Presentation is loading. Please wait.

Presentation is loading. Please wait.

Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Immune System and Search Technology Designing a Fast Search Algorithm.

Published byNelson Booth Modified over 8 years ago

Similar presentations

Presentation on theme: "Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Immune System and Search Technology Designing a Fast Search Algorithm."— Presentation transcript:

1

2 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Immune System and Search Technology Designing a Fast Search Algorithm for P2P Network using concepts from Immune Systems

3 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Overview of the Presentation ● P2P Network – Paradigm for Decentralised Computing ● Immune System Features ● Experimental Setup ● Simulation Results

4 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Peer To Peer Network ● Most Direct Method of Connecting Computers – Simple – Inexpensive – No Boss – No Regulation

5 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Peer To Peer Network ● PCs at the edge of the network are called “Peers” ● Peers can retrieve objects directly from each other Advantages of a P2P Network A large collection of peers may be available for content distribution-- sometimes millions! User takes advantage of the network’s currently available resources.

6 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Peer To Peer Network ● Problem of Hugeness – Emergence of Protocol ● Centralized Directory – Napster ● Decentralized Directory – KaZaA ● Query Flooding – Gnutella

7 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Centralized Directory (Napster) When peer connects, it informs central server: – IP address – content Centralized directory server peers Alice Bob 1 1 1 1 3 Alice queries for Das Wunder von Bern Alice requests file from Bob While file transfer is decentralized, locating content is highly centralized

8 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Centralized Directory (Napster) ● Fast ● Single point of failure – Application crash ● Performance bottleneck ● Huge database to maintain ● Copyright infringement – Legal proceedings may result in the company having to shut down directory server Centralized directory server peers Alice Bob 1 1 1 1 3

9 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Intermediate Arrangement (Kazaa) Feature Has a centralized server that maintains user registrations, logs users into the systems to keep statistics, provides downloads of client software. Two client types are supported: Supernodes (fast cpus + high bandwidth connections) Nodes (slower cpus and/or connections) Supernodes addresses are provided in the initial download. They also maintain searchable indexes and proxies search requests for users. ^

10 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Totally Decentralized (Gnutella) Basic Feature ● no hierarchy, peers have similar responsibilities: no group leader ● no peer maintains directory info ● highly decentralized Joining Algorithm ● use bootstrap node to learn about others ● Join message ^

11 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Totally Decentralized (Gnutella) Message Query : ● Send query to neighbors ● Neighbors forward query ● If queried peer has object, it sends message back to querying peer ● The queried peer forwards the query to its immediate neighbor. ● The resulting results are carried back to the user. ● A message Flooding occurs ^

12 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Totally Decentralized (Gnutella) Pros : ● Totally Decentralized query ● Robust; Query doesn't stop on break down of one of the nodes ● Fresh Results : No outdated Index Cons ● Query radius: Query Radius can be long ● Excessive query traffic : 25% of the total traffic is query traffic Courtesy : Limewire

13 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Totally Decentralized (Gnutella) Challenges Ahead : ● Reduce Query time ● Stop Flooding; use Intelligent method for search to stop network congestion Topology of Gnutella Network Total Traffic in Gnutella Network is 1.7 Gbps 1.7% of total traffic in US Internet Backbone

14 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly P2P: Totally Decentralized (Gnutella) Perspective ● Introduce Intelligence in the System through Bio- Inspired Techniques ● Ants, Immune System Topology of Gnutella Network Total Traffic in Gnutella Network is 1.7 Gbps 1.7% of total traffic in US Internet Backbone

15 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Artificial Immune System ● Relatively new branch of computer science – Using natural immune system as a metaphor for solving computational problems – Not modelling the immune system ● Variety of applications so far … – Fault diagnosis (Ishida) – Computer security (Forrest, Kim) – Novelty detection (Dasgupta) – Robot behaviour (Lee) – Machine learning (Hunt, Timmis, de Castro) – AIS are computational systems, inspired by theoretical immunology and observed immune functions, which are applied to complex problem domains (Timmis, 2001)

16 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Why the Immune System? ● Recognition – Anomaly detection – Noise tolerance ● Robustness ● Feature extraction ● Diversity ● Reinforcement learning ● Memory ● Distributed ● Adaptive

17 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Role of the Immune System ● Protect our bodies from infection ● Primary immune response – Launch a response to invading pathogens ● Secondary immune response – Remember past encounters – Faster response the second time around MHC proteinAntigen APC Peptide T-cell Activated T-cell B- Lymphokines Activated B-cell (plasma cell) ( I ) ( III ) ( IV ) ( V ) ( VI ) ( VII ) ( II )

18 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Role of the Immune System ● Remembers encounters – No need to start from scratch – Memory cells Lymphatic vessels Lymph nodes Thymus Spleen Tonsils and adenoids Bone marrow Appendix Peyer’s patches Primary lymphoid organs Secondarylymphoid organs Epitopes - B cell Receptors Antigen The immune recognition is based on the complementarily between the binding region of the receptor and a portion of the antigen called epitope.

