後卓越進度報告蔡育仁老師實驗室 2006/07/10. Non-uniform Deployment for Lifetime-based Sensor Networks Propose a non-uniform density for random deployment based on the.

Slides:

Advertisements

Similar presentations

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

Advertisements

CLUSTERING IN WIRELESS SENSOR NETWORKS B Y K ALYAN S ASIDHAR.

An Energy Efficient Routing Protocol for Cluster-Based Wireless Sensor Networks Using Ant Colony Optimization Ali-Asghar Salehpour, Babak Mirmobin, Ali.

General Description Coverage-Preserving Routing Protocol for WSNs Distributed, power-balanced multihop routing protocol Coverage-preserving based route-

Tufts Wireless Laboratory Tufts University School Of Engineering Energy-Efficient Structuralized Clustering for Sensor-based Cyber Physical Systems Jierui.

Improvement on LEACH Protocol of Wireless Sensor Network

Low-Energy Adaptive Clustering Hierarchy An Energy-Efficient Communication Protocol for Wireless Micro-sensor Networks M. Aslam hayat.

Kai Li, Kien Hua Department of Computer Science University of Central Florida.

A novel Energy-Efficient and Distance- based Clustering approach for Wireless Sensor Networks M. Mehdi Afsar, Mohammad-H. Tayarani-N.

By Areeba Rao with Dr. Nadeem Javaid COMSATS, Institute of Information Technology, Islamabad, Pakistan AM-DisCNT: Angular Multi-hop DIStance based Circular.

後卓越進度報告蔡育仁老師實驗室 2006/06/05. Step-by-Step Deployment of Location Sensors by Cramér-Rao Lower Bound Cramér-Rao Lower Bound (CRLB) is a lower bound of the.

後卓越進度報告蔡育仁老師實驗室 2007/03/19. Distribute Source Coding (DSC) in WSNs Distributed source coding is a data compression technique to reduce the redundancy.

1 後卓越計畫進度報告曾煜棋老師實驗室. 2 Problem Statement Event-driven Sensor Networks Exploiting the spatial correlation of sensor data Designing a specific MAC protocol.

後卓越進度報告蔡育仁老師實驗室 2006/12/06. Distribute Source Coding (DSC) in WSNs Distributed source coding (DSC) is a data compression technique to reduce the redundancy.

1 後卓越計畫進度報告曾煜棋老師實驗室. 2 A Link-layer Protocol for Event-driven WSNs Joint two subissues Exploiting the spatial correlation of sensor data Designing a.

LLR-based Distributed Detection for Wireless Sensor Networks 後卓越進度報告蔡育仁老師實驗室 2008/01/07.

1/7/ 後卓越計畫進度報告 Broadband System Laboratory Advisor : Prof. Chin-Liang Wang Presented by Tran Duc Thang A NEW TECHNIQUE FOR LOCALIZATION IN WIRELESS.

1 後卓越計畫進度報告楊舜仁老師實驗室 Objective Investigate the bandwidth management mechanisms for IEEE j networks. The goal of bandwidth management.

後卓越進度報告蔡育仁老師實驗室 2006/11/13. Distribute Source Coding (DSC) in WSNs Distributed source coding (DSC) is a data compression technique to reduce the redundancy.

Slide 1 後卓越計畫進度報告楊舜仁老師實驗室 Slide 2 Motivation l An MBMS source entity shall provide multiple classes of service quality for a single MBMS.

後卓越進度報告蔡育仁老師實驗室 2007/08/13. DSC with Slotted ALOHA in Clustered WSN We analyze further the clustered WSNs applying  Compression: DSC (sequential encoding/decoding)

IEEE TSMCA 2005 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS Presented by 황재호.

後卓越計畫進度報告楊舜仁老師實驗室 Overlapping RA Scheme Reduce the RAU cost caused by the ping-pong effect In overlapping RA scheme, one cell may belong.

Layered Diffusion based Coverage Control in Wireless Sensor Networks Wang, Bang; Fu, Cheng; Lim, Hock Beng; Local Computer Networks, LCN nd.

後卓越進度報告蔡育仁老師實驗室 2006/09/04. Distribute Source Coding in WSNs Distributed source coding is a data compression technique to reduce the redundancy without.

後卓越進度報告蔡育仁老師實驗室 2007/06/04. DSC with Slotted ALOHA Random Access Distributed source coding (DSC) We study the effect of MACs on the efficiency (delivery.

後卓越計畫進度報告 (2007/6/4) 中央大學許健平教授淡江大學張志勇教授. Routing with Hexagonal Virtual Coordinate in Wireless Sensor Networks.

後卓越進度報告蔡育仁老師實驗室 2006/05/01. Implementation — Coverage-preserving Routing (1/2) R1, R2 and R3: disjoint routes to the destination Coverage Metric: R2.

後卓越計畫 — 子計畫四進度報告陳文村校長實驗室 MNET. Lab.2 Group Guiding Services in WSNs Leader tracking Help service Member -recall.

Talha Naeem Qureshi Joint work with Tauseef Shah and Nadeem Javaid

CS 712 | Fall 2007 Using Mobile Relays to Prolong the Lifetime of Wireless Sensor Networks Wei Wang, Vikram Srinivasan, Kee-Chaing Chua. National University.

卓越計劃進度報告 JNDI Java Naming and Directory Interface 網際網路實驗室報告人潘燕弘.

TRUST, Spring Conference, April 2-3, 2008 Taking Advantage of Data Correlation to Control the Topology of Wireless Sensor Networks Sergio Bermudez and.

