Minimum Energy Mobile Wireless Networks IEEE JSAC 2001/10/18.

Slides:



Advertisements
Similar presentations
Mobility Increase the Capacity of Ad-hoc Wireless Network Matthias Gossglauser / David Tse Infocom 2001.
Advertisements

Routing and Congestion Problems in General Networks Presented by Jun Zou CAS 744.
Multicast in Wireless Mesh Network Xuan (William) Zhang Xun Shi.
1 K-clustering in Wireless Ad Hoc Networks Fernandess and Malkhi Hebrew University of Jerusalem Presented by: Ashish Deopura.
1 K-clustering in Wireless Ad Hoc Networks using local search Rachel Ben-Eliyahu-Zohary JCE and BGU Joint work with Ran Giladi (BGU) and Stuart Sheiber.
1 Routing Techniques in Wireless Sensor networks: A Survey.
Beyond Trilateration: On the Localizability of Wireless Ad Hoc Networks Reported by: 莫斌.
Generated Waypoint Efficiency: The efficiency considered here is defined as follows: As can be seen from the graph, for the obstruction radius values (200,
Topology Control of Multihop Wireless Networks Using Transmit Power Adjustment Paper By : Ram Ramanathan, Regina Resales-Hain Instructor : Dr Yingshu Li.
June 3, A New Multipath Routing Protocol for Ad Hoc Wireless Networks Amit Gupta and Amit Vyas.
1 Minimum-energy broadcasting in multi-hop wireless networks using a single broadcast tree Department of Computer Science and Information Engineering National.
KUASAR An efficient and light-weight protocol for routing and data dissemination in ad hoc wireless sensor networks David Andrews Aditya Mandapaka Joe.
On the Construction of Energy- Efficient Broadcast Tree with Hitch-hiking in Wireless Networks Source: 2004 International Performance Computing and Communications.
Speaker: Li-Sheng Chen 1 Jan 2, 2012 EOBDBR: an Efficient Optimum Branching-Based Distributed Broadcast Routing Protocol for Wireless Ad Hoc Networks.
LPT for Data Aggregation in Wireless Sensor networks Marc Lee and Vincent W.S Wong Department of Electrical and Computer Engineering, University of British.
Online Data Gathering for Maximizing Network Lifetime in Sensor Networks IEEE transactions on Mobile Computing Weifa Liang, YuZhen Liu.
Scalable and Distributed GPS free Positioning for Sensor Networks Rajagopal Iyengar and Biplab Sikdar Department of ECSE, Rensselaer Polytechnic Institute.
Mario Čagalj supervised by prof. Jean-Pierre Hubaux (EPFL-DSC-ICA) and prof. Christian Enz (EPFL-DE-LEG, CSEM) Wireless Sensor Networks:
Connected Dominating Sets in Wireless Networks My T. Thai Dept of Comp & Info Sci & Engineering University of Florida June 20, 2006.
1 Topology Control of Multihop Wireless Networks Using Transmit Power Adjustment Infocom /12/20.
Special Topics on Algorithmic Aspects of Wireless Networking Donghyun (David) Kim Department of Mathematics and Computer Science North Carolina Central.
International Technology Alliance In Network & Information Sciences International Technology Alliance In Network & Information Sciences 1 Cooperative Wireless.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2007 (TPDS 2007)
On the Construction of Data Aggregation Tree with Minimum Energy Cost in Wireless Sensor Networks: NP-Completeness and Approximation Algorithms National.
Efficient Gathering of Correlated Data in Sensor Networks
1 Optimal Power Allocation and AP Deployment in Green Wireless Cooperative Communications Xiaoxia Zhang Department of Electrical.
1 11 Subcarrier Allocation and Bit Loading Algorithms for OFDMA-Based Wireless Networks Gautam Kulkarni, Sachin Adlakha, Mani Srivastava UCLA IEEE Transactions.
Leader Election Algorithms for Mobile Ad Hoc Networks Presented by: Joseph Gunawan.
10/5/20151 Mobile Ad hoc Networks COE 549 Topology Control Tarek Sheltami KFUPM CCSE COE
IEEE Globecom 2010 Tan Le Yong Liu Department of Electrical and Computer Engineering Polytechnic Institute of NYU Opportunistic Overlay Multicast in Wireless.
Wireless Sensor Networks COE 499 Energy Aware Routing
1 Mobility Increases the Capacity of Ad-hoc Wireless Networks Matthias Grossglauser, David Tse IEEE Infocom 2001 (Best paper award) Oct 21, 2004 Som C.
DARP: Distance-Aware Relay Placement in WiMAX Mesh Networks Weiyi Zhang *, Shi Bai *, Guoliang Xue §, Jian Tang †, Chonggang Wang ‡ * Department of Computer.
Efficient Deployment Algorithms for Prolonging Network Lifetime and Ensuring Coverage in Wireless Sensor Networks Yong-hwan Kim Korea.
G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks Bin Wang and Sandeep K. S. Gupta NCA’03 speaker : Chi-Chih.
