Ants are very small insects.They are capable to find food even they are complete blind. The ants lives in
their nest and their job is to search food while they get hungry. We are not interested in their living style,
such as how they live, how they sleep. But we are interested in how they search for food, and how they find
the shortest path. The technique for finding the shortest path are now applying in cloud computing. The Ant
Colony approach towards Cloud Computing gives better performance.
32 Ways a Digital Marketing Consultant Can Help Grow Your BusinessBarry Feldman
How can a digital marketing consultant help your business? In this resource we'll count the ways. 24 additional marketing resources are bundled for free.
Comparative Study of Ant Colony Optimization And Gang SchedulingIJTET Journal
Abstract— Ant Colony Optimization (ACO) is a well known and rapidly evolving meta-heuristic technique. All optimization problems have already taken advantage of the ACO technique while countless others are on their way. Ant Colony Optimization (ACO) has been used as an effective algorithm in solving the scheduling problem in grid computing. Whereas gang scheduling is a scheduling algorithm that is used to schedule the parallel systems and schedules related threads or processes to run simultaneously on different processors. The threads that are scheduled are belonging to the same process, but they from different processes in some cases, for example when the processes have a producer-consumer relationship, when all processes come from the same MPI program.
PERFORMANCE ANALYSIS OF ANTHOCNET ROUTING PROTOCOL FOR HYBRID AD HOC NETWORKKhushbooGupta145
Mobile Ad hoc Networks (MANETs) are communication networks which consist of wireless nodes, placed together in an ad hoc manner, i.e. with minimal prior planning. The random node movement unpredictable behavior makes the topology very dynamic in nature. MANETs poses substantially different challenges to routing protocols than more traditional wired networks. The classification of MANETs protocols are Proactive based, Reactive based or Bio-inspired routing protocols. AntHocNet is a bio-inspired routing protocol based on ant colony optimization (ACO) which has many parallels with biology
thus the solutions of biology can also be used to solve the problems of computer networks.
This paper discusses the implementation and performance analysis of the AntHocNet algorithm which is based on the nature-inspired Ant Colony Optimization framework for
routing in mobile MANETs. AntHocNet is an adaptive hybrid algorithm which combines the reactive route setup process with the proactive maintenance process. The reactive route setup is carried out at the start of a communication session or whenever the source of a current session has no more routing information available for the destination. The proactive route maintenance is run for the entire duration of the session. Its aim is to keep
information about existing routes up to date and explore new routes. During simulation, the performance of AntHocNet is compared with DSR and AODV routing protocols.
32 Ways a Digital Marketing Consultant Can Help Grow Your BusinessBarry Feldman
How can a digital marketing consultant help your business? In this resource we'll count the ways. 24 additional marketing resources are bundled for free.
Comparative Study of Ant Colony Optimization And Gang SchedulingIJTET Journal
Abstract— Ant Colony Optimization (ACO) is a well known and rapidly evolving meta-heuristic technique. All optimization problems have already taken advantage of the ACO technique while countless others are on their way. Ant Colony Optimization (ACO) has been used as an effective algorithm in solving the scheduling problem in grid computing. Whereas gang scheduling is a scheduling algorithm that is used to schedule the parallel systems and schedules related threads or processes to run simultaneously on different processors. The threads that are scheduled are belonging to the same process, but they from different processes in some cases, for example when the processes have a producer-consumer relationship, when all processes come from the same MPI program.
PERFORMANCE ANALYSIS OF ANTHOCNET ROUTING PROTOCOL FOR HYBRID AD HOC NETWORKKhushbooGupta145
Mobile Ad hoc Networks (MANETs) are communication networks which consist of wireless nodes, placed together in an ad hoc manner, i.e. with minimal prior planning. The random node movement unpredictable behavior makes the topology very dynamic in nature. MANETs poses substantially different challenges to routing protocols than more traditional wired networks. The classification of MANETs protocols are Proactive based, Reactive based or Bio-inspired routing protocols. AntHocNet is a bio-inspired routing protocol based on ant colony optimization (ACO) which has many parallels with biology
thus the solutions of biology can also be used to solve the problems of computer networks.
