Efficient, Proximity-Aware Load Balancing for DHT-Based P2P Systems Yingwu Zhu, Yiming Hu Appeared on IEEE Trans. on Parallel and Distributed Systems,

Slides:



Advertisements
Similar presentations
SkipNet: A Scalable Overlay Network with Practical Locality Properties Nick Harvey, Mike Jones, Stefan Saroiu, Marvin Theimer, Alec Wolman Microsoft Research.
Advertisements

CAN 1.Distributed Hash Tables a)DHT recap b)Uses c)Example – CAN.
Peer to Peer and Distributed Hash Tables
Digital Library Service – An overview Introduction System Architecture Components and their functionalities Experimental Results.
Scalable Content-Addressable Network Lintao Liu
Peer-to-Peer Systems Chapter 25. What is Peer-to-Peer (P2P)? Napster? Gnutella? Most people think of P2P as music sharing.
Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility Antony Rowstron, Peter Druschel Presented by: Cristian Borcea.
Presented By- Sayandeep Mitra TH SEMESTER Sensor Networks(CS 704D) Assignment.
Chord: A scalable peer-to- peer lookup service for Internet applications Ion Stoica, Robert Morris, David Karger, M. Frans Kaashock, Hari Balakrishnan.
SplitStream: High- Bandwidth Multicast in Cooperative Environments Monica Tudora.
Common approach 1. Define space: assign random ID (160-bit) to each node and key 2. Define a metric topology in this space,  that is, the space of keys.
Small-world Overlay P2P Network
ZIGZAG A Peer-to-Peer Architecture for Media Streaming By Duc A. Tran, Kien A. Hua and Tai T. Do Appear on “Journal On Selected Areas in Communications,
©NEC Laboratories America 1 Hui Zhang Samrat Ganguly Sudeept Bhatnagar Rauf Izmailov NEC Labs America Abhishek Sharma University of Southern California.
Network Coding for Large Scale Content Distribution Christos Gkantsidis Georgia Institute of Technology Pablo Rodriguez Microsoft Research IEEE INFOCOM.
Peer-to-Peer Based Multimedia Distribution Service Zhe Xiang, Qian Zhang, Wenwu Zhu, Zhensheng Zhang IEEE Transactions on Multimedia, Vol. 6, No. 2, April.
A Trust Based Assess Control Framework for P2P File-Sharing System Speaker : Jia-Hui Huang Adviser : Kai-Wei Ke Date : 2004 / 3 / 15.
Load Balancing in Structured P2P Systems (DHTs) Sonesh Surana [Brighten Godfrey, Karthik Lakshminarayanan, Ananth Rao, Ion Stoica,
P2P: Advanced Topics Filesystems over DHTs and P2P research Vyas Sekar.
Design, Implementation, and Evaluation of Differentiated Caching Services Ying Lu, Tarek F. Abdelzaher, Avneesh Saxena IEEE TRASACTION ON PARALLEL AND.
SCALLOP A Scalable and Load-Balanced Peer- to-Peer Lookup Protocol for High- Performance Distributed System Jerry Chou, Tai-Yi Huang & Kuang-Li Huang Embedded.
Online Data Gathering for Maximizing Network Lifetime in Sensor Networks IEEE transactions on Mobile Computing Weifa Liang, YuZhen Liu.
Chord-over-Chord Overlay Sudhindra Rao Ph.D Qualifier Exam Department of ECECS.
SkipNet: A Scaleable Overlay Network With Practical Locality Properties Presented by Rachel Rubin CS294-4: Peer-to-Peer Systems By Nicholas Harvey, Michael.
Supporting VCR-like Operations in Derivative Tree-Based P2P Streaming Systems Tianyin Xu, Jianzhong Chen, Wenzhong Li, Sanglu Lu Nanjing University Yang.
12006/9/26 Load Balancing in Dynamic Structured P2P Systems Brighten Godfrey, Karthik Lakshminarayanan, Sonesh Surana, Richard Karp, Ion Stoica INFOCOM.
P2P Course, Structured systems 1 Skip Net (9/11/05)
P2P Course, Structured systems 1 Introduction (26/10/05)
ICDE A Peer-to-peer Framework for Caching Range Queries Ozgur D. Sahin Abhishek Gupta Divyakant Agrawal Amr El Abbadi Department of Computer Science.
File Sharing : Hash/Lookup Yossi Shasho (HW in last slide) Based on Chord: A Scalable Peer-to-peer Lookup Service for Internet ApplicationsChord: A Scalable.
“Umbrella”: A novel fixed-size DHT protocol A.D. Sotiriou.
Structured P2P Network Group14: Qiwei Zhang; Shi Yan; Dawei Ouyang; Boyu Sun.
Roger ZimmermannCOMPSAC 2004, September 30 Spatial Data Query Support in Peer-to-Peer Systems Roger Zimmermann, Wei-Shinn Ku, and Haojun Wang Computer.
Towards Efficient Load Balancing in Structured P2P Systems Yingwu Zhu, Yiming Hu University of Cincinnati.
Other Structured P2P Systems CAN, BATON Lecture 4 1.
