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Maintenance is an important activity in industry. It is performed either to revive a machine/component or to prevent it from breaking down. Different strategies have evolved through time, bringing maintenance to its current state: condition-based and predictive maintenances. This evolution was due to the increasing demand of reliability in industry. The key process of condition-based and predictive...
In this paper, we deal with the problem of distributed data fusion in unsafe large-scale sensor networks. Data fusion application is the phase of processing the collected data by sensor nodes before sending it the end user. During this phase, resource failures are more likely to occur and can have an adverse effect on the application. Hence, we introduce first an efficient self-stabilizing algorithm...
In this paper, we deal with the problem of scheduling streaming applications on unreliable heterogeneous platforms. We use the realistic one-port model with full computation/communication overlap. We deal with three optimization objectives. The first two, latency and throughput, are performance-related while the third, tolerating a given number of processor failures, is reliability-oriented. The major...
Most list scheduling heuristics rely on a simple platform model where communication contention is not taken into account. In addition, it is generally assumed that processors in the systems are completely safe. To schedule precedence graphs in a more realistic framework, we introduce an efficient fault tolerant scheduling algorithm that is both contention-aware and capable of supporting epsiv arbitrary...
Fault tolerance and latency are important requirements in several applications which are time critical in nature: such applications require guaranties in terms of latency, even when processors are subject to failures. In this paper, we propose a fault tolerant scheduling heuristic for mapping precedence task graphs on heterogeneous systems. Our approach is based on an active replication scheme, capable...
This paper presents a new bi-objective greedy heuristic for scheduling parallel applications on heterogeneous distributed computing systems. The proposed algorithm which is called BSA (bi-objective scheduling algorithm) takes into account not only the time makespan but also the failure probability of the application. Since it is not usually possible to achieve the two conflicting objectives (performance...
Previous work on scheduling dynamic competitive jobs is focused on multiprocessors configurations. This paper presents a new distributed dynamic scheduling scheme for sporadic real-time jobs with arbitrary precedence relations on arbitrary wide networks. A job is modeled by a directed acyclic graph (DAG). Jobs arrive on any site at any time and compete for the computational resources of the network...
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