Environmentally Opportunistic Computing

2013 ◽  
pp. 347-362
Keyword(s):  
Opportunistic Computing

scholarly journals The EPOC Project - Energy Proportional and Opportunistic Computing System

2015 ◽  
Author(s):  
Nicolas Beldiceanu ◽  
Barbara Dumas Feris ◽  
Philippe Gravey ◽  
Sabbir Hasan ◽  
Claude Jard ◽  
...  
Keyword(s):  
Computing System ◽  
Opportunistic Computing

Social Opportunistic Computing: Design for Autonomic User-Centric Systems

2009 ◽  
pp. 211-229 ◽  
Author(s):  
Iacopo Carreras ◽  
David Tacconi ◽  
Arianna Bassoli
Keyword(s):  
Opportunistic Computing ◽  
User Centric

scholarly journals HEP Analyses on Dynamically Allocated Opportunistic Computing Resources

2020 ◽  
Vol 1525 ◽  
pp. 012067
Author(s):  
M J Schnepf ◽  
R F von Cube ◽  
C Heidecker ◽  
M Fischer ◽  
M Giffels ◽  
...  
Keyword(s):  
Opportunistic Computing

scholarly journals Service Provisioning through Opportunistic Computing in Mobile Clouds

2014 ◽  
Vol 40 ◽  
pp. 143-150 ◽  
Author(s):  
Davide Mascitti ◽  
Marco Conti ◽  
Andrea Passarella ◽  
Laura Ricci
Keyword(s):  
Service Provisioning ◽  
Opportunistic Computing

scholarly journals Dynamic integration of distributed, Cloud-based HPC and HTC resources using JSON Web Tokens and the INDIGO IAM Service

2020 ◽  
Vol 245 ◽  
pp. 07020
Author(s):  
Danele Spiga ◽  
Stefano Dal Pra ◽  
Davide Salomoni ◽  
Andrea Ceccanti ◽  
Roberto Alfieri
Keyword(s):  
Enabling Technology ◽  
On Demand ◽  
The Past ◽  
Batch Systems ◽  
Batch System ◽  
Opportunistic Computing ◽  
User Communities ◽  
Increasing Demand ◽  
Cloud Infrastructures ◽  
Distributed Cloud

In the past couple of years, we have been actively developing the Dynamic On-Demand Analysis Service (DODAS) as an enabling technology to deploy container-based clusters over hybrid, private or public, Cloud infrastructures with almost zero effort. DODAS is particularly suitable for harvesting opportunistic computing resources; this is why several scientific communities already integrated their computing use cases into DODAS-instantiated clusters, automating the instantiation, management and federation of HTCondor batch systems. The increasing demand, availability and utilization of HPC resources by and for multidisciplinary user communities, often mandates the possibility to transparently integrate, manage and mix HTC and HPC resources. In this paper, we discuss our experience extending and using DODAS to connect HPC and HTC resources in the context of a distributed Italian regional infrastructure involving multiple sites and communities. In this use case, DODAS automatically generates HTCondor batch system on-demand. Moreover it dynamically and transparently federates sites that may also include HPC resources managed by SLURM; DODAS allows user workloads to make opportunistic and automated use of both HPC and HTC resources, thus effectively maximizing and optimizing resource utilization. We also report on our experience of using and federating HTCondor batch systems exploiting the JSON Web Token capabilities introduced in recent HTCondor versions, replacing the traditional X509 certificates in the whole chain of workload authorization. In this respect we also report on how we integrated HTCondor using OAuth with the INDIGO IAM service.

Context-aware opportunistic computing in vehicle-to-vehicle networks

2020 ◽  
Vol 24 ◽  
pp. 100236 ◽  
Author(s):  
Anis Ur Rahman ◽  
Asad Waqar Malik ◽  
Vishwani Sati ◽  
Arpita Chopra ◽  
Sri Devi Ravana
Keyword(s):  
Context Aware ◽  
Vehicle To Vehicle ◽  
Opportunistic Computing ◽  
Vehicle Networks
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