M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol

A novel gossip-based sensing coverage algorithm for dense wireless sensor networks Vinh Tran-Quang a, Takumi Miyoshi a,b a Graduate School of Engineering,

Grammati Pantziou 1, Aristides Mpitziopoulos 2, Damianos Gavalas 2, Charalampos Konstantopoulos 3, and Basilis Mamalis 1 1 Department of Informatics, Technological.

Design of a distributed energy efficient clustering (DEEC) algorithm for heterogeneous wireless sensor networks.

Patch Based Mobile Sink Movement By Salman Saeed Khan Omar Oreifej.

Efficient Deployment Algorithms for Prolonging Network Lifetime and Ensuring Coverage in Wireless Sensor Networks Yong-hwan Kim Korea.

Maximum Network Lifetime in Wireless Sensor Networks with Adjustable Sensing Ranges Cardei, M.; Jie Wu; Mingming Lu; Pervaiz, M.O.; Wireless And Mobile.

On Energy-Efficient Trap Coverage in Wireless Sensor Networks Junkun Li, Jiming Chen, Shibo He, Tian He, Yu Gu, Youxian Sun Zhejiang University, China.

Wireless Sensor Network Protocols Dr. Monir Hossen ECE, KUET Department of Electronics and Communication Engineering, KUET.

ENERGY-EFFICIENT FORWARDING STRATEGIES FOR GEOGRAPHIC ROUTING in LOSSY WIRELESS SENSOR NETWORKS Presented by Prasad D. Karnik.

P-Percent Coverage Schedule in Wireless Sensor Networks Shan Gao, Xiaoming Wang, Yingshu Li Georgia State University and Shaanxi Normal University IEEE.

REECH ME: Regional Energy Efficient Cluster Heads based on Maximum Energy Routing Protocol Prepared by: Arslan Haider. 1.

Bounded relay hop mobile data gathering in wireless sensor networks

Optimal Self-placement of Heterogeneous Mobile Sensors in Sensor Networks Lidan Miao AICIP Research Oct. 19, 2004.

By Naeem Amjad 1.  Challenges  Introduction  Motivation  First Order Radio Model  Proposed Scheme  Simulations And Results  Conclusion 2.

Authors: N. Javaid, M. Aslam, K. Djouani, Z. A. Khan, T. A. Alghamdi

Maximizing Lifetime per Unit Cost in Wireless Sensor Networks

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

An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks Julien Champ and Clement Saad I-SPAN 2008, Sydney (The international.

MCEEC: MULTI-HOP CENTRALIZED ENERGY EFFICIENT CLUSTERING ROUTING PROTOCOL FOR WSNS N. Javaid, M. Aslam, K. Djouani, Z. A. Khan, T. A. Alghamdi.

Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSNs under real-time constraints Fei Yang, Isabelle Augé-Blum National Institute of.

Group Members Usman Nazir FA08-BET-179 M.Usman Saeed FA08-BET-173

A Coverage-Preserving Node Scheduling Scheme for Large Wireless Sensor Networks Di Tian, and Nicolas D. Georanas ACM WSNA ‘ 02.

Energy-Efficient Randomized Switching for Maximizing Lifetime in Tree- Based Wireless Sensor Networks Sk Kajal Arefin Imon, Adnan Khan, Mario Di Francesco,

Simulation of DeReClus Yingyue Xu September 6, 2003.

後卓越計畫進度報告楊舜仁老師實驗室 SCTP Multihoming.

“LPCH and UDLPCH: Location-aware Routing Techniques in WSNs”. Y. Khan, N. Javaid, M. J. Khan, Y. Ahmad, M. H. Zubair, S. A. Shah.

後卓越計畫進度報告楊舜仁老師實驗室 Outline  Introduction  SIP based mobile QoS model  MH registers the SIP based service  MH initiates the SIP based.

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

Abstract 1/2 Wireless Sensor Networks (WSNs) having limited power resource report sensed data to the Base Station (BS) that requires high energy usage.

後卓越計畫進度報告中央大學許健平教授淡江大學張志勇教授 94/06/05 Obstacle-Free Routing for WSNs.

1 Power-efficient Clustering Routing Protocol Based on Applications in Wireless Sensor Network Authors: Tao Liu and Feng Li Form:International Conferecnce.

How to minimize energy consumption of Sensors in WSN Dileep Kumar HMCL 30 th Jan, 2015.

Xiaobing Wu, Guihai Chen and Sajal K. Das

後卓越計畫進度報告陳志成教授實驗室 2008/01/06.

Distributed Energy Efficient Clustering (DEEC) Routing Protocol

Edinburgh Napier University

Presentation transcript:

後卓越進度報告蔡育仁老師實驗室 2006/07/10

Non-uniform Deployment for Lifetime-based Sensor Networks Propose a non-uniform density for random deployment based on the distribution of power consumption to extend the lifetime of the whole network. Consider two WSN scenarios  Multihop routing  LEACH Server Line Server Multihop Routing LEACH

Calculation of Desired Density at the Distance d from Server Iterative Density Calculation

Numerical Result — Density of Deployment as a Function of d (Distance from Server) in 50 × 250 m 2 area Node Number = 200 Node Number = 500 Distance from Server ( 10m /unit) Normalized Density

Simulation — Lifetime Comparison Node Number = 200 Node Number = 500 Rounds (Time steps) Number of alive nodes

Simulation — Coverage Comparison Node Number = 200 Node Number = 500 Rounds (Time steps) Coverage Ratio