULTS As compared to voluntary-return migrants, deportees were less likely to have medical insurance in the United States (OR = 0.05; 95%CI 0.04;0.06). In the regression model a poorer self-perceived health was found to be associated with having been deported (OR = 1.71, 95%CI 1.52;1.92), as well as age (OR = 1.03, 95%CI 1.02;1.03) and years of education (OR = 0.94 95%CI 0.93;0.95). CONCLUSIONS According to our results, deportees had less access to care while in the United States, as compared with voluntary-return migrants. Our results also showed an independent and statistically significant association between deportation and having poorer self-perceived health. To promote the health and access to care of deported Mexican migrants coming back from the United States, new health and social policies are required.
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Consider the problem of sharing a wireless channel between a set of computer nodes. Hidden nodes exist and there is no base station. Each computer node hosts a set of sporadic message streams where a message stream releases messages with real-time deadlines. We propose a collision-free wireless medium access control (MAC) protocol which implements staticpriority scheduling. The MAC protocol allows multiple masters and is fully distributed. It neither relies on synchronized clocks nor out-of-band signaling; it is an adaptation to a wireless channel of the dominance protocol used in the CAN bus. But unlike that protocol, our protocol does not require a node having the ability to receive an incoming bit from the channel while transmitting to the channel. Our protocol has the key feature of not only being prioritized and collision-free but also dealing successfully with hidden nodes. This key feature enables schedulability analysis of sporadic message streams in multihop networks.