This paper discusses the implementation and performance analysis of the AntHocNet algorithm which is based on the nature-inspired Ant Colony Optimization framework for
routing in mobile MANETs. AntHocNet is an adaptive hybrid algorithm which combines the reactive route setup process with the proactive maintenance process. The reactive route setup is carried out at the start of a communication session or whenever the source of a current session has no more routing information available for the destination. The proactive route maintenance is run for the entire duration of the session. Its aim is to keep
information about existing routes up to date and explore new routes. During simulation, the performance of AntHocNet is compared with DSR and AODV routing protocols.
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.
MHead - Self-Organized Flocking in Mobile Robot SwarmsSamet Baykul
DATE: 2019.05
- Engineering design
- CAD by creating complex geometry via SolidWorks
- Arduino programming
- Control systems design
- Physics simulation in robotics by using Webots
- Prototyping by using a 3d printer
- Test setups
- Selection of mechatronics components
- Building an effective robot algorithms by using C++
- Literature survey for recent academic studies
PROJECT:
Goal: In order to have a more natural flocking behavior implementation, the data acquisition of each individual robot has to be kept as low as possible. On the other hand, in order to achieve a successful flocking behavior and to solve a more complex task, the number of individuals within a swarm robots must be increased. In other words, flocking size should be as much as possible. Consequently, there is need to develop a new swarm of robot platform that can demonstrate the solution of complex problems with large amounts of limited information. In order to achieve this goal, each individual robot should be designed in a minimalistic way and produced as cheaply as possible.
Tremendous usage of internet has made huge data on the network, without compromising on the
performance of network the end-users must obtain best service. As cloud provides different services on
leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should
not compromise on performance of the cloud, The performance of the cloud can be improved by having
excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which
a cloud can be partitioned and a study of different algorithm with comparative study to balance the
dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which
algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the
partition are in Idle state
"Ant colony algorithm suffers drawbacks such as slow convergence and easy to trap into local optimum, therefore the path planning for mobile robot based on an improved ant colony optimization algorithm is proposed. The workspace for mobile robot is established with grid method. A hybrid ant colony which is composed of common ants and exploratory ants is utilized to avoid trapping into local optimum. To increase the convergence speed, the pheromone update mechanism is improved by enhancing the sensitivity of the ants to the optimal path with reserving the elite ants. The optimal collision free path can be planned rapidly in the workspace with multiple obstacles. Simulation and experiment results show that the algorithm is practical and effective. P. Hema Suganthi | Mrs. K. Subha ""Path Navigation in ACO Using Mobile Robot"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21642.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/21642/path-navigation-in-aco-using-mobile-robot/p-hema-suganthi"
Proposing a New Job Scheduling Algorithm in Grid Environment Using a Combinat...Editor IJCATR
Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources.
The purpose of job scheduling in grid environment is to achieve high system throughput and minimize the execution time of applications.
The complexity of scheduling problem increases with the size of the grid and becomes highly difficult to solve effectively.
To obtain a good and efficient method to solve scheduling problems in grid, a new area of research is implemented. In this paper, a job
scheduling algorithm is proposed to assign jobs to available resources in grid environment. The proposed algorithm is based on Ant
Colony Optimization (ACO) algorithm. This algorithm is combined with one of the best scheduling algorithm, Suffrage. This paper uses
the result of Suffrage in proposed ACO algorithm. The main contribution of this work is to minimize the makespan of a given set of
jobs. The experimental results show that the proposed algorithm can lead to significant performance in grid environment.
The optimization of running queries in relational databases using ant colony ...ijdms
The issue of optimizing queries is a cost-sensitive
process and with respect to the number of associat
ed
tables in a query, its number of permutations grows
exponentially. On one hand, in comparison with oth
er
operators in relational database, join operator is
the most difficult and complicated one in terms of
optimization for reducing its runtime. Accordingly,
various algorithms have so far been proposed to so
lve
this problem. On the other hand, the success of any
database management system (DBMS) means
exploiting the query model. In the current paper, t
he heuristic ant algorithm has been proposed to sol
ve this
problem and improve the runtime of join operation.
