Mutation-Like Oriented Diversity for Dependability Improvement: A Distributed System Case Study

Author(s):  
Daniel O. Bortolas ◽  
Avelino F. Zorzo ◽  
Eduardo A. Bezerra ◽  
Flavio M. de Oliveira
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Author(s):  
Teruaki Ito ◽  
Shuichi Fukuda

Abstract The paper describes the methodology of concurrent migration with optimal utilization of existing computer resources which has been used in organizations. Concurrent migration bypasses a transitional system which is described as migration model. Migration model includes modules for resource utilization, minimum modification, advance implementation, continuous utilization and concurrent development. Procedure for concurrent migration includes seven steps in which the migration system is included. A case study of concurrent migration of a centralized system converted to a distributed system based on remote/local (R/L) computing is presented to show the availability of the model and the procedure.


Author(s):  
Anna Maria Nestorov ◽  
Alberto Scolari ◽  
Enrico Reggiani ◽  
Luca Stornaiuolo ◽  
Marco D. Santambrogio
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Author(s):  
Antonio Menendez Leonel de Cervantes ◽  
Hector Benitez Perez

<p>Node-Availability is a new metric that based on processor utilization, free RAM and number of processes queued at a node, compares different workload levels of the nodes participating in a distributed system. Dynamic scheduling and Load-Balancing in distributed systems can be achieved through the Node-Availability metric as decision criterion, even without previously knowing the execution time of the processes, nor other information about them such as process communication requirements.<br /> This paper also presents a case study which shows that the metric is feasible to implement in conjunction with a dynamic Load-Balancing algorithm, obtaining an acceptable performance.</p>


Author(s):  
A. Menéndez-Leonel de Cervantes ◽  
H. Benítez-Pérez

The objective of this paper is to show the use of a global Scheduling Strategy based on the analysis of a Real-Time Distributed System. The use of a Networked Controlled System as a case study shows that the performance of the system depends not only on the sampling periods of its individual components, but also on the time dispersion amongst these periods. It is also shown that it is possible to have a schedulable but unstable RTDS.


2021 ◽  
Vol 64 (1) ◽  
pp. 161-175
Author(s):  
Joshua J. Jackson ◽  
Michael D. Montross

HighlightsTotal transportation costs were reduced by 32% to 63% with distributed biobutanol depots.An 8 km distance to the depot manifested the most desirable transportation costs.Across regions, biomass transport costs from field to depot were similar at equivalent distances.Abstract. The transportation efficiencies of centralized biomass processing facilities were compared to a proposed distributed preprocessing network with centralized refining facilities. Centralized biomass processing was defined as transport of baled corn stover directly from the field to the refinery. Distributed preprocessing with centralized refining was defined as transport of baled corn stover from the field to a biobutanol preprocessing depot and transport of completely dewatered crude biobutanol solution from the depot to a centralized refinery. For both systems, the locations of the corn fields, as identified through the cropland data layer, and of the refinery were fixed. For the distributed system, the biobutanol depot locations were variable and depended on different maximum transport distances (8 to 80 km) from the field to the depot. In this case study, site-specific transportation costs and biobutanol production capacities were developed for different agricultural regions in Kentucky. The distributed system produced a 32% to 63% reduction in total transportation cost with decreased (50% to 90%) fuel use as compared to the centralized system. The GIS transportation model demonstrated that on-farm biofuel production could be an effective means of producing biofuel and reducing transportation costs. Keywords: Biomass transport, Depot, Distributed biomass collection, GIS location-allocation, Minimize facilities, Satellite facilities.


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