On bandwidth reservation for optimal resource utilization in high-performance networks

2012 ◽  
Author(s):  
Poonam Dharam ◽  
Qishi Wu ◽  
Mengxia Zhu
Keyword(s):  
Resource Utilization ◽  
High Performance ◽  
Bandwidth Reservation ◽  
Optimal Resource

Hierarchical Load Balancing Model by Optimal Resource Utilization

2021 ◽  
pp. 150-164
Author(s):  
Jagdish Chandra Patni
Keyword(s):  
Load Balancing ◽  
Grid Computing ◽  
Resource Utilization ◽  
Resource Availability ◽  
High Performance ◽  
Low Cost ◽  
Original Form ◽  
Computing Paradigm ◽  
Optimal Resource ◽  
Performance Computing

Powerful computational capabilities and resource availability at a low cost is the utmost demand for high performance computing. The resources for computing can viewed as the edges of an interconnected grid. It can attain the capabilities of grid computing by balancing the load at various levels. Since the nature of resources are heterogeneous and distributed geographically, the grid computing paradigm in its original form cannot be used to meet the requirements, so it can use the capabilities of the cloud and other technologies to achieve the goal. Resource heterogeneity makes grid computing more dynamic and challenging. Therefore, in this article the problem of scalability, heterogeneity and adaptability of grid computing is discussed with a perspective of providing high computing, load balancing and availability of resources.

Farming and optimal resource utilization in Guyuan, China

Food Policy ◽  
1986 ◽  
Vol 11 (2) ◽  
pp. 133-142 ◽  
Author(s):  
Feng-Shu Zhu ◽  
Refugio I. Rochin ◽  
Yen-Shong Chiao
Keyword(s):  
Resource Utilization ◽  
Optimal Resource

scholarly journals N-Doped Animal Keratin Waste Porous Biochar derived from Trapa Natans Husks

Materials ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 987
Author(s):  
Wenjun Yin ◽  
Zhonghua Zhang ◽  
Tongcai Liu ◽  
Jiao Xu ◽  
Shaoze Xiao ◽  
...  
Keyword(s):  
Pore Size ◽  
Resource Utilization ◽  
High Performance ◽  
Fish Meal ◽  
Chemical Properties ◽  
Fish Scales ◽  
Surface Chemical ◽  
Microporous Structure ◽  
Trapa Natans ◽  
Crab Meat

Animal-keratin-wastes (AKWs), horns (HN), hair (HR), puffed waterfowl feathers (PF), hydrolyzed waterfowl feathers (HF), hydrolyzed fish meal (HM), crab meat (CM), feathers (FR), shrimp chaff (SC), fish scales (FS), and waste leather (WL) were used as modifiers to prepare animal-keratin-wastes biochars (AKWs-BC) derived from Trapa natans husks (TH). AKWs-BC have a well-developed microporous structure with a pore size mainly below 3 nm. Due to the doping of AKWs, the surface chemical properties of AKWs-BC (especially N functional groups) were improved. The utilization of APWs not only realizes the resource utilization of waste, but also can be used to prepare high-performance biochars.

scholarly journals CCCORE: Cloud Container for Collaborative Research

2018 ◽  
Vol 8 (3) ◽  
pp. 1659
Author(s):  
Salini Suresh ◽  
L. Manjunatha Rao
Keyword(s):  
Resource Allocation ◽  
Collaborative Research ◽  
High Performance ◽  
Research Collaboration ◽  
Resource Provisioning ◽  
Dynamic Allocation ◽  
Research Environment ◽  
Dynamic Resource Provisioning ◽  
Optimal Resource ◽  
Dynamic Resource

Cloud-based research collaboration platforms render scalable, secure and inventive environments that enabled academic and scientific researchers to share research data, applications and provide access to high- performance computing resources. Dynamic allocation of resources according to the unpredictable needs of applications used by researchers is a key challenge in collaborative research environments. We propose the design of Cloud Container based Collaborative Research (CCCORE) framework to address dynamic resource provisioning according to the variable workload of compute and data-intensive applications or analysis tools used by researchers. Our proposed approach relies on–demand, customized containerization and comprehensive assessment of resource requirements to achieve optimal resource allocation in a dynamic collaborative research environment. We propose algorithms for dynamic resource allocation problem in a collaborative research environment, which aim to minimize finish time, improve throughput and achieve optimal resource utilization by employing the underutilized residual resources.

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