Presented by Ramy Shahin March 12th 2018

Slides:



Advertisements
Similar presentations
The Who, What, Why and How of High Performance Computing Applications in the Cloud Soheila Abrishami 1.
Advertisements

Green Cloud Computing Hadi Salimi Distributed Systems Lab, School of Computer Engineering, Iran University of Science and Technology,
Efficient Autoscaling in the Cloud using Predictive Models for Workload Forecasting Roy, N., A. Dubey, and A. Gokhale 4th IEEE International Conference.
Automatic Resource Scaling for Web Applications in the Cloud Ching-Chi Lin Institute of Information Science, Academia Sinica Department of Computer Science.
COMMA: Coordinating the Migration of Multi-tier applications 1 Jie Zheng* T.S Eugene Ng* Kunwadee Sripanidkulchai† Zhaolei Liu* *Rice University, USA †NECTEC,
SLA-aware Virtual Resource Management for Cloud Infrastructures
COMS E Cloud Computing and Data Center Networking Sambit Sahu
U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science Virtualization in Data Centers Prashant Shenoy
1 Characterizing Selfishly Constructed Overlay Routing Networks March 11, 2004 Byung-Gon Chun, Rodrigo Fonseca, Ion Stoica, and John Kubiatowicz University.
Architecture and Real Time Systems Lab University of Massachusetts, Amherst I Koren and C M Krishna Electrical and Computer Engineering University of Massachusetts.
Telco Clouds: Modelling and Simulation
Jordan University of Science and Technology
Energy-aware Hierarchical Scheduling of Applications in Large Scale Data Centers Gaojin Wen, Jue Hong, Chengzhong Xu et al. Center for Cloud Computing,
Simulation of Cloud Environments
Virtual Machine Hosting for Networked Clusters: Building the Foundations for “Autonomic” Orchestration Based on paper by Laura Grit, David Irwin, Aydan.
Chapter 8 Architecture Analysis. 8 – Architecture Analysis 8.1 Analysis Techniques 8.2 Quantitative Analysis  Performance Views  Performance.
1 Enabling Large Scale Network Simulation with 100 Million Nodes using Grid Infrastructure Hiroyuki Ohsaki Graduate School of Information Sci. & Tech.
UI and Data Entry UI and Data Entry Front-End Business Logic Mid-Tier Data Store Back-End.
Software-defined Networking Capabilities, Needs in GENI for VMLab ( Prasad Calyam; Sudharsan Rajagopalan;
CloudNaaS: A Cloud Networking Platform for Enterprise Applications Theophilus Benson*, Aditya Akella*, Anees Shaikh +, Sambit Sahu + (*University of Wisconsin,
Vic Liu Liang Xia Zu Qiang Speaker: Vic Liu China Mobile Network as a Service Architecture draft-liu-nvo3-naas-arch-01.
Net-Centric Software and Systems I/UCRC A Framework for QoS and Power Management for Mobile Devices in Service Clouds Project Lead: I-Ling Yen, Farokh.
Modeling and Simulation of Cloud Computing:A Review Wei Zhao, Yong Peng, Feng Xie, Zhonghua Dai 報告者 : 饒展榕.
Copyright © 2011, A New MMOG Framework On Cloud Computing Environment 張晏誌 1.
ISC 2011 Flying through the Clouds Flying through the Clouds.
Overview and Comparison of Software Tools for Power Management in Data Centers Msc. Enida Sheme Acad. Neki Frasheri Polytechnic University of Tirana Albania.
Cloudsim: simulator for cloud computing infrastructure and modeling Presented By: SHILPA V PIUS 1.
Universidade Federal do Ceará FOLE: A Framework for Elasticity Performance Evaluation in Cloud Computing Systems Emanuel F. Coutinho Group of Computer.
Www3.informatik.uni-wuerzburg.de Institute of Computer Science Chair of Communication Networks Prof. Dr.-Ing. P. Tran-Gia Simulation Framework for Live.
Usage Of Cloud Computing Simulators And Future Systems In Computational Research Dr. Ramkumar Lakshminarayanan Mr. Rajasekar Ramalingam.
United States Army Combined Arms Center A next generation simulation architecture supporting both Computer Generated Forces (CGF) and SAF operations Provides.
A Hierarchical Edge Cloud Architecture for Mobile Computing IEEE INFOCOM 2016 Liang Tong, Yong Li and Wei Gao University of Tennessee – Knoxville 1.
Parallel programs Inf-2202 Concurrent and Data-intensive Programming Fall 2016 Lars Ailo Bongo
Md Baitul Al Sadi, Isaac J. Cushman, Lei Chen, Rami J. Haddad
LIGHTWEIGHT CLOUD COMPUTING FOR FAULT-TOLERANT DATA STORAGE MANAGEMENT
CIS 700-5: The Design and Implementation of Cloud Networks
LIGHTWEIGHT CLOUD COMPUTING FOR FAULT-TOLERANT DATA STORAGE MANAGEMENT
BEST CLOUD COMPUTING PLATFORM Skype : mukesh.k.bansal.
Reinforcement Learning Based Virtual Cluster Management
Network Simulators.
LIGHTWEIGHT CLOUD COMPUTING FOR FAULT-TOLERANT DATA STORAGE MANAGEMENT
Cloud-Assisted VR.
Introduction | Model | Solution | Evaluation
Resource Elasticity for Large-Scale Machine Learning
EDGE WP5 Communication Infrastructure - Status February
Cloud-Assisted VR.
Adaptive Cloud Computing Based Services for Mobile Users
3b 4b 1c 5a 5b 5a 2 3a 4c 3c TASK 1 - IMPROVE TEB GAME
Aled Edwards, Anna Fischer, Antonio Lain HP Labs
Collaborative Offloading for Distributed Mobile-Cloud Apps
Cloud Computing Dr. Sharad Saxena.
The Extensible Tool-chain for Evaluation of Architectural Models
Speaker: I-LUN LEE ADVISOR: DR. HO-TING WU
Object-Oriented Analysis
Moab® Automation Intelligence Overview
Concept of VLAN (Virtual LAN) and Benefits
Unified Modeling Language
Continous-Action Q-Learning
ElasticTree: Saving Energy in Data Center Networks
Topological Ordering Algorithm: Example
Cloud computing mechanisms
Chapter 0 : Introduction to Object Oriented Design
Resource and Service Management on the Grid
Topological Ordering Algorithm: Example
Topological Ordering Algorithm: Example
1. INTRODUCTION.
WP3: BPaaS Research Execution Environment
Progress Report 2017/02/08.
Topological Ordering Algorithm: Example
Title: Robust ONAP Platform Controller for LCM in a Distributed Edge Environment (In Progress) Source: ONAP Architecture Task Force on Edge Automation.
Presentation transcript:

