Metaheuristic can be considered as a "master strategy that guides and modifies other heuristics to produce solutions. Generally metaheuristic is used for solving problem in ad hoc networks.
Hear about data science techniques used by the data science team at Pivotal Software to create predictive maintenance applications for connected vehicles
Google driverless car technical seminar report (.docx)gautham p
Google Driverless Car is the latest technology or innovation that is going to hit the market in the coming years.
This report is especially for mechanical engineering students.
Hear about data science techniques used by the data science team at Pivotal Software to create predictive maintenance applications for connected vehicles
Google driverless car technical seminar report (.docx)gautham p
Google Driverless Car is the latest technology or innovation that is going to hit the market in the coming years.
This report is especially for mechanical engineering students.
With increasing vehicle size in the luxury segment and crunching parking space, traffic congestion is increasingly becoming an alarming concern in almost all major cities around the world. Burning about a million barrels of the world’s oil every day, and considering cities are turning urban without a well-planned, convenience-driven retreat from the cars, these problems will only worsen.
Smart Parking systems is one of the latest disruptive technologies that help address this problem by generating real time contextual information about the available parking spaces particular geographical area to accommodate vehicles low-cost sensors, mobility-enabled automated payment systems, real-time data collection, Smart Parking systems is designed to aid drivers to precisely find a spot.
What’s more, Smart Parking also minimizes emissions from vehicle in urban centers when deployed as a system by decreasing the dependency of people; unnecessarily circling the blocks trying to identify parking space. Apart from this green cause, by employing a host of technologies such as M2M telematics, Smart Parking helps resolve one of the biggest problems when driving around in urban areas – which is illegal parking and identifying free parking space.
Vehicle To Vehicle Communication SystemMonaco Motors
Vehicle to vehicle communication system enables vehicles to communicate with each other. Watch our slide to know the benefits of this system and what type of information we can share through it. Also keep track of some potential benefits of this system and the natural evolution in automotive safety development.
SMC takes a state machine stored in a .sm file and generates a State pattern in fourteen programming languages (C, C++, C#, [incr Tcl], Groovy, Java, Lua, Objective-C, Perl, PHP, Python, Ruby, Scala, VB.net). Includes: default transitions, transition args, transition guards, push/pop transitions and Entry/Exit actions.
See all details on http://smc.sourceforge.net/.
Hill Climbing Algorithm in Artificial IntelligenceBharat Bhushan
Hill Climbing Algorithm in Artificial Intelligence
Hill climbing algorithm is a local search algorithm which continuously moves in the direction of increasing elevation/value to find the peak of the mountain or best solution to the problem. It terminates when it reaches a peak value where no neighbor has a higher value.
Hill climbing algorithm is a technique which is used for optimizing the mathematical problems. One of the widely discussed examples of Hill climbing algorithm is Traveling-salesman Problem in which we need to minimize the distance traveled by the salesman.
It is also called greedy local search as it only looks to its good immediate neighbor state and not beyond that.
A node of hill climbing algorithm has two components which are state and value.
Hill Climbing is mostly used when a good heuristic is available.
In this algorithm, we don't need to maintain and handle the search tree or graph as it only keeps a single current state.
Features of Hill Climbing:
Following are some main features of Hill Climbing Algorithm:
Generate and Test variant: Hill Climbing is the variant of Generate and Test method. The Generate and Test method produce feedback which helps to decide which direction to move in the search space.
Greedy approach: Hill-climbing algorithm search moves in the direction which optimizes the cost.
No backtracking: It does not backtrack the search space, as it does not remember the previous states.
State-space Diagram for Hill Climbing:
The state-space landscape is a graphical representation of the hill-climbing algorithm which is showing a graph between various states of algorithm and Objective function/Cost.
On Y-axis we have taken the function which can be an objective function or cost function, and state-space on the x-axis. If the function on Y-axis is cost then, the goal of search is to find the global minimum and local minimum. If the function of Y-axis is Objective function, then the goal of the search is to find the global maximum and local maximum.
