60 resultados para Hadoop distributed file system (HDFS)


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In this paper, we analyse the ability of Profibus fieldbus to cope with the real-time requirements of a Distributed Computer Control System (DCCS), where messages associated to discrete events must be made available within a maximum bound time. Our methodology is based on the knowledge of real-time traffic characteristics, setting the network parameters in order to cope with timing requirements. Since non-real-time traffic characteristics are usually unknown at the design stage, we consider an operational profile where, constraining non-real-time traffic at the application level, we assure that realtime requirements are met.

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It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation.

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In this paper, we analyse the ability of P-NET [1] fieldbus to cope with the timing requirements of a Distributed Computer Control System (DCCS), where messages associated to discrete events should be made available within a maximum bound time. The main objective of this work is to analyse how the network access and queueing delays, imposed by P-NET’s virtual token Medium Access Control (MAC) mechanism, affect the realtime behaviour of the supported DCCS.

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Moving towards autonomous operation and management of increasingly complex open distributed real-time systems poses very significant challenges. This is particularly true when reaction to events must be done in a timely and predictable manner while guaranteeing Quality of Service (QoS) constraints imposed by users, the environment, or applications. In these scenarios, the system should be able to maintain a global feasible QoS level while allowing individual nodes to autonomously adapt under different constraints of resource availability and input quality. This paper shows how decentralised coordination of a group of autonomous interdependent nodes can emerge with little communication, based on the robust self-organising principles of feedback. Positive feedback is used to reinforce the selection of the new desired global service solution, while negative feedback discourages nodes to act in a greedy fashion as this adversely impacts on the provided service levels at neighbouring nodes. The proposed protocol is general enough to be used in a wide range of scenarios characterised by a high degree of openness and dynamism where coordination tasks need to be time dependent. As the reported results demonstrate, it requires less messages to be exchanged and it is faster to achieve a globally acceptable near-optimal solution than other available approaches.

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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 work focuses on highly dynamic distributed systems with Quality of Service (QoS) constraints (most importantly real-time constraints). To that purpose, real-time applications may benefit from code offloading techniques, so that parts of the application can be offloaded and executed, as services, by neighbour nodes, which are willing to cooperate in such computations. These applications explicitly state their QoS requirements, which are translated into resource requirements, in order to evaluate the feasibility of accepting other applications in the system.

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Replication is a proven concept for increasing the availability of distributed systems. However, actively replicating every software component in distributed embedded systems may not be a feasible approach. Not only the available resources are often limited, but also the imposed overhead could significantly degrade the system's performance. The paper proposes heuristics to dynamically determine which components to replicate based on their significance to the system as a whole, its consequent number of passive replicas, and where to place those replicas in the network. The results show that the proposed heuristics achieve a reasonably higher system's availability than static offline decisions when lower replication ratios are imposed due to resource or cost limitations. The paper introduces a novel approach to coordinate the activation of passive replicas in interdependent distributed environments. The proposed distributed coordination model reduces the complexity of the needed interactions among nodes and is faster to converge to a globally acceptable solution than a traditional centralised approach.

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As the complexity of embedded systems increases, multiple services have to compete for the limited resources of a single device. This situation is particularly critical for small embedded devices used in consumer electronics, telecommunication, industrial automation, or automotive systems. In fact, in order to satisfy a set of constraints related to weight, space, and energy consumption, these systems are typically built using microprocessors with lower processing power and limited resources. The CooperatES framework has recently been proposed to tackle these challenges, allowing resource constrained devices to collectively execute services with their neighbours in order to fulfil the complex Quality of Service (QoS) constraints imposed by users and applications. In order to demonstrate the framework's concepts, a prototype is being implemented in the Android platform. This paper discusses key challenges that must be addressed and possible directions to incorporate the desired real-time behaviour in Android.

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In distributed soft real-time systems, maximizing the aggregate quality-of-service (QoS) is a typical system-wide goal, and addressing the problem through distributed optimization is challenging. Subtasks are subject to unpredictable failures in many practical environments, and this makes the problem much harder. In this paper, we present a robust optimization framework for maximizing the aggregate QoS in the presence of random failures. We introduce the notion of K-failure to bound the effect of random failures on schedulability. Using this notion we define the concept of K-robustness that quantifies the degree of robustness on QoS guarantee in a probabilistic sense. The parameter K helps to tradeoff achievable QoS versus robustness. The proposed robust framework produces optimal solutions through distributed computations on the basis of Lagrangian duality, and we present some implementation techniques. Our simulation results show that the proposed framework can probabilistically guarantee sub-optimal QoS which remains feasible even in the presence of random failures.

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Replication is a proven concept for increasing the availability of distributed systems. However, actively replicating every software component in distributed embedded systems may not be a feasible approach. Not only the available resources are often limited, but also the imposed overhead could significantly degrade the system’s performance. This paper proposes heuristics to dynamically determine which components to replicate based on their significance to the system as a whole, its consequent number of passive replicas, and where to place those replicas in the network. The activation of passive replicas is coordinated through a fast convergence protocol that reduces the complexity of the needed interactions among nodes until a new collective global service solution is determined.

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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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This paper reports on the design and development of an Android-based context-aware system to support Erasmus students during their mobility in Porto. It enables: (i) guest users to create, rate and store personal points of interest (POI) in a private, local on board database; and (ii) authenticated users to upload and share POI as well as get and rate recommended POI from the shared central database. The system is a distributed client / server application. The server interacts with a central database that maintains the user profiles and the shared POI organized by category and rating. The Android GUI application works both as a standalone application and as a client module. In standalone mode, guest users have access to generic info, a map-based interface and a local database to store and retrieve personal POI. Upon successful authentication, users can, additionally, share POI as well as get and rate recommendations sorted by category, rating and distance-to-user.

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This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.

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Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts.

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Belief revision is a critical issue in real world DAI applications. A Multi-Agent System not only has to cope with the intrinsic incompleteness and the constant change of the available knowledge (as in the case of its stand alone counterparts), but also has to deal with possible conflicts between the agents’ perspectives. Each semi-autonomous agent, designed as a combination of a problem solver – assumption based truth maintenance system (ATMS), was enriched with improved capabilities: a distributed context management facility allowing the user to dynamically focus on the more pertinent contexts, and a distributed belief revision algorithm with two levels of consistency. This work contributions include: (i) a concise representation of the shared external facts; (ii) a simple and innovative methodology to achieve distributed context management; and (iii) a reduced inter-agent data exchange format. The different levels of consistency adopted were based on the relevance of the data under consideration: higher relevance data (detected inconsistencies) was granted global consistency while less relevant data (system facts) was assigned local consistency. These abilities are fully supported by the ATMS standard functionalities.