Presented by Ramy Shahin March 12th 2018 CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms Calheiros et al. - Softw. Pract. Exper. 2011 Presented by Ramy Shahin March 12th 2018

Cloud Computing

Cloud Federation

CloudSim Simulation Scenarios Resource Management Simulation Discrete Event Simulation

CloudSim Different aspects are modeled and simulated: VM allocation The cloud market Network behavior Federations of clouds Dynamic workloads Data center power consumption Dynamic entity creation

Provisioning Policies Space-shared for VMs Space-shared for tasks Space-shared for VMs Time-shared for tasks Time-shared for VMs Space-shared for tasks Time-shared for VMs Time-shared for tasks Each of vm1 and vm2 require 2 cores: - t1, t2, t3, t4 run on vm1 - t5, t6, t7, t8 run on vm2

Network Communication Flow Network topology description in BRITE format Latency matrix generated per scenario

Overhead Evaluation

Federation Case Study Workload migration scenario 25 VMs with 1 cloudlet each

Discussion Modeling and Simulation: What would make a modeling notation/environment more suitable for simulation? Domain-Specific Modeling: Taking CloudSim as an example, how much of such a system can be built on top of a general-purpose modeling system? What pieces would require a DSL? Model/Simulator modularity and interoperability: network topology simulator, cloud simulator, provisioning simulator, federation simulator, etc…