With increasing vehicle size in the luxury segment and crunching parking space, traffic congestion is increasingly becoming an alarming concern in almost all major cities around the world. Burning about a million barrels of the world’s oil every day, and considering cities are turning urban without a well-planned, convenience-driven retreat from the cars, these problems will only worsen.
Smart Parking systems is one of the latest disruptive technologies that help address this problem by generating real time contextual information about the available parking spaces particular geographical area to accommodate vehicles low-cost sensors, mobility-enabled automated payment systems, real-time data collection, Smart Parking systems is designed to aid drivers to precisely find a spot.
What’s more, Smart Parking also minimizes emissions from vehicle in urban centers when deployed as a system by decreasing the dependency of people; unnecessarily circling the blocks trying to identify parking space. Apart from this green cause, by employing a host of technologies such as M2M telematics, Smart Parking helps resolve one of the biggest problems when driving around in urban areas – which is illegal parking and identifying free parking space.
Vehicle To Vehicle Communication SystemMonaco Motors
Vehicle to vehicle communication system enables vehicles to communicate with each other. Watch our slide to know the benefits of this system and what type of information we can share through it. Also keep track of some potential benefits of this system and the natural evolution in automotive safety development.
SMC takes a state machine stored in a .sm file and generates a State pattern in fourteen programming languages (C, C++, C#, [incr Tcl], Groovy, Java, Lua, Objective-C, Perl, PHP, Python, Ruby, Scala, VB.net). Includes: default transitions, transition args, transition guards, push/pop transitions and Entry/Exit actions.
See all details on http://smc.sourceforge.net/.
Hill Climbing Algorithm in Artificial IntelligenceBharat Bhushan
Hill Climbing Algorithm in Artificial Intelligence
Hill climbing algorithm is a local search algorithm which continuously moves in the direction of increasing elevation/value to find the peak of the mountain or best solution to the problem. It terminates when it reaches a peak value where no neighbor has a higher value.
Hill climbing algorithm is a technique which is used for optimizing the mathematical problems. One of the widely discussed examples of Hill climbing algorithm is Traveling-salesman Problem in which we need to minimize the distance traveled by the salesman.
It is also called greedy local search as it only looks to its good immediate neighbor state and not beyond that.
A node of hill climbing algorithm has two components which are state and value.
Hill Climbing is mostly used when a good heuristic is available.
In this algorithm, we don't need to maintain and handle the search tree or graph as it only keeps a single current state.
Features of Hill Climbing:
Following are some main features of Hill Climbing Algorithm:
Generate and Test variant: Hill Climbing is the variant of Generate and Test method. The Generate and Test method produce feedback which helps to decide which direction to move in the search space.
Greedy approach: Hill-climbing algorithm search moves in the direction which optimizes the cost.
No backtracking: It does not backtrack the search space, as it does not remember the previous states.
State-space Diagram for Hill Climbing:
The state-space landscape is a graphical representation of the hill-climbing algorithm which is showing a graph between various states of algorithm and Objective function/Cost.
On Y-axis we have taken the function which can be an objective function or cost function, and state-space on the x-axis. If the function on Y-axis is cost then, the goal of search is to find the global minimum and local minimum. If the function of Y-axis is Objective function, then the goal of the search is to find the global maximum and local maximum.
Advancement in VANET Routing by Optimize the Centrality with ANT Colony Approachijceronline
In a wireless ad hoc network, an opportunistic routing strategy is a strategy where there is no predefined rule for choosing the next node to destination (as it is the case in conventional schemes such as OLSR, DSR or even Geo-Routing). A popular example of opportunistic routing is the “delay tolerant” forwarding to VANET network when a direct path to destination does not exist. Conventional routing in this case would just “drop” the packet. With opportunistic routing, a node acts upon the available information, In this thesis optimize the routing by centrality information then refine by ant colony metaheuristics. In this method validate our approach on different parameter like overhead, throughput.