Experiments and observed results reveal the efficie
ncy
of this algorithm compared to its similar algorithm
s.
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMijcseit
Tremendous usage of internet has made huge data on the network, without compromising on the
performance of network the end-users must obtain best service. As cloud provides different services on
leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should
not compromise on performance of the cloud, The performance of the cloud can be improved by having
excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which
a cloud can be partitioned and a study of different algorithm with comparative study to balance the
dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which
algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the
partition are in Idle state
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMijcseit
Tremendous usage of internet has made huge data on the network, without compromising on the
performance of network the end-users must obtain best service. As cloud provides different services on
leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should
not compromise on performance of the cloud, The performance of the cloud can be improved by having
excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which
a cloud can be partitioned and a study of different algorithm with comparative study to balance the
dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which
algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the
partition are in Idle state
Robot operating system based autonomous navigation platform with human robot ...TELKOMNIKA JOURNAL
In emerging technologies, indoor service robots are playing a vital role for people who are physically challenged and visually impaired. The service robots are efficient and beneficial for people to overcome the challenges faced during their regular chores. This paper proposes the implementation of autonomous navigation platforms with human-robot interaction which can be used in service robots to avoid the difficulties faced in daily activities. We used the robot operating system (ROS) framework for the implementation of algorithms used in auto navigation, speech processing and recognition, and object detection and recognition. A suitable robot model was designed and tested in the Gazebo environment to evaluate the algorithms. The confusion matrix that was created from 125 different cases points to the decent correctness of the model.
Hybrid aco iwd optimization algorithm for minimizing weighted flowtime in clo...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Hybrid aco iwd optimization algorithm for minimizing weighted flowtime in clo...eSAT Journals
Abstract Scientists and engineers conduct several experiments by executing the same coding against the various input data, which is achieved by the Parameter Sweep Experiments (PSEs). This may finally results in too many jobs with high computational requirements. Therefore the distributed environments, particularly clouds, are used in-order to fulfill these demands. Since it is an NP-complete problem the job scheduling is much changeling. Now the proposed work is determined by the Cloud scheduler based on the bio-inspired techniques, since it works well in approximating problems with little input. But in existing proposals the job priority is ignored; which in turn it is the important aspect in PSEs because it accelerates the result of the PSE and visualization of scientific clouds. The weighted flow time is minimized with the help of the cloud scheduler based on Ant Colony Optimization (ACO). All matching recourses of the job requirements and the routing information are defined by the Intelligent Water Drops (IWDs) in order to reach the recourses. Among all matching resources of the job the Ant colony optimization is determined as the best resources. The main aim of this approach is to converge to the optimal scheduler faster, minimize the make span of the job, improve load balancing. Keywords: Ant Colony Optimization, Intelligent Water Drops, Parameter Sweep Experiments, Weighted Flowtime.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
MHead - Self-Organized Flocking in Mobile Robot SwarmsSamet Baykul
DATE: 2019.05
- Engineering design
- CAD by creating complex geometry via SolidWorks
- Arduino programming
- Control systems design
- Physics simulation in robotics by using Webots
- Prototyping by using a 3d printer
- Test setups
- Selection of mechatronics components
- Building an effective robot algorithms by using C++
- Literature survey for recent academic studies
PROJECT:
Goal: In order to have a more natural flocking behavior implementation, the data acquisition of each individual robot has to be kept as low as possible. On the other hand, in order to achieve a successful flocking behavior and to solve a more complex task, the number of individuals within a swarm robots must be increased. In other words, flocking size should be as much as possible. Consequently, there is need to develop a new swarm of robot platform that can demonstrate the solution of complex problems with large amounts of limited information. In order to achieve this goal, each individual robot should be designed in a minimalistic way and produced as cheaply as possible.
