Sensor Network Simulation Simulators and Testbeds Jaehoon Kim Jeeyoung Kim Sungwook Moon.

Slides:



Advertisements
Similar presentations
KANSEI TESTBED OHIO STATE UNIVERSITY. HETEREGENOUS TESTBED Multiple communication networks, computation platforms, multi-modal sensors/actuators, and.
Advertisements

Sensor Network Platforms and Tools
Overview: Chapter 7  Sensor node platforms must contend with many issues  Energy consumption  Sensing environment  Networking  Real-time constraints.
Presented by: Thabet Kacem Spring Outline Contributions Introduction Proposed Approach Related Work Reconception of ADLs XTEAM Tool Chain Discussion.
Network Innovation using OpenFlow: A Survey
TOSSIM A simulator for TinyOS Presented at SenSys 2003 Presented by : Bhavana Presented by : Bhavana 16 th March, 2005.
Accurate Emulation of Wireless Sensor Networks Hejun Wu Joint work with Qiong Luo, Pei Zheng*, Bingsheng He, and Lionel M. Ni Department of Computer Science.
Generic Sensor Platform for Networked Sensors Haywood Ho.
SUPERB-IT Center for Hybrid and Embedded Software Systems COLLEGE OF ENGINEERING, UC BERKELEY August 4, 2006 SUPERB-IT.
Generic Sensor Platform for Networked Sensors Haywood Ho.
TinyOS Software Engineering Sensor Networks for the Masses.
1 Ultra-Low Duty Cycle MAC with Scheduled Channel Polling Wei Ye Fabio Silva John Heidemann Presented by: Ronak Bhuta Date: 4 th December 2007.
WSN Simulation Template for OMNeT++
Comparing Models of Computation for Real-time, Distributed Control Systems Shawn Schaffert Bruno Sinopoli.
Application Architectures Vijayan Sugumaran Department of DIS Oakland University.
TOSSIM: Visualizing the Real World Philip Levis, Nelson Lee, Dennis Chi and David Culler UC Berkeley NEST Retreat, January 2003.
WISENET Wireless Sensor Network Project Team: J. Dunne D. Patnode Advisors: Dr. Malinowski Dr. Schertz.
THE SECOND LIFE OF A SENSOR: INTEGRATING REAL-WORLD EXPERIENCE IN VIRTUAL WORLDS USING MOBILE PHONES Sherrin George & Reena Rajan.
報告日期 :2012/03/07 指導教授 : 蔡亮宙 報 告 者 : 吳烱華 自製率 :100%.
The Platforms enabling Wireless Sensor Networks Hill, Horton, Kling, Krishnamurthy CACM, June 2004.
Avrora Scalable Sensor Simulation with Precise Timing Ben L. Titzer UCLA CENS Seminar, February 18, 2005 IPSN 2005.
A Secure Protocol for Spontaneous Wireless Ad Hoc Networks Creation.
MICA: A Wireless Platform for Deeply Embedded Networks
Overview of SQL Server Alka Arora.
Introduction Chapter 1 S. Dandamudi To be used with S. Dandamudi, “Introduction to Assembly Language Programming,” Second Edition, Springer, 2005.
Summary Device protocols tied intimately to applications. A need to significantly reduce critical data update times. Current network bandwidth consumption.
DESIGN & IMPLEMENTATION OF SMALL SCALE WIRELESS SENSOR NETWORK
Event Metadata Records as a Testbed for Scalable Data Mining David Malon, Peter van Gemmeren (Argonne National Laboratory) At a data rate of 200 hertz,
COMP 410 & Sky.NET May 2 nd, What is COMP 410? Forming an independent company The customer The planning Learning teamwork.
Database Design - Lecture 2
Low-Power Wireless Sensor Networks
Building Mobile Augmented Reality Services in Pervasive Computing Environment Hiroaki Kimura Eiji Tokunaga
This is an overview of sophisticated configuration tools for online selling processes of network solutions. The tools address a very wide range of design.
1 A System for Simulation, Emulation, and Deployment of Heterogeneous Wireless Sensor Networks Lewis Girod, Thanos Stathopoulos, Nithya Ramanathan, Jeremy.
1 XYZ: A Motion-Enabled, Power Aware Sensor Node Platform for Distributed Sensor Network Applications Presenter: James D. Lymberopoulos, A. Savvides.
AirPatrol’s ZoneDefense for Corrections Complete 24/7 precision monitoring and detection of all mobile devices.
TRICKLE: A Self-Regulating Algorithm for Code Propagation and Maintenance in Wireless Sensor Networks Philip Levis, Neil Patel, Scott Shenker and David.
© 2012 xtUML.org Bill Chown – Mentor Graphics Model Driven Engineering.
Content Sharing over Smartphone-Based Delay- Tolerant Networks.
Simulation of Distributed Application and Protocols using TOSSIM Valliappan Annamalai.
Introduction Chapter 1 S. Dandamudi. Outline A user’s view of computer systems What is assembly language? – Relationship to machine language Advantages.
/42 Does Wireless Sensor Network Scale? A Measure Study on GreenOrbs Yunhao Liu, Yuan He, Mo Li, Jiliang Wang,Kebin Liu, Lufeng Mo, Wei Dong,
Introduction Advantages/ disadvantages Code examples Speed Summary Running on the AOD Analysis Platforms 1/11/2007 Andrew Mehta.
Issues Autonomic operation (fault tolerance) Minimize interference to applications Hardware support for new operating systems Resource management (global.
Model Checking and Model-Based Design Bruce H. Krogh Carnegie Mellon University.
Theia Technical Design Presentation 3. Theia Overview Theia’s purpose is to create three dimensional, virtual representations of a room. To allow the.
Simics: A Full System Simulation Platform Synopsis by Jen Miller 19 March 2004.
Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 1 Based upon slides from Jay Lepreau, Utah Emulab Introduction Shiv Kalyanaraman
Xiong Junjie Node-level debugging based on finite state machine in wireless sensor networks.
1 Copyright  2001 Pao-Ann Hsiung SW HW Module Outline l Introduction l Unified HW/SW Representations l HW/SW Partitioning Techniques l Integrated HW/SW.
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
Accurate Prediction of Power Consumption in Sensor Networks University of Tubingen, Germany In EmNetS 2005 Presented by Han.
Architecture & Cybersecurity – Module 3 ELO-100Identify the features of virtualization. (Figure 3) ELO-060Identify the different components of a cloud.
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
27-Apr-06 JAWS Deployment-Support Network Principle – Status – Current Work Jan Beutel Computer Engineering and Networks Lab, ETH Zurich.
DSN & SensorWare Projects Rockwell Science Center –Charles Chien UCLA –Mani Srivastava, Miodrag Potkonjak USC/ISI –Brian Schott, Bob Parker Virginia Tech.
1 Software Reliability in Wireless Sensor Networks (WSN) -Xiong Junjie
Lesson 1 1 LESSON 1 l Background information l Introduction to Java Introduction and a Taste of Java.
Mobile Application Testing Mobile Application Testing.
Introduction to Wireless Sensor Networks
From Use Cases to Implementation 1. Structural and Behavioral Aspects of Collaborations  Two aspects of Collaborations Structural – specifies the static.
Border Security Using Wireless Integrated Network Sensors
From Use Cases to Implementation 1. Mapping Requirements Directly to Design and Code  For many, if not most, of our requirements it is relatively easy.
Structured parallel programming on multi-core wireless sensor networks Nicoletta Triolo, Francesco Baldini, Susanna Pelagatti, Stefano Chessa University.
Goals: Provide a Full Range of Development Environments for Testing Goals: Provide a Full Range of Development Environments for Testing EmTOS: Bringing.
INTRODUCTION TO WIRELESS SENSOR NETWORKS
Software testing
WISENET Wireless Sensor Network
Sensor Networks – Motes, Smart Spaces, and Beyond
Task Manager & Profile Interface
Presentation transcript:

Sensor Network Simulation Simulators and Testbeds Jaehoon Kim Jeeyoung Kim Sungwook Moon

Contents 1.Introduction 2.Simulators 1.TOSSIM 2.Avrora 3.Viptos 3.Testbeds 1.MoteLab 2.Kansei 4.Conclusion

Introduction  What is a network simulator?  Why a sensor network simulator?  What is a testbed?  Simulators vs Testbeds?

Simulators 1.TOSSIM 2.Avrora 3.Viptos

TOSSIM  Overview. A TinyOS based interrupt-level discrete event simulator Can capture network behavior at a high fidelity while scaling to thousands of nodes (up to 8192 nodes) Helped to discover bugs in TinyOS Provides a high degree of accuracy by using models of only a few low-level components with or without a few modification of source code

TOSSIM  Disadvantages Only compatible with TinyOS No preemption Does not capture CPU time (cycle count) But it would limit scalability. Does not capture energy consumption. It requires adding hooks to the simulator implementations of hardware abstraction components

Avrora  Overview A cycle-accurate instruction level sensor network simulator which scales to networks of up to 10,000 nodes Uses a cycle-by-cycle implementation strategy where each node and each device are advanced by one clock cycle every round Performs as much as 20 times faster than its previous simulator(ATEMU) Only 50% slower than TOSSIM

Avrora  Disadvantages Did not model clock drift In reality, nodes may run at slightly different clock frequencies over time due to manufacturing tolerances, temperature, and battery reason. Validating timing results with real-world systems for all devices remains as future work Only verified timing results for large programs with radio communication and real hardware for small, simple programs.

Viptos  Overview Graphical development and simulation environment for TinyOS-based wireless sensor networks Transforms the diagram into a nesC program Extends the capabilities of TOSSIM to allow simulation of heterogeneous networks Allows application developers to easily transition between high-level simulation of algorithms to low-level implementation and simulation

Testbeds 1.MoteLab 2.Kansei

MoteLab  Overview Web-based sensor network testbed Set of permanently deployed nodes Web interface for users Direct interaction with individual nodes

MoteLab  Details Set of software tools Four main pieces MySQL Database Backend Web Interface DBLogger Job Daemon Use Models Batch Use Real-time Access

Kansei  Overview Networked sensing applications at scale Couple general set of arrays Readily add new platforms Addressing the scaling challenge Enables scaling via software in a high fidelity manner

Kansei  Details Set of hardware platforms Hardware infrastructure Stationary array Portable array Mobile array Director High fidelity sensor data generation tools Hybrid simulation

Conclusion  TOSSIM has good performance but with limited usability  Avrora has slightly improved fidelity but has a 50% slower performance rate (than TOSSIM)  Viptos enables a graphical representation of the simulation on top of TOSSIM  They are different but none are superior or inferior to the other

Conclusion (cont’d)  MoteLab provides a web-based interface  Kansei has better scalability  Both provide networked testbeds with shared access for users

Any questions?