Ant colony optimization based routing algorithm in various wireless sensor ne...Editor Jacotech
Wireless Sensor Network has several issues and challenges due to limited battery backup, limited computation capability, and limited computation capability. These issues and challenges must be taken care while designing the algorithms to increase the Network lifetime of WSN. Routing, the act of moving information across an internet world from a source to a destination is one of the vital issue associated with Wireless Sensor Network. The Ant Colony Optimization (ACO) algorithm is a probabilistic technique for solving computational problems that can be used to find optimal paths through graphs. The short route will be increasingly enhanced therefore become more attractive. The foraging behavior and optimal route finding capability of ants can be the inspiration for ACO based algorithm in WSN. The nature of ants is to wander randomly in search of food from their nest. While moving, ants lay down a pheromone trail on the ground. This chemical pheromone has the ability to evaporate with the time. Ants have the ability to smell pheromone. When selecting their path, they tend to select, probably the paths that has strong pheromone concentrations. As soon as an ant finds a food source, carries some of it back to the nest. While returning, the quantity of chemical pheromone that an ant lay down on the ground may depend on the quantity and quality of the food. The pheromone trails will lead other ants towards the food source. The path which has the strongest pheromone concentration is followed by the ant which is the shortest paths between their nest and food source. This paper surveys the ACO based routing in various Networking domains like Wireless Sensor Networks and Mobile Ad Hoc Networks.
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Cooperative Black Hole Attack Prevention by Particle Swarm Optimization with ...IJARIIT
MANET (Mobile Ad Hoc Network) is a type of ad hoc network that can change locations and configure
itself, because of moving of nodes. As MANETs are mobile in nature, they use wireless connections to connect various
networks without infrastructure or any centralized administration. Open medium, dynamic topology, distributed
cooperation are the characteristics of MANET and hence ad hoc networks are open to different types of security
attacks. A Grey hole is a node that selectively drops and forwards data packets after advertises itself as having the
shortest path to the destination node in response to a route request message. Our mechanism helps to protect the
network by detecting and reacting to malicious activities of any node. The results enable us to minimize the attacks on
integrated MANET-Internet communication efficiently. Simulation will be carried out by using network simulator
tool so as to address the problem of detection & prevention of grey hole attack in mobile ad-hoc network. In this thesis
uses Particle swarm optimization(PSO).Which monitors by changing its values because of adhoc nature ,if node
converge then it change its value infinite and prevent the node to send packet.
Mitigation of sink hole attack in manet using acoIJARIIT
MANET (Mobile ad hoc network) is the emerging and most demanding technology of wireless network. Because of
self-deliberate property, the network points behave as router or source and the nodes keep moving freely in the network area.
MANET plays a significant role in connection less infrastructure. Securing a network is the fundamental issue in MANET for
securing the susceptible information from hackers. MANET has different attacks that are routing protocol attacks. The sink
hole is known as the severe one from all the attacks in MANET. It generally attracts the neighbour’s nodes towards itself and
transmits the bogus or fake routing path. This attack decreases the network lifetime and increases the network overhead by
boosting energy consumption and later destroys the network. In the proposed work, the routing protocol is being optimized by
utilizing ACO (Ant Colony Optimization) with NN (Neural Network) for achieving enhanced performance as compared to
existing work. Different parameters, namely, Bit error rate, throughput, an end to end delay and energy consumption are used
for calculating the performance of the proposed wok in MANET or to check the effect of Sinkhole attack. The environment
created by simulating the work has 50 to 100 nodes. The width and height of the network is 1000 nodes
Efficient Routing Protocol in the Mobile Ad-hoc Network (MANET) by using Gene...IOSR Journals
An Ad hoc network is a collection of wireless mobile hosts forming a temporary network without the
aid of any centralized administration or standard support services. MANET can be defined using unstable
network infrastructure, self-organizing network topology and independent node mobility. This becomes
obtainable due to their routing techniques; in other terms, routing is a backbone for MANET. However, due to
network load routing performance of MANET is degraded thus, some optimization on network routing strategy
is required.