Tremendous usage of internet has made huge data on the network, without compromising on the
performance of network the end-users must obtain best service. As cloud provides different services on
leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should
not compromise on performance of the cloud, The performance of the cloud can be improved by having
excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which
a cloud can be partitioned and a study of different algorithm with comparative study to balance the
dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which
algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the
partition are in Idle state
"Ant colony algorithm suffers drawbacks such as slow convergence and easy to trap into local optimum, therefore the path planning for mobile robot based on an improved ant colony optimization algorithm is proposed. The workspace for mobile robot is established with grid method. A hybrid ant colony which is composed of common ants and exploratory ants is utilized to avoid trapping into local optimum. To increase the convergence speed, the pheromone update mechanism is improved by enhancing the sensitivity of the ants to the optimal path with reserving the elite ants. The optimal collision free path can be planned rapidly in the workspace with multiple obstacles. Simulation and experiment results show that the algorithm is practical and effective. P. Hema Suganthi | Mrs. K. Subha ""Path Navigation in ACO Using Mobile Robot"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21642.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/21642/path-navigation-in-aco-using-mobile-robot/p-hema-suganthi"
Proposing a New Job Scheduling Algorithm in Grid Environment Using a Combinat...Editor IJCATR
Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources.
The purpose of job scheduling in grid environment is to achieve high system throughput and minimize the execution time of applications.
The complexity of scheduling problem increases with the size of the grid and becomes highly difficult to solve effectively.
To obtain a good and efficient method to solve scheduling problems in grid, a new area of research is implemented. In this paper, a job
scheduling algorithm is proposed to assign jobs to available resources in grid environment. The proposed algorithm is based on Ant
Colony Optimization (ACO) algorithm. This algorithm is combined with one of the best scheduling algorithm, Suffrage. This paper uses
the result of Suffrage in proposed ACO algorithm. The main contribution of this work is to minimize the makespan of a given set of
jobs. The experimental results show that the proposed algorithm can lead to significant performance in grid environment.
The optimization of running queries in relational databases using ant colony ...ijdms
The issue of optimizing queries is a cost-sensitive
process and with respect to the number of associat
ed
tables in a query, its number of permutations grows
exponentially. On one hand, in comparison with oth
er
operators in relational database, join operator is
the most difficult and complicated one in terms of
optimization for reducing its runtime. Accordingly,
various algorithms have so far been proposed to so
lve
this problem. On the other hand, the success of any
database management system (DBMS) means
exploiting the query model. In the current paper, t
he heuristic ant algorithm has been proposed to sol
ve this
problem and improve the runtime of join operation.
Experiments and observed results reveal the efficie
ncy
of this algorithm compared to its similar algorithm
s.
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMijcseit
Tremendous usage of internet has made huge data on the network, without compromising on the
performance of network the end-users must obtain best service. As cloud provides different services on
leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should
not compromise on performance of the cloud, The performance of the cloud can be improved by having
excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which
a cloud can be partitioned and a study of different algorithm with comparative study to balance the
dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which
algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the
partition are in Idle state
CLOUD COMPUTING – PARTITIONING ALGORITHM AND LOAD BALANCING ALGORITHMijcseit
Tremendous usage of internet has made huge data on the network, without compromising on the
performance of network the end-users must obtain best service. As cloud provides different services on
leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should
not compromise on performance of the cloud, The performance of the cloud can be improved by having
excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which
a cloud can be partitioned and a study of different algorithm with comparative study to balance the
dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which
algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the
partition are in Idle state
Robot operating system based autonomous navigation platform with human robot ...TELKOMNIKA JOURNAL
In emerging technologies, indoor service robots are playing a vital role for people who are physically challenged and visually impaired. The service robots are efficient and beneficial for people to overcome the challenges faced during their regular chores. This paper proposes the implementation of autonomous navigation platforms with human-robot interaction which can be used in service robots to avoid the difficulties faced in daily activities. We used the robot operating system (ROS) framework for the implementation of algorithms used in auto navigation, speech processing and recognition, and object detection and recognition. A suitable robot model was designed and tested in the Gazebo environment to evaluate the algorithms. The confusion matrix that was created from 125 different cases points to the decent correctness of the model.
