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.

Slides:

Advertisements

Similar presentations

Network II.5 simulator ..

Advertisements

Communication Topics Jason Hill –

INTRODUCTION TO SIMULATION WITH OMNET++ José Daniel García Sánchez ARCOS Group – University Carlos III of Madrid.

System Design Issues In Sensor Databases Qiong Luo and Hejun Wu Department of Computer Science and Engineering The Hong Kong University of Science & Technology.

System Area Network Abhiram Shandilya 12/06/01. Overview Introduction to System Area Networks SAN Design and Examples SAN Applications.

Decentralized Reactive Clustering in Sensor Networks Yingyue Xu April 26, 2015.

FLIGHT: Clock Calibration Using Fluorescent Lighting Zhenjiang Li, Wenwei Chen, Cheng Li, Mo Li, Xiang-Yang Li, Yunhao Liu Nanyang Technological University,

Emulatore di Protocolli di Routing per reti Ad-hoc Alessandra Giovanardi DI – Università di Ferrara Pattern Project Area 3: Problematiche di instradamento.

Distributed Processing, Client/Server, and Clusters

TOSSIM A simulator for TinyOS Presented at SenSys 2003 Presented by : Bhavana Presented by : Bhavana 16 th March, 2005.

Smart-Sensor Infrastructure in the IPAC Architecture V.Tsetsos 1, V. Papataxiarhis 1, F.Kontos 1, P.Patelis 2, S.Hadjiefthymiades 1, E.Fytros 2, L.Liotti.

1 University of Freiburg Computer Networks and Telematics Prof. Christian Schindelhauer Wireless Sensor Networks 13th Lecture Christian Schindelhauer.

2008/7/3 NanoMon: An Adaptable Sensor Network Monitoring Software Misun Yu, Haeyong Kim, and Pyeongsoo Mah Embedded S/W Research Division Electronics and.

On the Energy Efficient Design of Wireless Sensor Networks Tariq M. Jadoon, PhD Department of Computer Science Lahore University of Management Sciences.

Glenn Research Center at Lewis Field Deep Space Network Emulation Shaun Endres and Behnam Malakooti Case Western Reserve University Department of Electrical.

Department of Computer Science University of Massachusetts, Amherst PRESTO: Feedback-driven Data Management in Sensor Network Ming Li, Deepak Ganesan,

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

Mobile Handset Hardware Architecture

RaPTEX: Rapid Prototyping of Embedded Communication Systems Dr. Alex Dean & Dr. Mihai Sichitiu (ECE) Dr. Tom Wolcott (MEAS) Motivation  Existing work.

Avrora Scalable Sensor Simulation with Precise Timing Ben L. Titzer UCLA CENS Seminar, February 18, 2005 IPSN 2005.

Spring 2000, 4/27/00 Power evaluation of SmartDust remote sensors CS 252 Project Presentation Robert Szewczyk Andras Ferencz.

COGNITIVE RADIO FOR NEXT-GENERATION WIRELESS NETWORKS: AN APPROACH TO OPPORTUNISTIC CHANNEL SELECTION IN IEEE BASED WIRELESS MESH Dusit Niyato,

FlockLab: A Testbed for Distributed, Synchronized Tracing and Proﬁling of Wireless Embedded Systems IPSN 2013 NSLab study group 2013/04/08 Presented by:

Qian Zhang and Christopher LIM Department of Computer Science and Engineering, Hong Kong University of Science and Technology IEEE ICC 2009.

Resource Allocation using Java RMI Amrish Kaushik Minal Malde CS599-Grid Computing Project Report USC Computer Science.

TinyOS By Morgan Leider CS 411 with Mike Rowe with Mike Rowe.

Low-Power Wireless Sensor Networks

Overview of the ORBIT Radio Grid Testbed for Evaluation of Next-Generation Wireless Network Protocols D.Raychaudhuri, M.ott, S.Ganu, K.ramachandran, H.Kremo,

Power Save Mechanisms for Multi-Hop Wireless Networks Matthew J. Miller and Nitin H. Vaidya University of Illinois at Urbana-Champaign BROADNETS October.

Design and Implementation of a Multi-Channel Multi-Interface Network Chandrakanth Chereddi Pradeep Kyasanur Nitin H. Vaidya University of Illinois at Urbana-Champaign.