In this paper, we introduce a new technique by using the concept of Genetic algorithm (GA) with
AODV Protocol to make routing decision in computer network.
The goal of this paper is to find the optimal path between the source and destination nodes and increased the
QoS and Throughput. We implemented and compare this a new technique with the traditional AODV, and we
shows that the new technique is better performance than the traditional AODV.
Back-Bone Assisted HOP Greedy Routing for VANETijsrd.com
Using advanced wireless local area network technologies, vehicular ad hoc networks (VANETs) have become viable and valuable for their wide variety of novel applications, such as road safety, multimedia content sharing, commerce on wheels, etc., currently, geographic routing protocols are widely adopted for VANETs as they do not require route construction and route maintenance phases. Again, with connectivity awareness, they perform well in terms of reliable delivery. Further, in the case of sparse and void regions, frequent use of the recovery strategy elevates hop count. Some geographic routing protocols adopt the minimum weighted algorithm based on distance or connectivity to select intermediate intersections. However, the shortest path or the path with higher connectivity may include numerous intermediate intersections. As a result, these protocols yield routing paths with higher hop count. In this paper, we propose a hop greedy routing scheme that yields a routing path with the minimum number of intermediate intersection nodes while taking connectivity into consideration. Moreover, we introduce back-bone nodes that play a key role in providing connectivity status around an intersection. Apart from this, by tracking the movement of source as well as destination, the back-bone nodes enable a packet to be forwarded in the changed direction. Simulation results signify the benefits of the proposed routing strategy in terms of high packet delivery ratio and shorter end-to-end delay.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Simulation Based Analysis of Bee Swarm Inspired Hybrid Routing Protocol Param...Editor IJCATR
Vehicular Ad-hoc Networks (VANET's) are basically emanated from Mobile Ad hoc networks (MANET's) in which
vehicles act as the mobile nodes, the nodes are vehicles on the road and mobility of these vehicles are very high. The main objective of
VANET is to enhance the safety and amenity of road users. It provides intelligent transportation services in vehicles with the
automobile equipment to communicate and co-ordinates with other vehicles in the same network that informs the driver’s about the
road status, unseen obstacles, internet access and other necessary travel service information’s. The evaluation of vehicular ad hoc
networks applications in based on the simulations. A Realistic Mobility model is a basic component for VANET simulation that
ensures that conclusion drawn from simulation experiments will carry through to real deployments. This paper attempts to evaluate the
performance of a Bee swarm inspired Hybrid routing protocol for vehicular ad hoc network, that protocol should be tested under a
realistic condition including, representative data traffic models, and the realistic movement of the mobile nodes which are the vehicles.
In VANET the simulation of Realistic mobility model has been generated using SUMO and MOVE software and network simulation
has been performed using NS2 simulator, we conducted performance evaluation based on certain metric parameters such as packet
delivery ratio, end-to-end delay and normalized overhead ratio.
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Similar to Various Metaheuristic algorithms For Securing VANET (20)
Real World Testbeds Emulation for Mobile Ad-hoc NetworksKishan Patel
It focuses on creating an original computer environment, which can be time-consuming and difficult to achieve, and also it is very costly because of its ability to maintain a closer connection to the authenticity object.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
2. OUTLINE
INTODUCTION OF VANET
SECURITY IN VANET
ADVANTAGES AND DISADVANTAGES
METAHEURISTIC
METAHEURISTIC TECHNIQUES
PROPERTIES OF METAHEURISTIC
WHY METAHEURISTIC…?