Hybrid aco iwd optimization algorithm for minimizing weighted flowtime in clo...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Hybrid aco iwd optimization algorithm for minimizing weighted flowtime in clo...eSAT Journals
Abstract Scientists and engineers conduct several experiments by executing the same coding against the various input data, which is achieved by the Parameter Sweep Experiments (PSEs). This may finally results in too many jobs with high computational requirements. Therefore the distributed environments, particularly clouds, are used in-order to fulfill these demands. Since it is an NP-complete problem the job scheduling is much changeling. Now the proposed work is determined by the Cloud scheduler based on the bio-inspired techniques, since it works well in approximating problems with little input. But in existing proposals the job priority is ignored; which in turn it is the important aspect in PSEs because it accelerates the result of the PSE and visualization of scientific clouds. The weighted flow time is minimized with the help of the cloud scheduler based on Ant Colony Optimization (ACO). All matching recourses of the job requirements and the routing information are defined by the Intelligent Water Drops (IWDs) in order to reach the recourses. Among all matching resources of the job the Ant colony optimization is determined as the best resources. The main aim of this approach is to converge to the optimal scheduler faster, minimize the make span of the job, improve load balancing. Keywords: Ant Colony Optimization, Intelligent Water Drops, Parameter Sweep Experiments, Weighted Flowtime.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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Load balancing using ant colony in cloud computing
1. International Journal of Information Technology Convergence and Services (IJITCS) Vol.3, No.5, October 2013
LOAD BALANCING USING ANT COLONY IN CLOUD
COMPUTING
Ranjan Kumar1 and G Sahoo2
1
Department of Computer Science & Engineering, C.I.T Tatisilwai, Ranchi, India
2
Department of Information Technology, B.I.T Mesra, Ranchi, India
ABSTRACT
Ants are very small insects.They are capable to find food even they are complete blind. The ants lives in
their nest and their job is to search food while they get hungry. We are not interested in their living style,
such as how they live, how they sleep. But we are interested in how they search for food, and how they find
the shortest path. The technique for finding the shortest path are now applying in cloud computing. The Ant
Colony approach towards Cloud Computing gives better performance.
KEYWORDS
Ant Colony, Cloud Computing, Pheromone, Web Servers, Job Schedulers.
1. INTRODUCTION
Cloud Computing is very hot topic in IT field. Many researches are going on Cloud Computing.
This is basically “on-demand” service. It means whenever we need for some applications or some
software, we demand for it and we immediately get it. We have to pay only that we use. This is
the main motto of cloud computing. Our desired application will present in our computer in few
moment. Cloud Computing has basically two parts, the First part is of Client Side and the second
part is of Server Side. The Client Side requests to the Servers and the Server responds to the
Clients. The request from the client firstly goes to the Master Processor of the Server Side. The
Master Processor are attached to many Slave Processors, the master processor sends that request
to any one of the Slave Processor which have free space. All Processors are busy in their assigned
job and non of the Processor get Idle. The process of assigning job from Master processor to the
Slave processor and after completion the job, then returning from the Slave processor to the
Master processor is just like Ant takes their food and return to their nest. The real ants left out
pheromone while travelling. A pheromone is a chemical used for communication. Now we are
moving from real ants to artificial ants. The artificial ants have some special characteristics which
is not found in real ants, such as they are not completely blind, they have some memory called
tabu. Now the artificial ants are used in cloud computing. The cloud computing is composed of
three service models, five essential characteristics, and four deployment models.
The three service models are as follows.
Software as a Service (SaaA).
Platform as a Service (PaaS).
Infrastructure as a Service (IaaS).
The five essential charactersistics are as follows.
DOI:10.5121/ijitcs.2013.3501
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2. International Journal of Information Technology Convergence and Services (IJITCS) Vol.3, No.5, October 2013
On-demand self service
Ubiquitous network access
Resource pooling
Rapid elasticity
Location independence
The four deployment models are as follows.
Private Cloud
Public Cloud
Community Cloud
Hybrid Cloud
Organization of this paper is as follows: Related work is discussed in section II. Proposed Ant
Colony is discussed in section III. Experimental setup is discussed in section IV. Result is
discussed in section V. And section VI gives conclusion.