College of Engineering Grid-based Coordinated Routing in Wireless Sensor Networks Uttara Sawant Major Advisor : Dr. Robert Akl Department of Computer Science.
P-Percent Coverage Schedule in Wireless Sensor Networks Shan Gao, Xiaoming Wang, Yingshu Li Georgia State University and Shaanxi Normal University IEEE.
Energy-Efficient Shortest Path Self-Stabilizing Multicast Protocol for Mobile Ad Hoc Networks Ganesh Sridharan
On Reducing Broadcast Redundancy in Wireless Ad Hoc Network Author: Wei Lou, Student Member, IEEE, and Jie Wu, Senior Member, IEEE From IEEE transactions.
REECH ME: Regional Energy Efficient Cluster Heads based on Maximum Energy Routing Protocol Prepared by: Arslan Haider. 1.
Efficient Energy Management Protocol for Target Tracking Sensor Networks X. Du, F. Lin Department of Computer Science North Dakota State University Fargo,
A Dead-End Free Topology Maintenance Protocol for Geographic Forwarding in Wireless Sensor Networks IEEE Transactions on Computers, vol. 60, no. 11, November.
By Naeem Amjad 1.  Challenges  Introduction  Motivation  First Order Radio Model  Proposed Scheme  Simulations And Results  Conclusion 2.
Topology Control of Multihop Wireless Networks Using Transmit Power Adjustment Paper By : Ram Ramanathan, Regina Resales-Hain Slides adapted from R. Jayampathi.
Multi-channel Wireless Sensor Network MAC protocol based on dynamic route.
Algorithms for Energy-Efficient Multicasting in Static Ad Hoc Wireless Networks Mobile Networks and Applications 6, ,2001 Author : JEFFREY E. WIESELTHIER.
Zaid A. Shafeeq Mohammed N. Al-Damluji Al-Ahliyya Amman University Amman - Jordan September
 Tree in Sensor Network Patrick Y.H. Cheung, and Nicholas F. Maxemchuk, Fellow, IEEE 3 rd New York Metro Area Networking Workshop (NYMAN 2003)
Paper by Song Guo and Oliver Yang; supporting images and definitions from Wikipedia Presentation prepared by Al Funk, VT CS 6204, 10/30/07.
CSR: Cooperative Source Routing Using Virtual MISO in Wireless Ad hoc Networks IEEE WCNC 2011 Yang Guan, Yao Xiao, Chien-Chung Shen and Leonard Cimini.
An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks Julien Champ and Clement Saad I-SPAN 2008, Sydney (The international.
LOCALIZED MINIMUM - ENERGY BROADCASTING IN AD - HOC NETWORKS Paper By : Julien Cartigny, David Simplot, And Ivan Stojmenovic Instructor : Dr Yingshu Li.
Two Connected Dominating Set Algorithms for Wireless Sensor Networks Overview Najla Al-Nabhan* ♦ Bowu Zhang** ♦ Mznah Al-Rodhaan* ♦ Abdullah Al-Dhelaan*
Energy-Aware Data-Centric Routing in Microsensor Networks Azzedine Boukerche SITE, University of Ottawa, Canada Xiuzhen Cheng, Joseph Linus Dept. of Computer.
A Framework for Reliable Routing in Mobile Ad Hoc Networks Zhenqiang Ye Srikanth V. Krishnamurthy Satish K. Tripathi.
Efficient Resource Allocation for Wireless Multicast De-Nian Yang, Member, IEEE Ming-Syan Chen, Fellow, IEEE IEEE Transactions on Mobile Computing, April.
Localized Low-Power Topology Control Algorithms in IEEE based Sensor Networks Jian Ma *, Min Gao *, Qian Zhang +, L. M. Ni *, and Wenwu Zhu +
A Bandwidth Scheduling Algorithm Based on Minimum Interference Traffic in Mesh Mode Xu-Yajing, Li-ZhiTao, Zhong-XiuFang and Xu-HuiMin International Conference.
Mobility Increases the Connectivity of K-hop Clustered Wireless Networks Qingsi Wang, Xinbing Wang and Xiaojun Lin.
Connected Point Coverage in Wireless Sensor Networks using Robust Spanning Trees IEEE ICDCSW, 2011 Pouya Ostovari Department of Computer and Information.
SERENA: SchEduling RoutEr Nodes Activity in wireless ad hoc and sensor networks Pascale Minet and Saoucene Mahfoudh INRIA, Rocquencourt Le Chesnay.
On Mobile Sink Node for Target Tracking in Wireless Sensor Networks Thanh Hai Trinh and Hee Yong Youn Pervasive Computing and Communications Workshops(PerComW'07)
Efficient Geographic Routing in Multihop Wireless Networks Seungjoon Lee*, Bobby Bhattacharjee*, and Suman Banerjee** *Department of Computer Science University.
Construction of Optimal Data Aggregation Trees for Wireless Sensor Networks Deying Li, Jiannong Cao, Ming Liu, and Yuan Zheng Computer Communications and.
1 Minimum Interference Algorithm for Integrated Topology Control and Routing in Wireless Optical Backbone Networks Fangting Sun Mark Shayman University.
Introduction Wireless Ad-Hoc Network  Set of transceivers communicating by radio.
2010 IEEE Global Telecommunications Conference (GLOBECOM 2010)
Topology Control –power control
Minimizing Broadcast Latency and Redundancy in Ad Hoc Networks
Constructing a m-connected k-Dominating Set in Unit Disc Graphs
Presentation transcript:

Minimum Energy Mobile Wireless Networks IEEE JSAC 2001/10/18

Outline Introduction Network layer requirements The power consumption model Minimum power networks Distributed network protocol Simulations Conclusion

Introduction This paper present a position-based algorithm to set up and maintain a minimum energy network between users that are randomly deployed over an area and are allowed to move with random velocities. Each node has a low-power globe positioning system (GPS) receiver on board. The protocol is self-reconfiguring in mobile scenarios.

Network Layer Requirements A network graph is said to be “strongly connected” if there exists a path from any node to any other node in the graph. This paper take one of the nodes to be the information sink for all nodes in the network. They call this node the “master- site.”

The Power Consumption Model This model has three components –Small-scale variations –Large-scale variations –Path loss

The Power Consumption Model Small-scale variations –These are modeled by a Rayleigh distribution. –A wireless communication receiver is designed with diversity reception to combat small-scale variations. (Rake receiver) –In a rake receiver, a technique called maximum ratio combining (MRC) is used to optimally combine these independent stream.

The Power Consumption Model Large-scale variations –The received signal power averaged over small- scale variations. –A outage probability is specified for large-scale variations. The transmitter must adjust its transmit power to satisfy the specification.

The Power Consumption Model Path loss –The received signal power averaged over large- scale variations has been found to have a distance dependence which is well modeled by 1/d n. –The path loss may normally depend on the heights of the transmit antenna

The Power Consumption Model Directly transmit form A to C will consume more power than relay the message through node B.

Minimum Power Networks Consider three node i(transmitter), r(relay), and j(destination). The position of j is (x,y). Definition 1- relay region: the relay region R i→j of the transmit-relay node pair (i,j) is defined to be

Minimum Power Networks Definition 2-deployment region: any bounded set in R 2 that has the position of the nodes in Ñ as a subset is said to be a deployment region. Definition 3-enclosure and neighbor: the enclosure of a transmit node i is define as the nonempty solution ε i to the set of the equations

Minimum Power Networks

Definition 4-enclosed node: a node i is said to be enclosed if it has communication links to each of its neighbors. Definition 5-enclosure graph: the enclosure graph of a set of nodes Ñ is the graph whose vertex set is Ñ and whose edge set is where l i→k is the directed communications link from i to k.

Minimum Power Networks Theorem 1-strong connectivity: fix the deployment region D Ñ for a set of node Ñ. The enclosure graph of Ñ is strongly connected.

Distributed Network Protocol The main idea of this protocol is that a node does not need to consider all the nodes in the network to find the globe minimum power path to the master-site. This protocol can divide into two parts: –Phase1: search for enclosure –Phase2: cost distribution

Distributed Network Protocol Phase1 : Search for Enclosure –Each node in the algorithm starts a search by sending out a beacon search signal that include the position information. –Every node runs exactly the same algorithm. Then it will concentrate on a particular node and call it the transmit node. –The transmit node listens for nearby nodes and calculates the relay region for them.

Distributed Network Protocol –The transmit node must keep only those nodes that do not lie in the relay region of previously found nodes. –Each time new nodes are found, the transmit node must update it relay graph.

Distributed Network Protocol If a node found (call it k) falls in the relay region of some other found (call it j), then we mark k “dead”. We say that j “blocks” k. If a node is not blocked by any other node found in this search, then we mark the node “alive”. The set of alive nodes constitutes the set of neighbors for transmit node i when the search terminates.

Distributed Network Protocol Phase2 : Cost Distribution –The algorithm finds the optimal links on the enclosure graph. –The cost of a node i is defined as the minimum power necessary for i to establish a path to the master-site.

Distributed Network Protocol –Each node calculates the minimum cost it can attain given the cost of its neighbors. Let n N(i). When i receives the information Cost(n), it computes: then i compute

Simulations

Conclusion This paper present a routing protocol which find the minimum power topology for a stationary ad hoc network environment. Brief and to the point, this paper modeled the ad hoc network as the spanning tree then find the minimum spanning tree.