PIC: Practical Internet Coordinates for Distance Estimation Manuel Costa joint work with Miguel Castro, Ant Rowstron, Peter Key Microsoft Research Cambridge.
Multi-level Hashing for Peer-to-Peer System in Wireless Ad Hoc Environment Dewan Tanvir Ahmed and Shervin Shirmohammadi Distributed & Collaborative Virtual.
09/07/2004Peer-to-Peer Systems in Mobile Ad-hoc Networks 1 Lookup Service for Peer-to-Peer Systems in Mobile Ad-hoc Networks M. Tech Project Presentation.
Load Balancing in Structured P2P System Ananth Rao, Karthik Lakshminarayanan, Sonesh Surana, Richard Karp, Ion Stoica IPTPS ’03 Kyungmin Cho 2003/05/20.
Distributed Load Balancing for Key-Value Storage Systems Imranul Hoque Michael Spreitzer Malgorzata Steinder.
1 On the Placement of Web Server Replicas Lili Qiu, Microsoft Research Venkata N. Padmanabhan, Microsoft Research Geoffrey M. Voelker, UCSD IEEE INFOCOM’2001,
A Prediction-based Fair Replication Algorithm in Structured P2P Systems Xianshu Zhu, Dafang Zhang, Wenjia Li, Kun Huang Presented by: Xianshu Zhu College.
1 Distributed Hash Tables (DHTs) Lars Jørgen Lillehovde Jo Grimstad Bang Distributed Hash Tables (DHTs)
Efficient Peer to Peer Keyword Searching Nathan Gray.
1 On the Placement of Web Server Replicas Lili Qiu, Microsoft Research Venkata N. Padmanabhan, Microsoft Research Geoffrey M. Voelker, UCSD IEEE INFOCOM’2001,
Load-Balancing Routing in Multichannel Hybrid Wireless Networks With Single Network Interface So, J.; Vaidya, N. H.; Vehicular Technology, IEEE Transactions.
CHAN Siu Lung, Daniel CHAN Wai Kin, Ken CHOW Chin Hung, Victor KOON Ping Yin, Bob SPRINT: A Scalable Parallel Classifier for Data Mining.
An IP Address Based Caching Scheme for Peer-to-Peer Networks Ronaldo Alves Ferreira Joint work with Ananth Grama and Suresh Jagannathan Department of Computer.
November 17, 2015Department of Computer Sciences, UT Austin1 SDIMS: A Scalable Distributed Information Management System Praveen Yalagandula Mike Dahlin.
Bounded relay hop mobile data gathering in wireless sensor networks
DHT-based unicast for mobile ad hoc networks Thomas Zahn, Jochen Schiller Institute of Computer Science Freie Universitat Berlin 報告 : 羅世豪.
1 Distributed Hash Table CS780-3 Lecture Notes In courtesy of Heng Yin.
1. Outline  Introduction  Different Mechanisms Broadcasting Multicasting Forward Pointers Home-based approach Distributed Hash Tables Hierarchical approaches.
Pastry Antony Rowstron and Peter Druschel Presented By David Deschenes.
Plethora: Infrastructure and System Design. Introduction Peer-to-Peer (P2P) networks: –Self-organizing distributed systems –Nodes receive and provide.
On Reducing Mesh Delay for Peer- to-Peer Live Streaming Dongni Ren, Y.-T. Hillman Li, S.-H. Gary Chan Department of Computer Science and Engineering The.
LOOKING UP DATA IN P2P SYSTEMS Hari Balakrishnan M. Frans Kaashoek David Karger Robert Morris Ion Stoica MIT LCS.
CS Spring 2014 CS 414 – Multimedia Systems Design Lecture 37 – Introduction to P2P (Part 1) Klara Nahrstedt.
Bandwidth-Efficient Continuous Query Processing over DHTs Yingwu Zhu.
INTERNET TECHNOLOGIES Week 10 Peer to Peer Paradigm 1.
Security Kim Soo Jin. 2 Contents Background Introduction Secure multicast using clustering Spatial Clustering Simulation Experiment Conclusions.
P2P Search COP6731 Advanced Database Systems. P2P Computing  Powerful personal computer Share computing resources P2P Computing  Advantages: Shared.
CS Spring 2012 CS 414 – Multimedia Systems Design Lecture 37 – Introduction to P2P (Part 1) Klara Nahrstedt.
NCLAB 1 Supporting complex queries in a distributed manner without using DHT NodeWiz: Peer-to-Peer Resource Discovery for Grids Sujoy Basu, Sujata Banerjee,
Malugo – a scalable peer-to-peer storage system..
A Two-Tier Heterogeneous Mobile Ad Hoc Network Architecture and Its Load-Balance Routing Problem C.-F. Huang, H.-W. Lee, and Y.-C. Tseng Department of.
Plethora: A Locality Enhancing Peer-to-Peer Network Ronaldo Alves Ferreira Advisor: Ananth Grama Co-advisor: Suresh Jagannathan Department of Computer.
COS 461: Computer Networks
Zhichen Xu, Mallik Mahalingam, Magnus Karlsson
COS 461: Computer Networks
Presentation transcript:

Efficient, Proximity-Aware Load Balancing for DHT-Based P2P Systems Yingwu Zhu, Yiming Hu Appeared on IEEE Trans. on Parallel and Distributed Systems, vol. 16, no. 4, April 2005 Presented by Ki

2 Outline Introduction System Design Proximity-Aware Load Balancing Experimental Evaluations Conclusions

3 Introduction DHT-based P2P systems like Chord, Pastry, Tapestry, CAN, …  Provide a distributed hash table abstraction for object storage and retrieval  Assume nodes are homogeneous Two main drawbacks  Imbalance load  Node heterogeneity

4 Introduction Existing solutions for DHT load balancing  Some ignore node heterogeneity  Some ignore proximity information This work proposes a proximity-aware load balancing scheme which considered the above two aspects

5 System Design - Basic Virtual Server (VS)  Act like an autonomous peer  Responsible for a contiguous portion of the DHT’s identifier space  Responsible for certain amount of load Physical Peer  Can host multiple virtual servers Heavily loaded physical peer  Moves some of its virtual servers to other lightly loaded physical peers to achieve load balancing  Movement of virtual server can be viewed as a leave operation followed by a join operation

6 System Design – Four Phrases The load balancing scheme proceed in 4 phrases  Load balancing information (LBI) aggregation Collect load and capacity information of whole system  Node classification Classify nodes into HEAVY, LIGHT, NEUTRAL  Virtual server assignment (VSA) Determine the VS assignment to make HEAVY nodes becomes LIGHT Proximity-aware  Virtual server transferring (VST)

7 System Design – k-ary Tree on DHT A k-ary tree (KT) is built on top of the DHT  Occupying the same identifier space KT root node is responsible for the entire identifier space Each child node is responsible for a portion of their parent’s identifier space