2. RELATED WORK
Marco Dorigo and Luca Maria Gambardella [1] described about real and artificial ant. An
artificial ant colony, that was capable of solving Travelling Salesman Problem. Real ants are
capable of finding the shortest path from food source to the nest without using visual cues. Also,
they are capable of adapting to changes in the environment, for example finding a new shortest
path once the old one is no longer feasible due to a new obstacle. Zehua Zhang and Xuejie Zhang
[2] described about Load balancing mechanism based on Ant Colony. They described about the
function of Load balancing and how to distribute the workload in a cloud and to realize a high
ratio of user satisfication. They described the two characteristic of Complex Network and these
two characteristics are considered for the move of the ants in the work, since the ants move more
quickly towards that region where more resources found. They also described about Underload
and Overload of load balancing methods. Sarayut Nonsiri and Siriporn Supratid [3] discussed
about the ACO that allows fast near optimal solutions to be found. It is useful in industrial
environments where computational resources and time are limited. Patomporn Premprayoon and
Paramote Wardkein [4] discussed about the topological communication network design. They
discussed about the backbone network and the Local Area Network (LAN), they give the formula
of Total number of possible links in a single design. They discussed about the Reliability
calculation using backtracking algorithm for correctly calculate the system reliability. They also
discussed about the basic principle of ant colony and State Transition Rule in Ant Colony
Optimization technique and Global updating rule. Zenon Chaczko, Venkatesh Mahadevan,
Shahrzad Aslanzadeh and Christopher Mcdermid [7] discussed about the availability and load
balancing in cloud computing. They discussed about the static and dynamic algorithms and the
load balancing techniques to obtain measurable improvements in resource utilization and
availability of cloud computing environment.
3. PROPOSED ANT COLONY
Marco Dorigo, first introduced the Ant System (AS) in his Ph.D thesis in 1992. Now it is one of
the best optimization technique, which finds the shortest path. The deposition of pheromone and
the ant move is approximately at the same speed and at the same rate. And that pheromone
attracts another ants to move on same path. So, more ants move on same path have higher
concentration of pheromone and the evaporation rate is very low on shorter path, that’s why ants
chooses the shorter path.
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3. International Journal of Information Technology Convergence and Services (IJITCS) Vol.3, No.5, October 2013
The probability with which ant k currently at stage i choosing to go to stage j .
k
p ij ( t )
[ ij ( t )] [ ij ( t )] [A p ]
l J ik
[ ij ( t )] [ ij ( t )]
Where,
ij = Pheromone trail
ij = Heuristic value
= Parameter which determines the relative influence of the pheromone trail.
= Parameter which determines the relative influence of the pheromone trail.
Ap = Amount of pheromone
The proposed Algorithm is defined as follow.
Step 1 : Randomly select a Job Schedular.
Step 2 : Job Schedular Schedules job to different web services.
While Job is not schedule to web services
Repeat steps 3 & 4.
Step 3: Job checks its surrounding area for availability of web services with
Probability,
k
p ij ( t )
[ ij ( t )] [ ij ( t )] [A p ]
l J ik
[ ij ( t )] [ ij ( t )]
Step 4 : if
Web server is available
Then
Acquire web server
Else
Go to step 3
Step 5 : Return to the Job Schedular.
Step 6 : After completition kill the job.
Step 7 : End
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4. International Journal of Information Technology Convergence and Services (IJITCS) Vol.3, No.5, October 2013
The Web Services have some amount of load at any time, since non of the processor get idle. The
decision point makes ants to realize the Load of different Web Services.
4. EXPERIMENTAL SETUP
To evaluate the performance of Ant Colony, the results were simulated in Window 7 basic (64bit), i3 processor, 370 M processor, 2.40 GHz of speed with memory of 3 GB and language used
C++. There are 10 job sechedulers and 44 different web services. The job secheduler sechedules
the different jobs to the different web services. The number of ants in this simulation varies from
1 to 1000. These ants deposit some amount of pheromone in there move.
5. RESULT
We have experimented by taking different amount of number of ants. The amount of pheromone
varies between 0 to 1. The table I shows the number of ants and the amount of pheromone
deposited.
