Smart Antenna Research Laboratory Aravind Kailas

Slides:



Advertisements
Similar presentations
Quality-aware Data Collection in Energy Harvesting WSN Nga Dang Elaheh Bozorgzadeh Nalini Venkatasubramanian University of California, Irvine.
Advertisements

Presented by : Poorya Ghafoorpoor Yazdi Eastern Mediterranean University Mechanical Engineering Department Master Thesis Presentation Eastern Mediterranean.
Cooperative Multiple Input Multiple Output Communication in Wireless Sensor Network: An Error Correcting Code approach using LDPC Code Goutham Kumar Kandukuri.
System Design for Cognitive Radio Communications
PROMETHEUS Intelligent Multi-Stage Energy Transfer System for Near Perpetual Sensor Networks Xiaofan JiangJoseph PolastreDavid Culler Electrical Engineering.
Energy-Efficient Target Coverage in Wireless Sensor Networks Mihaela Cardei, My T. Thai, YingshuLi, WeiliWu Annual Joint Conference of the IEEE Computer.
Peering in Infrastructure Ad hoc Networks Mentor : Linhai He Group : Matulya Bansal Sanjeev Kohli EE 228a Course Project.
Cross Layer Design in Wireless Networks Andrea Goldsmith Stanford University Crosslayer Design Panel ICC May 14, 2003.
August 18-19, 2002 UCSC Baskin School of Engineering1 UCSC PERC COMPONENT: Protocols for Wireless Internetworks J.J. Garcia-Luna-Aceves Computer Communication.
Researches in MACS Lab Prof. Xiaohua Jia Dept of Computer Science City University of Hong Kong.
CS230 Project Mobility in Energy Harvesting Wireless Sensor Network Nga Dang, Henry Nguyen, Xiujuan Yi.
Kick-off meeting 3 October 2012 Patras. Research Team B Communication Networks Laboratory (CNL), Computer Engineering & Informatics Department (CEID),
1 Energy Efficient Communication in Wireless Sensor Networks Yingyue Xu 8/14/2015.
MAXIMIZING SPECTRUM UTILIZATION OF COGNITIVE RADIO NETWORKS USING CHANNEL ALLOCATION AND POWER CONTROL Anh Tuan Hoang and Ying-Chang Liang Vehicular Technology.
International Technology Alliance In Network & Information Sciences International Technology Alliance In Network & Information Sciences 1 Cooperative Wireless.
Emerging Technologies in Smart Device Communications Mary Ann Ingram School of Electrical and Computer Engineering Georgia Institute of Technology TR-50.
M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol
Multimedia & Networking Lab
1 Cooperative Wireless Networking Elza Erkip Department of Electrical and Computer Engineering Polytechnic Institute of New York University.
GreenDelivery: Proactive Content Caching and Push with Energy- Harvesting-based Small Cells IEEE Communications Magazine, 2015 Sheng Zhou, Jie Gong, Zhenyu.
Optimal Power Control, Rate Adaptation and Scheduling for UWB-Based Wireless Networked Control Systems Sinem Coleri Ergen (joint with Yalcin Sadi) Wireless.
Function Computation over Heterogeneous Wireless Sensor Networks Xuanyu Cao, Xinbing Wang, Songwu Lu Department of Electronic Engineering Shanghai Jiao.
Green Communications Kaya Tutuncuoglu 4/26/2010. Outline  The “Green” Concept  Green Communications  Alternative Energy Sources  Energy-Aware Routing.
Overview of Research Activities Aylin Yener
User Cooperation via Rateless Coding Mahyar Shirvanimoghaddam, Yonghui Li, and Branka Vucetic The University of Sydney, Australia IEEE GLOBECOM 2012 &
نیمسال اوّل افشین همّت یار دانشکده مهندسی کامپیوتر مخابرات سیّار (626-40) ارتباطات همکارانه.
An Energy-Efficient MAC Protocol for Wireless Sensor Networks Qingchun Ren and Qilian Liang Department of Electrical Engineering, University of Texas at.
ELECTIONEL ECTI ON ELECTION: Energy-efficient and Low- latEncy sCheduling Technique for wIreless sensOr Networks Shamim Begum, Shao-Cheng Wang, Bhaskar.
Cognitive Radio: Next Generation Communication System
Indian Institute of Science (IISc), Bangalore, India Selection Criteria and Distributed Selection Algorithms in Wireless Cellular and Sensor Networks Neelesh.
Presented by: Sheeraz Ahmed 1.  ARCUN a reliable, energy-efficient and high throughput routing protocol  Cooperative routing a potential scheme for.
Link-Utility-Based Cooperative MAC Protocol for Wireless Multi-Hop Networks Yong Zhou, Ju Liu, Lina Zheng, Chao Zhai, He Chen National Mobile Communications.
Cooperative MIMO Paradigms for Cognitive Radio Networks
TELEHEALTH [3] Remote Patient Monitoring obtained from patches of sensors on human body. Challenge: Energy efficient Body Area Network (BAN) and reliable.
S. K. S. Gupta, Arizona State Univ On Maximizing Lifetime of Multicast Trees in Wireless Ad hoc Networks Bin Wang and Sandeep K. S. Gupta Computer Science.
Maximizing Angle Coverage in Visual Sensor Networks Kit-Yee Chow, King-Shan Lui and Edmund Y. Lam Department of Electrical and Electronic Engineering The.
On Mitigating the Broadcast Storm Problem with Directional Antennas Sheng-Shih Wang July 14, 2003 Chunyu Hu, Yifei Hong, and Jennifer Hou Dept. of Electrical.
Network System Lab. Sungkyunkwan Univ. Differentiated Access Mechanism in Cognitive Radio Networks with Energy-Harvesting Nodes Network System Lab. Yunmin.
Wireless Networks Projects Roberto Riggio, PhD CREATE-NET Via Alla Cascata 56/c 38123, Povo (TN)
IC1301 -WiPE Optical Power Delivery and Data Transmission in a Wireless and Batteryless Microsystem Assoc. Prof. Şenol Mutlu Boğaziçi Unviersity,
1 Wireless Networking Understanding the departure from wired networks, Case study: IEEE (WiFi)
Medium Access Control. MAC layer covers three functional areas: reliable data delivery access control security.
Energy-Aware Opportunistic Mobile Data Offloading
EE 525 Antenna Engineering
Is there a promising way?
Enabling QoS Multipath Routing Protocol for Wireless Sensor Networks
Sensing Support Comments
Energy Constrained Routing Algorithm for Wireless Networks
Advanced Wireless Transmission for Skin Patches and Implants
SENSYS Presented by Cheolki Lee
Speaker: Qi-Hong Cai Advisor: Dr. Ho-Ting Wu 2017/4/13
Thanasis Korakis, FP7 FLEX Project Coordinator
Multi-channel, multi-radio wireless networks
Algorithms for Big Data Delivery over the Internet of Things
Net 435: Wireless sensor network (WSN)
Bluetooth Based Smart Sensor Network
Wireless Communication Co-operative Communications
Introduction to locality sensitive approach to distributed systems
Wireless Communication Co-operative Communications
Opportunistic Beam-forming with Limited Feedback
On Achieving Maximum Network Lifetime Through Optimal Placement of Cluster-heads in Wireless Sensor Networks High-Speed Networking Lab. Dept. of CSIE,
Sensing Support Comments
Outline 1. INTRODUCTION 2. PRELIMINARIES 3.THE PROPOSED PROTOCOL
Setting of DTIM Interval for MCCA
EE 525 Antenna Engineering
Submission Title: [channel dependent initial backoff of CSMA]
Energy Provision and Storage for Pervasive Computing
Distributed Minimum-Cost Clustering for Underwater Sensor Networks
Survey on Coverage Problems in Wireless Sensor Networks - 2
Survey on Coverage Problems in Wireless Sensor Networks
Presentation transcript:

Green Wireless Networking Using Concurrent Cooperative Transmissions and Energy Scavenging Smart Antenna Research Laboratory Aravind Kailas (aravindk@ieee.org) School of Electrical and Computer Engineering Some Applications of Cooperative Networking Structural Health Monitoring Problem Statement: Solve energy problem in wireless networks Preserve cycle-life of the rechargeable batteries Extending base station coverage MAC-free aerial data gathering Concurrent Cooperative Transmissions Fraction of energy saved (FES) in a single broadcast Factors of life extension (FLE) during multiple broadcasts Each cycle is an OLA with transmission threshold (OLA-T) broadcast OLA1 2.78 Strip Strip-shaped networks 0.64 Minimum Node Degree Diversity and array gain No contention Node mobility Disc FES 1.47 FLE Disc-shaped networks 0.32 1 10 100 1 10 100 Node Degree # Alternating Sets Alternating OLA with transmission threshold (A-OLA-T) with 2 alternating sets Y. W. Hong and A. Scaglione, “Energy-Efficient Broadcasting with Cooperative Transmissions in Wireless Sensor Networks,” IEEE Trans. Wireless Commun., vol. 5, no. 10, pp. 2844-55, Oct. 2006. Energy Scavenging Using a Hybrid Energy Storage System First-order approximation of SC energy mechanisms S1 S2 A A Energy cost of 3562 or N bits Orange area represents the radiated energy (100nJ/bit) Load Supercapacitor (SC) Energy Harvesting Unit Solar C R Ih R C 570mW Dark blue area represents the circuit energy (300nJ/bit) Energy pulse from car Harvester Rechargeable Battery SC 1 residual energy B B 1.425mJ Leakage ignored here; how many bits can be transmitted if leakage is included? Harvesting-aware algorithm using HESS extends battery life by 400% Cooperative transmissions and energy harvesting SC + - VH(t) RL S1(t)=1 RSC Rleak C S1(t)=0 S2(t)=1 S2(t)=0 S3(t)=1 S3(t)=0 570mW Energy pulse from car Main idea: combine SC energy on multiple nodes, if necessary, to make a cost-free transmission SC 2 residual energy Load leakage 1.425mJ SC Energy SC Energy SC Energy Not enough on one node 2.5 3.5 Harvester Rechargeable Battery Clearly, with regards to SC2 energy, you “use it or lose it”. CT would enable the data rate to be increased due to array and diversity gain User cooperation1 for nodes with only SCs increases throughput by a factor of ~7 relative to non-cooperative schemes J. W. Jung and M. A. Ingram, “Residual-energy-activated cooperative transmission (REACT) to avoid the energy hole,” IEEE International Conference on Communications (ICC) Workshop on Cooperative and Cognitive Mobile Networks (CoCoNet3), June 2010, accepted.