METAHEURISTIC ALGORITHMS
SURVEY OF VARIOUS METAHEURISTIC
CONCLUSION
REFERENCES
3. INTRODUCTION OF VANET
Vehicular ad hoc network (VANET) uses cars as mobile nodes in
a MANET to create a mobile network.
Vehicular ad hoc networks are a subgroup of mobile ad hoc
networks (MANETs).
Cars fall out of the signal range and drop out of the network,
other cars can join, by connecting vehicles to one another form a
wireless network called “Vehicular Ad Hoc Network.
Due to high mobility, frequent changes in topology such
characteristics of this network that make routing decisions more
challenging.
3
4. SECURITY IN VANET
The nature of VANETs could lead to malicious attacks.
o Predictable movement of nodes.
o High mobility of victim/attacker.
Adversaries could break the system.
o Data sinkholes (black hole).
o Gray hole
o Feed false information.
o Flood the system.
Security measures must be taken to avoid malicious attacks on the
system
4
5. ADVANTAGES AND DISADVANTAGES
Advantages
Public Safety.
Traffic Management.
Traffic Coordination and Assistance.
Traveller Information Support.
Comfort.
Air pollution emission measurement and reduction.
Disadvantages
Flooding in route discovery initial phase.
Wasted band width.
Delay.
Increasing network congestion.
External sources for destination location.
5
6. METAHEURISTIC
Heuristic means to find or to discover by trial and error. And meta
means higher level and metaheuristics generally perform better
than simple heuristics.
The word "metaheuristic” can be considered as a "master strategy
that guides and modifies other heuristics to produce solutions.
Generally metaheuristic is used for solving problem in ad hoc
networks.
7. METAHUERISTIC TECHNIQUES
There are two techniques:
Online metaheuristic approach and Offline metaheuristic
approach.
The main difference between them is the moment when they are
applied for solving problem.
1. Online metaheuristic approaches are used for decision making
or solving the problem during run time.
2. Offline metaheuristic approaches are useful when there is no
requirement for system to adapt change during runtime.
8. PROPERTIES OF METAHEURISTIC
1. Search process is influenced by Metaheuristic approch.
2. The main purpose of the search process is to find near to
optimal solutions.
3. It range from simple local search procedures to complex
processes.
4. They are non-deterministic.
5. They are not problem-specific
9. WHY METAHEURISTIC….?
1. Metaheuristics are used for solving the security and routing
problems in ad hoc networks.
2. Security problem in the network may be due to selfish and
malicious node. Metaheuristic approach can be used for
overcoming the problem of node misbehaving in ad hoc
networks.
3. For route optimization e.g selecting the shortest and quality
route from source to destination in the ad hoc networks.
4. Metaheuristic approach is also used for solving the supply
chain problems.
5. Metaheuristic approach is important for generating optimum set
of test data in software testing.
10. METAHEURISTIC ALGORITHMS
Metaheuristic is a procedure for finding or select a lower
heuristic and provide a good solution to an optimization and
security problem with limited computation
capacity. Metaheuristics may make few assumptions about the
problems in ad hoc networks so it is used for a variety of
problems.
As shown in next figure classification of metaheuristics. It
includes Ant colony optimization (ACO), Tabu search (TS),
scatter search(SS), Variable neighborhood search (VNS), Guided
local search (GLS), iterated local search (ILS), simulated
annealing (SA), evolutionary algorithms (EC) etc.
11.
12. CONT…
Ant colony optimization (ACO):
It is a population-based metaheuristic for the solution to the
difficult combinatorial optimization problems. The inspiring
source of ACO is behavior of real ants. This behavior empowers
ants to find shortest paths from food sources to their nest. While
walking from food sources to the nest, ants dregs a substance
called pheromone on the ground. This behavior is the basis for a
cooperative interaction for emerging of shortest paths.
Tabu search :
It is a heuristic procedure for solving optimization problems.
