Call for Papers for IEEE Transactions on Parallel and Distributed Systems (TPDS) Special Issue on Cloud Computing

2011 ◽  
Vol 22 (12) ◽  
pp. 2126-2127
Keyword(s):  
Cloud Computing ◽  
Distributed Systems ◽  
Special Issue

THE LANDSCAPE OF INCONSISTENCY: A PERSPECTIVE

2011 ◽  
Vol 05 (03) ◽  
pp. 235-256 ◽  
Author(s):  
DU ZHANG ◽  
ÉRIC GRÉGOIRE
Keyword(s):  
Cloud Computing ◽  
Social Computing ◽  
Special Issue ◽  
Computing Systems ◽  
Semantic Computing

The focus of this introduction to this special issue is to draw a picture as comprehensive as possible about various dimensions of inconsistency. In particular, we consider: (1) levels of knowledge at which inconsistency occurs; (2) categories and morphologies of inconsistency; (3) causes of inconsistency; (4) circumstances of inconsistency; (5) persistency of inconsistency; (6) consequences of inconsistency; (7) metrics for inconsistency; (8) theories for handling inconsistency; (9) dependencies among occurrences of inconsistency; and (10) problem domains where inconsistency has been studied. The take-home message is that inconsistency is ubiquitous and handling inconsistency is consequential in our endeavors. How to manage and reason in the presence of inconsistency presents a very important issue in semantic computing, cloud computing, social computing, and many other data-rich or knowledge-rich computing systems.

Guest Editors' Introduction: Special Issue on Cloud Computing

2013 ◽  
Vol 24 (6) ◽  
pp. 1062-1065 ◽  
Author(s):  
Vojislav B. Misic ◽  
Rajkumar Buyya ◽  
Dejan Milojicic ◽  
Yong Cui
Keyword(s):  
Cloud Computing ◽  
Special Issue

Adaptive Threshold Based Scheduler for Batch of Independent Jobs for Cloud Computing System

2021 ◽  
pp. 2246-2266
Author(s):  
TAJ ALAM ◽  
PARITOSH DUBEY ◽  
ANKIT KUMAR
Keyword(s):  
Cloud Computing ◽  
Distributed Systems ◽  
High Performance ◽  
Large Scale ◽  
Real Life ◽  
Interval Estimation ◽  
Computing System ◽  
Adaptive Threshold ◽  
Batch Simulation ◽  
Heterogeneous Distributed Systems

Distributed systems are efficient means of realizing high-performance computing (HPC). They are used in meeting the demand of executing large-scale high-performance computational jobs. Scheduling the tasks on such computational resources is one of the prime concerns in the heterogeneous distributed systems. Scheduling jobs on distributed systems are NP-complete in nature. Scheduling requires either heuristic or metaheuristic approach for sub-optimal but acceptable solutions. An adaptive threshold-based scheduler is one such heuristic approach. This work proposes adaptive threshold-based scheduler for batch of independent jobs (ATSBIJ) with the objective of optimizing the makespan of the jobs submitted for execution on cloud computing systems. ATSBIJ exploits the features of interval estimation for calculating the threshold values for generation of efficient schedule of the batch. Simulation studies on CloudSim ensures that the ATSBIJ approach works effectively for real life scenario.

scholarly journals Special issue on big data for IoT cloud computing convergence

2019 ◽  
Vol 17 (2) ◽  
pp. 101-103
Author(s):  
Z.X. Hou ◽  
Y. Xiao
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Special Issue

Introduction to the special issue on Cloud Computing: Recent Developments and Challenging Issues

2015 ◽  
Vol 42 ◽  
pp. 31-32
Author(s):  
Danielo G. Gomes ◽  
Rodrigo N. Calheiros ◽  
Rafael Tolosana-Calasanz
Keyword(s):  
Cloud Computing ◽  
Special Issue ◽  
Recent Developments
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