AN ENERGY CONSUMPTION ANALYTIC MODEL FOR WIRELESS SENSOR MAC PROTOCOL ERIC MAKITA SEPTEMBRE

Korea Advanced Institute of Science and Technology Active Sensor Networks(Mate) (Published by Philip Levis, David Gay, and David Culler in NSDI 2005) 11/11/09.

MAC Protocols In Sensor Networks.  MAC allows multiple users to share a common channel.  Conflict-free protocols ensure successful transmission. Channel.

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology 1 Wireless Sensor Network Wireless Sensor Network Based.

System Architecture Directions for Networked Sensors Jason Hill, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, Kris Pister Presented by Yang Zhao.

Simulation of Distributed Application and Protocols using TOSSIM Valliappan Annamalai.

The IBM VM CS450/550 Section 2 Stephen Kam. IBM VM - Origins Originally an experimental OS called “CP-67” Designed to run on the IBM System/360 Model.

 Virtual machine systems: simulators for multiple copies of a machine on itself.  Virtual machine (VM): the simulated machine.  Virtual machine monitor.

1 Environment and Sensor Networks US – France Workshop Guillaume Chelius ARES Project, INRIA October, , 2007.

Efficient Energy Management Protocol for Target Tracking Sensor Networks X. Du, F. Lin Department of Computer Science North Dakota State University Fargo,

Workshop BigSim Large Parallel Machine Simulation Presented by Eric Bohm PPL Charm Workshop 2004.

Presentation by Tom Hummel OverSoC: A Framework for the Exploration of RTOS for RSoC Platforms.

KAIS T Distributed cross-layer scheduling for In-network sensor query processing PERCOM (THU) Lee Cheol-Ki Network & Security Lab.

CPE 631 Project Presentation Hussein Alzoubi and Rami Alnamneh Reconfiguration of architectural parameters to maximize performance and using software techniques.

1 RealProct: Reliable Protocol Conformance Testing with Real Nodes for Wireless Sensor Networks Junjie Xiong, Edith C.-Ngai, Yangfan Zhou, Michael R. Lyu.

Simics: A Full System Simulation Platform Synopsis by Jen Miller 19 March 2004.

Token-DCF, COMSNET(2013) -> MOBICOM(2014). Introduction ▣ To improve standard MAC protocol of IEEE for WLAN. ▣ S-MAC, A-MAC, SPEED-MAC, and etc.

Evaluating Wireless Network Performance David P. Daugherty ITEC 650 Radford University March 23, 2006.

A Dynamic Operating System for Sensor Nodes Chih-Chieh Han, Ram Kumar, Roy Shea, Eddie Kohler, Mani, Srivastava, MobiSys ‘05 Oct., 2009 발표자 : 김영선, 윤상열.

Architectures and Applications for Wireless Sensor Networks ( ) Sensor Network Programming and MoteLib Simulator Chaiporn Jaikaeo

Adaptive Sleep Scheduling for Energy-efficient Movement-predicted Wireless Communication David K. Y. Yau Purdue University Department of Computer Science.

Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.

DSN & SensorWare Projects Rockwell Science Center –Charles Chien UCLA –Mani Srivastava, Miodrag Potkonjak USC/ISI –Brian Schott, Bob Parker Virginia Tech.

UNIT IV INFRASTRUCTURE ESTABLISHMENT. INTRODUCTION When a sensor network is first activated, various tasks must be performed to establish the necessary.

1 Software Reliability in Wireless Sensor Networks (WSN) -Xiong Junjie

(1) SIMICS Overview. (2) SIMICS – A Full System Simulator Models disks, runs unaltered OSs etc. Accuracy is high (e.g., pollution effects factored in)

Younghwan Yoo† and Dharma P. Agrawal‡ † School of Computer Science and Engineering, Pusan National University, Busan, KOREA ‡ OBR Center for Distributed.

Power-Efficient Rendez- vous Schemes for Dense Wireless Sensor Networks En-Yi A. Lin, Jan M. Rabaey Berkeley Wireless Research Center University of California,

Energy Efficient Data Management in Sensor Networks Sanjay K Madria Web and Wireless Computing Lab (W2C) Department of Computer Science, Missouri University.

Building Wireless Efficient Sensor Networks with Low-Level Naming J. Heihmann, F.Silva, C. Intanagonwiwat, R.Govindan, D. Estrin, D. Ganesan Presentation.