Tabu search has obtained optimal and near to optimal solutions to
a wide variety of practical problems in varied applications such
as scheduling, character recognition.
13. CONT…
Scatter Search (SS):
It is designed to operate on a set of points, which is called
reference points. It also captures information which is not present
in reference points. It takes advantage of auxiliary heuristic
methods.
Variable neighbourhood search (VNS):
It is based on simple principal . It starts from feasible solution X
and from a predefined set of steps, chooses a random solution
within the neighborhood of X and move there if the solution is
better.
14. CONT…
Simulated annealing :
It is a probabilistic metaheuristic for the global optimization
problem for finding a good approximation to the global optimum
for a given function in a large search space.
Evolutionary computing:
Evolution is a process in which functioning deals with
chromosomes. The process takes place during the reproduction
stage. For e.g mutation and recombination. It is combination of
genetic algorithms, evolution strategies, evolutionary
programming and genetic programming.
16. 16
Title Mechanism /
Algorithm
Purpose Methodology
TARA: Trusted Ant Colony Multi
Agent Based Routing Algorithm
for Mobile Ad-Hoc Networks.
TARA: Trusted Ant Colony Multi
Agent Based Routing Algorithm
To avoid trust value propagation. To
minimize the number of messages
been exchanged. To find the best
route for delivery.
Trust value of each node is directly
aped to the route and no need to
propagate the trust values like other
trusted protocols.
Trust Based QOS Protocol(TBQP)
using Metaheuristic
Genetic Algorithm for Optimizing
and
Securing MANET
Trust Based QOS Protocol (TBQP)
Using Meta-heuristic Genetic
Algorithm.
To provide QOS by selecting the
fittest shortest route among the
number of routes to provide
optimization. Acquaintance
And Authentication of packets for
routing in network.
Intriguing a trust based packet
delivering scheme for detecting and
isolating the malignant nodes using
the routing layer information. A
trust weigh is maintained and a
node is remunerated by decreasing
or increasing the trust weigh value.
If the trust weigh falls below a trust
threshold, node is marked as
malicious node.
Performance analysis of optimized
Trust AODV using ant Algorithms
Ant colony optimization To sustain security against the dos
attacks.
At agents can move freely to find
destination it will update positive
pheromone to the routing table. The
pheromone is deposited if node is
trusted.
17. 17
Title Mechanism /
Algorithm
Purpose Methodology
Ant Colony and Load Balancing
Optimizations for AODV Routing
Protocol
Multi-Route AODV Ant routing
(MRAA)
Load balancing( LBMRAA)
To reduce
the routing overhead, buffer
overflow, end-to-end delay and
increase the performance
Data packets are balanced
over discovered paths and energy
consumption is distributed across
many nodes through network.
Secure Ant-Based Routing Protocol
for Wireless Sensor Network.
Secure Ant-Based Routing
Protocol(SARP)
To provide Route security in
network.
It uses two paths for data
forwarding to overcome the
problem of node failure and to
increase the efficiency of overall
network.
MANET link Performance using Ant
Colony
Optimization and Particle Swarm
Optimization
Algorithms.
Ant colony optimization and
Particle swarm optimization.
Finds the best solution over the
particle’s position and velocity with
the cost and minimum. End-to-end
delay.
Ant Colony Optimization
(ACO) algorithm uses mobile agents
as ants to discover feasible and best
path in a network and PSO finds the
best solution over the particle’s
position and velocity with the
objective of cost and minimum End-
to-end delay.
AntTrust: A Novel Ant Routing
Protocol forWireless Ad-hoc
Network Based on
Trust Between Nodes.
Ant Trust Routing Protocol To increase the security of route.
And malicious manipulations
of data packets.
AntTrust is located precisely in the
context of the security of routing. It
also facilitates malicious
manipulations of data packets.
