Synchronous communication of molecular and electronic structure information in a distributed computing environment

1999 ◽  
pp. 11-16
Author(s):  
Peter F. Flükiger ◽  
Stefan Portmann ◽  
Peter Lüthi
Keyword(s):  
Electronic Structure ◽  
Distributed Computing ◽  
Synchronous Communication ◽  
Computing Environment ◽  
Structure Information ◽  
Molecular And Electronic Structure

scholarly journals IoT-enabled directed acyclic graph in spark cluster

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Jahwan Koo ◽  
Nawab Muhammad Faseeh Qureshi ◽  
Isma Farah Siddiqui ◽  
Asad Abbas ◽  
Ali Kashif Bashir
Keyword(s):  
Distributed Computing ◽  
Real Time ◽  
Directed Acyclic Graph ◽  
Random Access ◽  
Heterogeneous Data ◽  
The Body ◽  
Computing Environment ◽  
Time Data ◽  
Acyclic Graph ◽  
Sensory Data

Abstract Real-time data streaming fetches live sensory segments of the dataset in the heterogeneous distributed computing environment. This process assembles data chunks at a rapid encapsulation rate through a streaming technique that bundles sensor segments into multiple micro-batches and extracts into a repository, respectively. Recently, the acquisition process is enhanced with an additional feature of exchanging IoT devices’ dataset comprised of two components: (i) sensory data and (ii) metadata. The body of sensory data includes record information, and the metadata part consists of logs, heterogeneous events, and routing path tables to transmit micro-batch streams into the repository. Real-time acquisition procedure uses the Directed Acyclic Graph (DAG) to extract live query outcomes from in-place micro-batches through MapReduce stages and returns a result set. However, few bottlenecks affect the performance during the execution process, such as (i) homogeneous micro-batches formation only, (ii) complexity of dataset diversification, (iii) heterogeneous data tuples processing, and (iv) linear DAG workflow only. As a result, it produces huge processing latency and the additional cost of extracting event-enabled IoT datasets. Thus, the Spark cluster that processes Resilient Distributed Dataset (RDD) in a fast-pace using Random access memory (RAM) defies expected robustness in processing IoT streams in the distributed computing environment. This paper presents an IoT-enabled Directed Acyclic Graph (I-DAG) technique that labels micro-batches at the stage of building a stream event and arranges stream elements with event labels. In the next step, heterogeneous stream events are processed through the I-DAG workflow, which has non-linear DAG operation for extracting queries’ results in a Spark cluster. The performance evaluation shows that I-DAG resolves homogeneous IoT-enabled stream event issues and provides an effective stream event heterogeneous solution for IoT-enabled datasets in spark clusters.

Synthesis of uranium complexes incorporating extended azo-imine ligands: Molecular and electronic structure

2021 ◽  
pp. 100049
Author(s):  
Poulami Pattanayak ◽  
Sankar Prasad Parua ◽  
Debprasad Patra ◽  
Ashoke Prasun Chattopadhyay ◽  
Surajit Chattopadhyay
Keyword(s):  
Electronic Structure ◽  
Uranium Complexes ◽  
Imine Ligands ◽  
Molecular And Electronic Structure

Designing a distributed computing environment for global-scale systems

1999 ◽  
Vol 7 (1) ◽  
pp. 25-30 ◽  
Author(s):  
Rajeev R. Raje ◽  
Sivakumar Chinnasamy
Keyword(s):  
Distributed Computing ◽  
Global Scale ◽  
Computing Environment

scholarly journals Molecular and Electronic Structure of Dinuclear Uranium Bis-μ-Oxo Complexes with Diamond Core Structural Motifs

2014 ◽  
Vol 136 (34) ◽  
pp. 11980-11993 ◽  
Author(s):  
Anna-Corina Schmidt ◽  
Frank W. Heinemann ◽  
Wayne W. Lukens ◽  
Karsten Meyer
Keyword(s):  
Electronic Structure ◽  
Structural Motifs ◽  
Oxo Complexes ◽  
Molecular And Electronic Structure
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