8 System Design – k-ary Tree on DHT A KT node is responsible for identifier space region  key & host is obtained by procedure plant_KT_node()  Keeps track of its parent and children KT node, X, is planted into a virtual server which responsible for X.key Example (KT Node X, VS S):  X.region = (3,5]  X.key = 4  S’s region = (3, 6]  X is planted in S

9 System Design – k-ary Tree on DHT For KT node X, its region  is further divided into k parts, then taken by its k children Until…  X’s region is completely covered by its hosting VS Each KT node periodically check if its region is completely covered by its VS  Yes  delete the existing children  No  keep k children

10 Load Balancing Information Aggregation Load Balancing Information (LBI) of node i  L i  total load of VS in node i  C i  capacity of node i  L i,min  minimum load of VS in node i X.host randomly responds to one of its VS only

11 Load Balancing Information Aggregation KT root node obtains the system-wide LBI  L  Total load  C  Total capacity  L min  minimum load of all VS in system KT root node distribute the system-wide LBI  Along the tree, back to the leaf nodes, VS and finally the DHT node

12 Node Classification System-wide utilization = L / C Utilization of node i = L i / C i Define T i = (L / C + ε) * C i  ε is a parameter for trade off between amount of load movement and quality of load balance Classification  HEAVY node if L i > T i  LIGHT node if (T i – L i ) >= L min  NEUTRAL node if 0 <= (T i – L i ) < L min

13 Virtual Server Assignment Each HEAVY DHT node i  Randomly choose a subset of its VS that minimizes s.t.  Minimized the amount of load movement  VSA info.: … Each LIGHT DHT node j  VSA info.: This VSA information propagates upward along the KT

14 Virtual Server Assignment Proximity Ignorant Each KT node i  Collects the VSA information until the a pairing_threshold  Uses a best-fit heuristic to reassign VS Reassign VS in HEAVY nodes to LIGHT nodes And minimize load movement  DHT nodes of reassigned VS get notified while the rest of VSA information propagate to i’s parent

15 Virtual Server Assignment Proximity Aware Use landmark clustering  Measure distance to a number of landmark nodes  Obtain a landmark vector which represent point in a m-dimensional space  Nodes with close landmark vectors are in general physically close Transform the landmark m-dimensional space to the DHT identifier space and obtains a DHT key, LM i  By Hilbert curve, i.e. N m  N  Proximity preserving

16 Virtual Server Assignment Proximity Aware Each node i independently determines its landmark vector and its corresponding DHT key, LM i Node publish its VSA information in the DHT network with the DHT key LM i  Node j that responsible for the region contains LM i receive the VSA information  Node j propagate the received VSA information into the KT

17 Virtual Server Transferring Upon receiving the reassigned VSA info.  HEAVY node transfer the reassigned VS to the LIGHT node The transfer of VS would cause KT to reconstruct Lazy migration  Reconstruction of KT only after the completion of all transfers

18 Experimental Evaluations Load Balancing Information aggregation and virtual server assignment latency

19 Experimental Evaluations Underlying network  Generated by GT-ITM with about 5000 nodes Underlying DHT overlay  Chord with 4096 nodes  5 virtual servers in each node, exponential identifier space k-ary tree  k = 2 Pairing threshold  50 Landmark node count  15

20 Experimental Evaluations Nodes carry loads proportional to their capacities by reassigning virtual servers

21 Experimental Evaluations Cumulative distribution of moved load  Proximity-aware 36% within 2 hops, 57% within 10 hops  Proximity-ignorant 17% within 10 hops Proximity-aware  Reduce load balancing cost  Fast and efficient load balancing

22 Experimental Evaluations Effect of node churn (join & leave) Overhead = (M d – M s ) / M s  M d : number of VSA messages with node churn  M s : number of VSA messages without node churn

23 Conclusions This work focuses on an efficient, proximity-aware load balancing scheme  Align load distribution and node capacity  Use proximity information to guide load reassignment and transferring