Integrating job scheduling and constrained network routing

2010 ◽  
Vol 36 ◽  
pp. 57-64
Author(s):  
M. Gamst
Networks ◽  
2012 ◽  
Vol 61 (3) ◽  
pp. 248-262 ◽  
Author(s):  
Mette Gamst ◽  
David Pisinger

2010 ◽  
Vol 30 (8) ◽  
pp. 2066-2069
Author(s):  
Yong-cai TAO ◽  
Lei SHI

2011 ◽  
Vol 31 (2) ◽  
pp. 332-334
Author(s):  
Shao-qiong ZHOU ◽  
Yi XU ◽  
Li JIANG ◽  
Rui WANG

2020 ◽  
Vol 15 ◽  
Author(s):  
Weiwen Zhang ◽  
Long Wang ◽  
Theint Theint Aye ◽  
Juniarto Samsudin ◽  
Yongqing Zhu

Background: Genotype imputation as a service is developed to enable researchers to estimate genotypes on haplotyped data without performing whole genome sequencing. However, genotype imputation is computation intensive and thus it remains a challenge to satisfy the high performance requirement of genome wide association study (GWAS). Objective: In this paper, we propose a high performance computing solution for genotype imputation on supercomputers to enhance its execution performance. Method: We design and implement a multi-level parallelization that includes job level, process level and thread level parallelization, enabled by job scheduling management, message passing interface (MPI) and OpenMP, respectively. It involves job distribution, chunk partition and execution, parallelized iteration for imputation and data concatenation. Due to the design of multi-level parallelization, we can exploit the multi-machine/multi-core architecture to improve the performance of genotype imputation. Results: Experiment results show that our proposed method can outperform the Hadoop-based implementation of genotype imputation. Moreover, we conduct the experiments on supercomputers to evaluate the performance of the proposed method. The evaluation shows that it can significantly shorten the execution time, thus improving the performance for genotype imputation. Conclusion: The proposed multi-level parallelization, when deployed as an imputation as a service, will facilitate bioinformatics researchers in Singapore to conduct genotype imputation and enhance the association study.


2016 ◽  
Vol 26 (1) ◽  
pp. 17
Author(s):  
Carlos Deyvinson Reges Bessa

ABSTRACTThis work aims to study which wireless sensor network routing protocol is more suitable for Smart Grids applications, through simulation of AODV protocols, AOMDV, DSDV and HTR in the NS2 simulation environment. Was simulated a network based on a residential area with 47 residences, with one node for each residence and one base station, located about 25m from the other nodes. Many parameters, such as packet loss, throughput, delay, jitter and energy consumption were tested.  The network was increased to 78 and 93 nodes in order to evaluate the behavior of the protocols in larger networks. The tests proved that the HTR is the routing protocol that has the best results in performance and second best in energy consumption. The DSDV had the worst performance according to the tests.Key words.- Smart grid, QoS analysis, Wireless sensor networks, Routing protocols.RESUMENEste trabajo tiene como objetivo estudiar el protocolo de enrutamiento de la red de sensores inalámbricos es más adecuado para aplicaciones de redes inteligentes, a través de la simulación de protocolos AODV, AOMDV, DSDV y HTR en el entorno de simulación NS2. Se simuló una red basada en una zona residencial con 47 residencias, con un nodo para cada residencia y una estación base, situada a unos 25 metros de los otros nodos. Muchos parámetros, tales como la pérdida de paquetes, rendimiento, retardo, jitter y el consumo de energía se probaron. La red se incrementó a 78 y 93 nodos con el fin de evaluar el comportamiento de los protocolos de redes más grandes. Las pruebas demostraron que el HTR es el protocolo de enrutamiento que tiene los mejores resultados en el rendimiento y el segundo mejor en el consumo de energía. El DSDV tuvo el peor desempeño de acuerdo a las pruebas.Palabras clave.- redes inteligentes, análisis de calidad de servicio, redes de sensores inalámbricas, protocolos de enrutamiento.


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