19 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Role of the Immune System ● Antibodies present a single type of receptor, antigens might present several epitopes. ● This means that different antibodies can recognize a single antigen Lymphatic vessels Lymph nodes Thymus Spleen Tonsils and adenoids Bone marrow Appendix Peyer’s patches Primary lymphoid organs Secondarylymphoid organs Epitopes - B cell Receptors Antigen The immune recognition is based on the complementarily between the binding region of the receptor and a portion of the antigen called epitope.

20 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Clonal Selection (Burnet, 1978) ● Elimination of self antigens ● Proliferation and differentiation on contact of mature lymphocytes with antigen ● Restriction of one pattern to one differentiated cell and retention of that pattern by clonal descendants ● Generation of new random genetic changes, subsequently expressed as diverse antibody patterns by a form of accelerated somatic mutation

21 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly General Framework for AIS Application Domain Representation Affinity MeasuresImmune Algorithms Solution P2P Network Search Search Item - Antigen Similarity (message,search item) ImmuneSearch Algorithm

22 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Reiterating the Perspective Solution P2P Network Search Search Item - Antigen Similarity (message,search item) ImmuneSearch Algorithm Design Search Algorithm ● Stop Flooding; ● Reduce Query Time

23 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Modelling the Network Design Search Algorithm ● Stop Flooding; ● Reduce Query Time Information Profile – Immune System Search Profile – Fußball User

24 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Modelling the Network Design Search Algorithm ● Stop Flooding; ● Reduce Query Time Zipf Law (Information and SearchProfile) 1 1 1 1 1 1 1 1 0 0 0 0 0 2 2 3

25 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Flooding Flooding essentially implies sending the message packet to all the neighboring nodes

26 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Random Walk A Message packet travels at its will

27 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Immune Search Algorithm Consists of two parts 1.The movement of Message Packets 2.Rearrangement of Topology Proliferation Mutation High Concentration of Packets Homing Antibodies

28 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Immune Search Algorithm Consists of two parts 1.The movement of Message Packets 2.Rearrangement of Topology Aim Cluster Similar Nodes (Similar in Information and Search Profile) Algorithm Move nodes similar to user node closer to the user

29 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Immune Search Movement Depends on 1.The Distance from the user node 2.Amount of Matching 3.Age Aim Cluster Similar Nodes (Similar in Information and Search Profile) Algorithm Move nodes similar to user node closer to the user

30 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Immune Search Movement Depends on 1.The Distance from the user node 2.Amount of Matching 3.Age Aim Cluster Similar Nodes (Similar in Information and Search Profile) Algorithm Move nodes similar to user node closer to the user

31 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Search the Network – Immune Search Movement Depends on 1.The Distance from the user node 2.Amount of Matching 3.Age Aim Cluster Similar Nodes (Similar in Information and Search Profile) Algorithm Move nodes similar to user node closer to the user No Movement

32 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Experimental Results Experiment : Run for 100 generation, without changing the participating nodes Each Generation 100 searches by users selected randomly Efficiency No. Of Search Items found in 50 time steps 100

33 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Experimental Results (Clustering) 100

34 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Experimental Results Experiment : Change 20 % of the node 100

35 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Experimental Results Experiment : Change 5% of the node at each generation 100

36 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Amount of Change in Neighborhood Experimental Results

37 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly ● Simulate the Results in Real Network ● Take into account the important concept of Network Traffic ● Test the algorithm with sophisticated Information Profile and Search Profile ● Building up mathematical framework through which the simulation results can be analytically justified Future Work

38 Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Fragen und Antworten

Download ppt "Zentrum für Hochleistungsrechnen (ZHR) – A Bios Group Presentation Niloy Ganguly Immune System and Search Technology Designing a Fast Search Algorithm."

Similar presentations

V-Detector: A Negative Selection Algorithm Zhou Ji, advised by Prof. Dasgupta Computer Science Research Day The University of Memphis March 25, 2005.

V-Detector: A Negative Selection Algorithm Zhou Ji, advised by Prof. Dasgupta Computer Science Research Day The University of Memphis March 25, 2005.
CIFD: Computational Immunology for Fraud Detection

CIFD: Computational Immunology for Fraud Detection
Peer-to-Peer and Social Networks An overview of Gnutella.

