Parallel LTL Model Checking CS 586. The Capacity Problem Capacity = memory states*stateSize Increase capacity by - Increasing memory - Decreasing states.

Slides:



Advertisements
Similar presentations
Artificial Bee Colony Algorithm
Advertisements

Artificiel Bee Colony (ABC) Algorithme Isfahan University of Technology Fall Elham Seifossadat Faegheh Javadi.
Adopt Algorithm for Distributed Constraint Optimization
(Chapter 5) Deleting Objects
COS 461 Fall 1997 Routing COS 461 Fall 1997 Typical Structure.
PROTOCOL VERIFICATION & PROTOCOL VALIDATION. Protocol Verification Communication Protocols should be checked for correctness, robustness and performance,
Bee Research By Ms. Kuykendall’s Class Honeybees and Honey Honeybees make honey so they have food to eat.
F exam 2 F learning in a natural environment F special case... flower learning F odor learning in the proboscis extension reflex F summary PART 4: BEHAVIORAL.
CS 484. Discrete Optimization Problems A discrete optimization problem can be expressed as (S, f) S is the set of all feasible solutions f is the cost.
Honeybee Communications: Dancing Bees. Dance Communication - Introduction Kinds of Dances – Round Dance – Wagtail Dance – Sickle Dance – Where to Live.
CS 267: Automated Verification Lecture 10: Nested Depth First Search, Counter- Example Generation Revisited, Bit-State Hashing, On-The-Fly Model Checking.
Swarm Intelligence (sarat chand) (naresh Kumar) (veeranjaneyulu) (kalyan raghu)‏
The Hive! (…and various colony activities) February 28, 2014.
Artificial Bee Colony Algorithm
Save the Gulf (stream) Functional Goal: Minimize oil leaks Sub-goals – Performance: Maximize area covered. – Fault-tolerance How: Search, recruit, and.
Nature’s Algorithms David C. Uhrig Tiffany Sharrard CS 477R – Fall 2007 Dr. George Bebis.
1 PHA*:Performing A* in Unknown Physical Environments Ariel Felner Bar-Ilan University. Joint work with Roni Stern and Sarit Kraus.
Informed Search CSE 473 University of Washington.
CS 584. Discrete Optimization Problems A discrete optimization problem can be expressed as (S, f) S is the set of all feasible solutions f is the cost.
A rtificial B ee C olony. Dancing aea for A Dancing area for B Unloading nectar from A Unloading nectar from B ES EF OB SB RF ER OB ER ES RF EF Behaviour.
Monte Carlo Analysis of Security Protocols: Needham-Schroeder Revisited Radu Grosu SUNY at Stony Brook Joint work with Xiaowan Huang, Scott Smolka, & Ping.
Monte Carlo Model Checking Scott Smolka SUNY at Stony Brook Joint work with Radu Grosu Main source of support: ARO – David Hislop.
Metaheuristics The idea: search the solution space directly. No math models, only a set of algorithmic steps, iterative method. Find a feasible solution.
Elements of the Heuristic Approach
ALL ABOUT POLLINATORS  Madelyn Morris, M.S. in Education.
Population-based metaheuristics Nature-inspired Initialize a population A new population of solutions is generated Integrate the new population into the.
FORS 8450 Advanced Forest Planning Lecture 19 Ant Colony Optimization.
Distributed Network Intrusion Detection An Immunological Approach Steven Hofmeyr Stephanie Forrest Patrik D’haeseleer Dept. of Computer Science University.
Distributed Systems 15. Multiagent systems and swarms Simon Razniewski Faculty of Computer Science Free University of Bozen-Bolzano A.Y. 2014/2015.
The Hive is Hungry: Exploring Bee Colony Search and Foraging Behavior through Simulation Peter Bailis, Peter Lifland Harvard Robobees 11 Dec 2009.
 C. C. Hung, H. Ijaz, E. Jung, and B.-C. Kuo # School of Computing and Software Engineering Southern Polytechnic State University, Marietta, Georgia USA.
V.C.E. Biology Unit 2 Animal Behaviour. What is behaviour? Individual behaviours are those related to the movement of an animal or its physiology. Such.
Genetic Algorithms and Ant Colony Optimisation
Distributed Constraint Optimization Michal Jakob Agent Technology Center, Dept. of Computer Science and Engineering, FEE, Czech Technical University A4M33MAS.
CSCI-455/552 Introduction to High Performance Computing Lecture 18.
Wishnu Prasetya Model Checking with SPIN A Bit More about SPIN.
By: Megan Smith.  What are the different types of a honey bee?  What is the job of a worker bee?  What is the job of a drone bee?
A Framework for Elastic Execution of Existing MPI Programs Aarthi Raveendran Graduate Student Department Of CSE 1.
Kavita Singh CS-A What is Swarm Intelligence (SI)? “The emergent collective intelligence of groups of simple agents.”
Dancing Bees Heather Mahaney September 26 th, 2002.
Introduction CS 3358 Data Structures. What is Computer Science? Computer Science is the study of algorithms, including their  Formal and mathematical.
Security Mechanisms for Distributed Computing Systems A9ID1007, Xu Ling Kobayashi Laboratory GSIS, TOHOKU UNIVERSITY 2011/12/15 1.
Honeybee learning and memory. Honeybee brain AL Moth AL.
Biology 441: 9/17/07 Last time  Types of questions (Proximate vs. Ultimate)  Behavioral research methods Today  Behavioral methods cont’d  Crickets.
Quantitative Model Checking Radu Grosu SUNY at Stony Brook Joint work with Scott A. Smolka.
Distributed Algorithms for Multi-Robot Observation of Multiple Moving Targets Lynne E. Parker Autonomous Robots, 2002 Yousuf Ahmad Distributed Information.
Parallel External Directed Model Checking with Linear I/O Shahid Jabbar Stefan Edelkamp Computer Science Department University of Dortmund, Dortmund, Germany.
Technical Seminar Presentation Presented By:- Prasanna Kumar Misra(EI ) Under the guidance of Ms. Suchilipi Nepak Presented By Prasanna.
CS 584. Discrete Optimization Problems A discrete optimization problem can be expressed as (S, f) S is the set of all feasible solutions f is the cost.
Internet-Based TSP Computation with Javelin++ Michael Neary & Peter Cappello Computer Science, UCSB.
Biologically Inspired Computation Ant Colony Optimisation.
BUSY BUZZY BEES By Kim Scott. A sample bee hive. There are approximately 3000 bees in here!
Topic1:Swarm Intelligence 李长河，计算机学院
Bees on the tree of life Bees: 100 million years old Flowers: 160 million years old Hymenoptera (social insects) beesants wasps socialsolitary bumblebees.
Foraging behaviors Variability in wing color in Catocala sp. Development of search images increases effective foraging behavior Stable vs constant conditioning.
Introduction Beehive is a routing algorithm with emphasis On wireless ad-hoc mobile networks and Energy awareness. It is Completely Distributed and does.
The Honeybee Dance By: Kaila Bishop 14 June 2011 Biology 3541.
Honey Bee Foraging Dances
Scientific Research Group in Egypt (SRGE)
From: The biological significance of color constancy: An agent-based model with bees foraging from flowers under varied illumination Journal of Vision.
Apollo Weize Sun Feb.17th, 2017.
Social Learning: The Importance of Copying Others
CS 584 Lecture7 Assignment -- Due Now! Paper Review is due next week.
Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014
PDSA Cycle Plan Do Study Act Step 4 : Act Step 1 : Plan Step 2 : Do
The Honeybee Dance By: Kaila Bishop 14 June 2011 Biology 3541.
Artificial Bee Colony Algorithm
Walk-Around Survey Individually:
Communication in Bees Dr. Arnab Ganguli Assistant Professor and Head
Presentation transcript:

Parallel LTL Model Checking CS 586

The Capacity Problem Capacity = memory states*stateSize Increase capacity by - Increasing memory - Decreasing states - Decreasing state size

Double DFS in Parallel Memory available in one machine Memory needed to store visited states

DDFS Search order A B C If the dfs2 from A visits C first, then the dfs2 from B will not visit C and will not detect a cycle. Solutions?

Solution Ideas Use a different algorithm. Schedule the dfs2 searches Use different bits to mark dfs2 visits ______ ?

One Idea Forget about proving correctness. Each search process is random. Coordinate efforts to find cycles. Coordination scheme should be.. Decentralized Fault-tolerant Better than no coordination at all

Forager Allocation Problem Given: several foraging sites with varying quality the current needs of the hive a pool of foragers Allocate the foragers to: maximize the collection of needed resources Without central control.

Scouts locate patches

Scouts multicast their findings Scout performs a waggle dance which is observed by unemployed foragers. Duration and intensity of the dance describe the quality of the patch.

Workers visit patches. A worker will observe a dance and leave for a patch. Returns, unloads and dances. May visit patch again.

Adaptation Apis Mellifera Bee forager Search flight pattern Flower patch Pollen Waggle dance BEE (bee-based error explorer) Search agent Random walk Accept state Property Violation Multicast

Decentralized Cooperative Search A B C Launch n random searches. When one finds an accept state, advertize its location. Listen to and possibly ignore advertizements.

BEE Search controller BEE distribute problem

BEE Search controller multicast an accept state

BEE Search controller more multicasts report an error

BEE Search controller search continues…

BEE Search controller search terminated

Experimental Environment Classroom laboratory workstations Lowest priority level 8 MB of RAM per machine Compare with isolated parallel random walks to measure advantage of coordination.

Speedup-SS7

Speedup-11peterson

Too Much Communication SS 7 11 Peterson

ACCEPT STATE FORAGING time to receive cycle advertisement recruit to cycle foraging abandon accept state foraging WATER COLLECTING water in hive recruiting to water collecting (waggle dance) abandoning of water collecting water seeking by receiver bees time to find an unloader evaporative cooling Negative Feedback

Feedback: Privacy Policy Feedback
Do Not Sell My Personal Information
About project: SlidePlayer Terms of Service

© 2025 SlidePlayer.com. Inc. All rights reserved.