18. 18
Title Mechanism /
Algorithm
Purpose Methodology
Mitigating Routing Misbehavior
Using Ant-Tabu-Based
Routing Algorithm for Wireless
Ad-Hoc Networks
Ant-Tabu-Based
Routing Algorithm(ATBR)
To mitigate the selfish nodes
problems and provide reliability in
a dynamic network.
To increase successful delivery
rate (SDR).
To decrease routing overhead
(RO).
To prevent from dos attacks to
enhance network performance.
Swarm intelligence based
approach for sinkhole attack
detection in wireless sensor
networks.
Proposed an Ant Colony
Optimization Attack Detection
(ACO-AD) algorithm and Ant
Colony Optimization Boolean
Expression Evolver Sign
Generation (ABXES).
To detect a sinkhole attack and to
identify an intruder in a wireless
sensor networks.
ACO-AD algorithm for detection of
sink hole attack, and ABXES
algorithm for distributing keys
among the group of node. And for
identification of the anomalous
connections without generation of
false positives and minimization of
storage in the sensor nodes.
Network Security Using Self
Organized Multi
Agent Swarms.
Self organized multi agent swarms
(SOMAS)
To provides a novel computer
network security management
framework.
SOMAS developmental aspects can
be improved in the approach,
methodology, an experimental
design and evaluation. Testing is
required for different agent rules
with scenario size
19. Title Mechanism /
Algorithm
Purpose Methodology
Sustaining Security in MANET:
Biometric Stationed Authentication
Protocol (BSAP) Inculcating Meta-
Heuristic Genetic Algorithm.
Biometric Stationed Authentication
Protocol (BSAP)
To sustain security in MANET
from DOS attacks.
Biometric cryptographic key is
produced to enhance security of
MANET. Hence data is protected
by applying three levels of security
by our prospective approach which
develops trust between various
nodes of ad-hoc network.
A memetic algorithm for enhancing
the robustness of scale-free
networks against malicious attacks.
Memetic algorithm To enhance the robustness of
networks against malicious attacks.
By using Hill climbing, Simulated
annealing, Smart rewiring and
memetic algorithms for solving the
problem of optimizing and security
in network .
A trust based clustering with ant
colony routing in Vanet.
Proposed a new Mobility-aware
Ant Colony Optimization Routing
(MAR-DYMO).
To decrease the routing overhead
by establishing creating trust in
between the nodes in vanet.
Trust in the routing algorithms in
terms of routing overhead. 20
random values are obtained for
different number of VANET nodes
and clusters and the average value
is presented.
A Survey on Anomaly Detection in
Network Intrusion
Detection System Using Particle
Swarm Optimization
Based Machine Learning
Techniques.
Particle swarm optimization
combined with Machine Learning
techniques for Anomaly Detection
in Network Intrusion Detection
System.
To enhance the performance of
intrusion detection system.
Recently developed IDS with single
techniques is insufficient against
increasing threats in the network.
So hybridization of techniques are
used to satisfy the increasing
demand of intelligent Intrusion
Detection System (IDS).
20. CONCLUSION
The metaheuristic approach is currently attracting considerable
interest for research community to meet the rising need.
The important advantage of metaheurisic approach is to provide
provably optimal solutions but they have potential to produce
good solutions in short amounts of time.
In this paper we present a survey of various metaheuristic
algorithms and its functioning to overcome security and
optimization problem to improve the performance of ad hoc
networks.
21. CONT….
In order to overcome the shortcoming of existing algorithms and
to enhance the robustness of an existing network against
malicious attacks various techniques are hybridized. We conclude
that metaheuristic approach can provide a best solution for
security and optimization problem with limited computation.
22. REFERENCES
[1] Kishan Patel, Rutvij Jhaveri, “Addressing Packet Dropping
Misbehavior using Metaheuristic Approach: A Survey”,
International Conference on Electrical, Electronics, Signals,
Communication and Optimization (IEEE EESCO-2015), Issue
3, pages 1036-1041, 24-25 January 2015.