Optimal bounds on the gain of permitting dynamic allocation of communication channels in distributed computing

1999 ◽  
Vol 36 (6) ◽  
pp. 425-446 ◽  
Author(s):  
Lars Lundberg ◽  
Håkan Lennerstad
Keyword(s):  
Distributed Computing ◽  
Communication Channels ◽  
Dynamic Allocation ◽  
Optimal Bounds

Dynamic allocation strategy based on pre-allocation and agent to implement Ada95's distributed computing

2003 ◽  
Vol 8 (4) ◽  
pp. 1061-1064
Author(s):  
Zhu Fu-xi ◽  
Fu Jian-ming ◽  
Wu Chan-le ◽  
Cao Zheng
Keyword(s):  
Distributed Computing ◽  
Dynamic Allocation ◽  
Allocation Strategy

Accounting and Charging

2011 ◽  
pp. 302-336
Author(s):  
Burkhard Stiller ◽  
David Hausheer ◽  
Jan Gerke ◽  
Peter Racz ◽  
Cristian Morariu ◽  
...  
Keyword(s):  
Distributed Computing ◽  
Ubiquitous Computing ◽  
Service Providers ◽  
Communication Channels ◽  
Value Added ◽  
Clear View ◽  
Network Transport ◽  
Area Of Interest ◽  
Contractual Relationships ◽  
Computing Approach

Charging for IP-based communications determines the overall term for metering or monitoring, accounting, pricing, charge calculation, and billing. These five actions are detailed in this chapter to provide a clear view on their interdependencies as well as their relations to distributed computing. Since an ubiquitous computing approach does require communication means between all entities involved, the provisioning of these communication channels is supported typically by commercial service providers— covering network, transport, and value-added services. Thus, the legal and contractual relationships between customers and providers as well as technological choices of protocols, mechanisms, and parameters define the area of interest here.

Abstract #1103: Comprehensive Diabetes Care Through Continuous Communication Channels to Patients with Diabetes

2017 ◽  
Vol 23 ◽  
pp. 290
Author(s):  
Vamsi Kolukula ◽  
Jayashree Gopal ◽  
Shantharam Duvuru ◽  
Kalpana Dash ◽  
Sanjiv Shah ◽  
...  
Keyword(s):  
Diabetes Care ◽  
Communication Channels ◽  
Patients With Diabetes

Power Consumption Evaluation of Distributed Computing Network Considering Traffic Locality

2012 ◽  
Vol E95.B (8) ◽  
pp. 2538-2548
Author(s):  
Yukio OGAWA ◽  
Go HASEGAWA ◽  
Masayuki MURATA
Keyword(s):  
Distributed Computing ◽  
Power Consumption

Matlab and Parallel Computing

2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Control Systems ◽  
High Performance ◽  
Parallel Applications ◽  
Process Simulations ◽  
Key Features ◽  
Financial Process

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.

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