Table I
No. of Ants
Amount of Pheromone
Upto 10
0.01-0.10
Upto 20
0.10-0.15
Upto 30
0.15-0.17
Upto 50
0.17-0.19
Upto 90
0.20-0.30
Upto 100
0.35-0.45
Upto 200
0.50-0.65
Upto 300
0.65-0.75
Upto 600
0.75-0.85
Upto 1000
0.85-1.00
From the table I, we see that as the number of ants increases, the amount of pheromone also
increases, Since most of the ants uses the same path. The figure I shows the graph of Table I.
No. of Ants------>
1500
Ant Colony
1000
500
Ant Colony
0
Pheromone Trail-------->
Figure I. Ant Colony in respect of Ants & Pheromone Trail
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5. International Journal of Information Technology Convergence and Services (IJITCS) Vol.3, No.5, October 2013
3. C ONCLUSIONS
In this paper, we have proposed a method for load balancing. In which we emphasis on deposition
of pheromone. Here we see that when a node with minimum load is attracted by most of the ants
gives result to the maximum deposition of pheromone.
REFERENCES
[1]
Marco Dorigo, Luca Maria Gambardella “ Ant Colonies for the travelling Salesman Problem”,
TR/IRIDIA, Vol.3, University Libre de Bruxelles, Belgium, 1996.
[2] Zehua Zhang and Xuejie Zhang “A Load Balancing Mechanism Based on Ant Colony and Complex
Network Theory in Open Cloud Computing Federation”, International Conference on Industrial
Mechatronics and Automation, pp-240-243,2010.
[3] Sarayut Nonsiri and Siriporn Supratid “Modifying Ant Colony Optimization”, IEEE Conference on
Soft Computing in Industrial Application, Muroran, Japan. Pp. 95-100. 2008.
[4] Patomporn Premprayoon and Paramote Wardkein “Topological Communication Network Design
Using Ant Colony Optimization”, Department of telecommunication Engineering, King Mongkut’s
Institute of Technology Landkrabang Bankok, Thailand. Pp. 1147-1151.
[5] Kun Li, Gaochao Xu, Guangyu Zhao, Yushuang Dong and Dan Wang “Cloud Task scheduling based
on Load Balancing Ant Colony Optimization”, Jilin University, ChangChun, China, Sixth Annual
ChinaGrid Conference. pp. 03-09. 2011.
[6] Shu-Ching Wang, Kuo-Qin Yan, Wen-Pin Liao and Shun-Sheng Wang “ Towards a Load Balancing
in a Three-Level Cloud Computing Network”, Chaoyang University of Technology, Taiwan, R.O.C.
pp. 108-113. 2010.
[7] Zenon Chaczko, Venkatesh Mahadevan, Shahrzad Aslanzadeh and Christopher Mcdermid “
Availability and Load Balancing in Cloud Computing”, International Conference on Computer and
Software Modelling, IPCSIT, vol. 14, Singapore. pp. 134-140. 2011.
[8] Ratan Mishra and Anant Jaiswal “ Ant Colony Optimization: A Solution of Load balancing in Cloud”
International Journal of Web and Semantic Technology. Vol. 3, No. 2. pp. 33-50. April 2012.
[9] Kumar Nishant, Pratik Sharma, Vishal Krishna, Chhavi Gupta, Kuwar Pratap Singh, Nitin and Ravi
Rastogi “ Load Balancing of Nodes in Cloud Using Ant Colony Optimization”, Department of CSE
and ICT, Jaypee University of Information Technology, 14th International Conference on Modelling
and Simulation. pp.03-08. 2012.
[10] “Swarm Intelligence from Natural to Artificial System” by Marco Dorigo and Eric Bonabeau, 1999.
[11] “Cloud Computing and SOA Convergence in Your Enterprise” by David s. Linthicum, 2011.
[12] “Cloud Computing Web Based Application” by Michael Miller, 2012.
Authors
Ranjan Kumar received M.Tech degree in Computer Science from B.I.T Mesra, Ranchi.
He has one year teaching experience. His research interests include cloud computing,
Algorithm and compiler.
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