Peer-to-Peer and Social Networks An overview of Gnutella.
P2P data retrieval DHT (Distributed Hash Tables) Partially based on Hellerstein’s presentation at VLDB2004.

P2P data retrieval DHT (Distributed Hash Tables) Partially based on Hellerstein’s presentation at VLDB2004.
Clayton Sullivan PEER-TO-PEER NETWORKS. INTRODUCTION What is a Peer-To-Peer Network A Peer Application Overlay Network Network Architecture and System.

Clayton Sullivan PEER-TO-PEER NETWORKS. INTRODUCTION What is a Peer-To-Peer Network A Peer Application Overlay Network Network Architecture and System.
Immune System Part III:

Immune System Part III:
1 BY: Nazanin Asadi Zohre Molaei Isfahan University of Technology.

1 BY: Nazanin Asadi Zohre Molaei Isfahan University of Technology.
1 An Overview of Gnutella. 2 History The Gnutella network is a fully distributed alternative to the centralized Napster. Initial popularity of the network.

1 An Overview of Gnutella. 2 History The Gnutella network is a fully distributed alternative to the centralized Napster. Initial popularity of the network.
16-1 Topics Immunity Lymphoid system. 16-2 Immunity Matures throughout life Has memory – enhanced response to pathogens Vaccination – deliberate exposureto.

16-1 Topics Immunity Lymphoid system Immunity Matures throughout life Has memory – enhanced response to pathogens Vaccination – deliberate exposureto.
Artificial Immune Systems Andrew Watkins. Why the Immune System? Recognition –Anomaly detection –Noise tolerance Robustness Feature extraction Diversity.

Artificial Immune Systems Andrew Watkins. Why the Immune System? Recognition –Anomaly detection –Noise tolerance Robustness Feature extraction Diversity.
Cis3.2 -- e-commerce -- lecture #6: Content Distribution Networks and P2P (based on notes from Dr Peter McBurney © 2002-2005)

Cis e-commerce -- lecture #6: Content Distribution Networks and P2P (based on notes from Dr Peter McBurney © )
Spotlighting Decentralized P2P File Sharing Archie Kuo and Ethan Le Department of Computer Science San Jose State University.

Spotlighting Decentralized P2P File Sharing Archie Kuo and Ethan Le Department of Computer Science San Jose State University.
Principles of Immunology Overview of Adaptive Immunity 1/24/06 “Too many people overvalue what they are not and undervalue what they are.” M Forbes.

Principles of Immunology Overview of Adaptive Immunity 1/24/06 “Too many people overvalue what they are not and undervalue what they are.” M Forbes.
A. Frank 1 Internet Resources Discovery (IRD) Peer-to-Peer (P2P) Technology (1) Thanks to Carmit Valit and Olga Gamayunov.

A. Frank 1 Internet Resources Discovery (IRD) Peer-to-Peer (P2P) Technology (1) Thanks to Carmit Valit and Olga Gamayunov.
1 Client-Server versus P2P  Client-server Computing  Purpose, definition, characteristics  Relationship to the GRID  Research issues  P2P Computing.

1 Client-Server versus P2P  Client-server Computing  Purpose, definition, characteristics  Relationship to the GRID  Research issues  P2P Computing.
Improving Data Access in P2P Systems Karl Aberer and Magdalena Punceva Swiss Federal Institute of Technology Manfred Hauswirth and Roman Schmidt Technical.

Improving Data Access in P2P Systems Karl Aberer and Magdalena Punceva Swiss Federal Institute of Technology Manfred Hauswirth and Roman Schmidt Technical.
Specific Immune Defense. Antigens Antibody-generator, Non-self, Large molecules Properties: ◦1. Immunogenicity ◦2. Reactivity Antigenic determinant or.

Specific Immune Defense. Antigens Antibody-generator, Non-self, Large molecules Properties: ◦1. Immunogenicity ◦2. Reactivity Antigenic determinant or.
Immunity : The Immune system plays a role in combating infection, creating inflammation (& consequently heart disease), controlling (or not) cancer and.

Immunity : The Immune system plays a role in combating infection, creating inflammation (& consequently heart disease), controlling (or not) cancer and.
By : Anas Assiri.  Introduction  fraud detection  Immune system  Artificial immune system (AIS)  AISFD  Clonal selection.

By : Anas Assiri.  Introduction  fraud detection  Immune system  Artificial immune system (AIS)  AISFD  Clonal selection.
Introduction to Peer-to-Peer Networks. What is a P2P network Uses the vast resource of the machines at the edge of the Internet to build a network that.

Introduction to Peer-to-Peer Networks. What is a P2P network Uses the vast resource of the machines at the edge of the Internet to build a network that.

Similar presentations

Ads by Google