Efficient Opportunistic Sensing using Mobile Collaborative Platform MOSDEN.

Source : 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Auther : Nacer Khalil, Mohamed.

Why does it need? [USN] ( 주 ) 한백전자 Background Wireless Sensor Network (WSN)  Relationship between Sensor and WSN Individual sensors are very limited.

Software Architecture of Sensors. Hardware - Sensor Nodes Sensing: sensor --a transducer that converts a physical, chemical, or biological parameter into.

Fermilab Scientific Computing Division Fermi National Accelerator Laboratory, Batavia, Illinois, USA. Off-the-Shelf Hardware and Software DAQ Performance.

Data Link Layer Architecture for Wireless Sensor Networks Charlie Zhong September 28, 2001.

Software and Communication Driver, for Multimedia analyzing tools on the CEVA-X Platform. June 2007 Arik Caspi Eyal Gabay.

Simulators for Sensor Networks

Communication Topics Jason Hill –

On Achieving Maximum Network Lifetime Through Optimal Placement of Cluster-heads in Wireless Sensor Networks High-Speed Networking Lab. Dept. of CSIE,

Presentation transcript:

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 The Hong Kong University of Science & Technology, China *Arcadia University, USA

Proxy Sink User Client Sensor mote Wireless Sensor Networks (WSNs)

Proxy Sink User Client Sensor mote Wireless Sensor Networks (WSN) Query

Sensor mote Proxy Sink User Client Wireless Sensor Networks (WSN) Query Result

Motivation of VMNet ► Substitute for sensor nodes in research  Easy to handle  Low price ► A realistic & controllable environment  Debugging  Testing  Evaluating Performance ► Parameter setting and validation for  Simulation  Modeling Applications Network protocols OS Drivers

VMNet architecture

Components in a VM Virtual mote Real mote binary code Virtual sensor board Virtual radio frequency module Virtual UART( In Virtual Sink) Virtual CPU EM (Emulation Manager) Virtual main board Virtual socket Virtual clock

Virtual Radio Channel Delay Module Bit error Module To VRFM Collision Module Bits From VRFM Control messages To/From Network Manager (NM) UDP packet from other VMs via LAN UDP packet to other VMs via LAN Collision signal to VRFM Queue

Key Features of VMNet ► Open architecture  Easy to transform to other WSN hardware emulation ► Detailed emulation  CPU instructions  Operations of the components ► CPU, Sensor and Radio ► Accurate running status logs  Accurate time emulation ► Granularity: microsecond level  power consumption evaluation

Open architecture design ► Conflict between generality & accuracy  Generality is desirable ► Ability to emulate various WSNs  Accuracy ► Close to the specified target WSN ► Highly modularized structure of a VM  Ensures the reusability ► Virtual socket in a VM  Uniform interface between modules

Virtual mote Real mote binary code Virtual sensor board Virtual radio frequency module Virtual UART( In Virtual Sink) Virtual CPU EM (Emulation Manager) Virtual main board Virtual socket Virtual clock Highly modularized structure

Performance Evaluation on Applications of WSNs ► Based on the fact that  Operation and time can be deduced by ► Instructions executed by the CPU in a sensor mote ► An instruction always takes constant time ► VMNet approach in performance evaluation  Logging and reporting ► Operations and time

Logging in VMNet ► The operations : ► VMNet logs  Running states ► the operations of each component (e.g. III)  CPU clocks ► describe the start time and end time CPUSensorRadio Compute (C) Compute (C) Acquire (A) Transmit (T) Idle (I) Receive(R) Hibernate (H) Power down (P) Control(C) Idle(I) Power down (p) Running states Time (In terms of CPU clock cycles) III IIR CIR The operations of components A fraction of a VMNet log

Conclusion ► Detailed emulation  Useful for many areas in a WSN ► Architecture, OS, and sensor network query processing.  Provides ► parameter and validation for simulation & modeling ► Performance evaluation  Especially valuable for query processing ► Query Optimization:  choose a query plan with minimum energy and time cost ► Query processor benchmark study

Future Work ► Power consumption evaluation ► Work in progress  Scalability  Mobile WSN emulation  Graphical Interface for VMNet ► In the near future  Use multiple PCs to emulate a WSN