This document discusses using graph theory to analyze network topologies. It begins by defining network topology as a graph model that can represent systems like communication networks. Challenges in network design include creating optimized configurations for performance and cost. Graph theory concepts like vertices, edges, isomorphism, and spanning trees are introduced. The document presents an example applying these concepts to analyze the topology of a telecommunication network for an oil and gas system. Graph matrices and algorithms for defining network topologies are also discussed.
Hex-Cell is an interconnection network that has attractive features like the embedding capability of topological structures; such as; bus, ring, tree and mesh topologies. In this paper, we present two algorithms for embedding bus and ring topologies onto Hex-Cell interconnection network. We use three metrics to evaluate our proposed algorithms: dilation, congestion, and expansion. Our evaluation results
show that the congestion of our two proposed algorithms is equal to one; and the dilation is equal to 2d-1 for the first algorithm and 1 for the second.
Analysis of Hill Road Network Structure in Developing CountriesIJRTEMJOURNAL
The purpose of this paper is to identify the critical road links and intersections in a road
network which have a great influence on the road network. A framework of road network structure
measurement model is proposed. The node importance number and the link importance number are introduced
in this model to define road network structure. Using this model, the critical components of the road network
can be identified. Then, necessary interventions in a road network can be designed to improve its structure
either adding a new link/s or upgrading the properties of the existing link/s or node/s (e.g. geometry, safety,
capacity). The road network of the hill town of Tansen in Nepal is analyzed by using this model. The network
structure measurement method proposed in this paper can be generalized to hill road network in developing
countries
In the VLSI physical design, Floorplanning is the very crucial step as it optimizes the chip. The goal of
floorplanning is to find a floorplan such that no module overlaps with other, optimize the interconnection between
the modules, optimize the area of the floorplan and minimize the dead space. In this Paper, Simulated Annealing (SA)
algorithm has been employed to shrink dead space to optimize area and interconnect of VLSI floorplanning problem.
Sequence pair representation is employed to perturb the solution. The outcomes received after the application of SA
on different benchmark files are compared with the outcomes of different algorithms on same benchmark files and
the comparison suggests that the SA gives the better result. SA is effective and promising in VLSI floorplan design.
Matlab simulation results show that our approach can give better results and satisfy the fixed-outline and nonoverlapping
constraints while optimizing circuit performance.
The world has many natural systems that are so complex to be understood easily. This creates a need to have simple
principles or systems that capture the complexity of the world. The simple systems make it easier for many people to
understand the world by representing the complex world in a more straightforward way (Stefan, 2003). Many objects
and projects are seen to be a network of processes or substances. Graphs and networks have been used widely in
different projects for different reasons by project managers mostly. There are techniques such as critical path analysis
that make use of graphs and networks and are applied by project managers and all the staff involved in projects. These
methods are used to ensure smooth planning and control of projects. However, the techniques have to be applied
correctly to achieve the desired objective. This paper looks at the impact of graphs and networks in minimizing the costs
of a project or product. From this research, it can be inferred that the techniques such as critical path method, that make
use of graphs and networks, play a significant role in determining and hence reducing the product cost. This is done by
making the right decisions regarding the resources and time most appropriate for a project. The paper shows clearly
how these techniques are applied in a project to determine project duration and hence minimize the cost.
Hex-Cell is an interconnection network that has attractive features like the embedding capability of topological structures; such as; bus, ring, tree and mesh topologies. In this paper, we present two algorithms for embedding bus and ring topologies onto Hex-Cell interconnection network. We use three metrics to evaluate our proposed algorithms: dilation, congestion, and expansion. Our evaluation results
show that the congestion of our two proposed algorithms is equal to one; and the dilation is equal to 2d-1 for the first algorithm and 1 for the second.
Analysis of Hill Road Network Structure in Developing CountriesIJRTEMJOURNAL
The purpose of this paper is to identify the critical road links and intersections in a road
network which have a great influence on the road network. A framework of road network structure
measurement model is proposed. The node importance number and the link importance number are introduced
in this model to define road network structure. Using this model, the critical components of the road network
can be identified. Then, necessary interventions in a road network can be designed to improve its structure
either adding a new link/s or upgrading the properties of the existing link/s or node/s (e.g. geometry, safety,
capacity). The road network of the hill town of Tansen in Nepal is analyzed by using this model. The network
structure measurement method proposed in this paper can be generalized to hill road network in developing
countries
In the VLSI physical design, Floorplanning is the very crucial step as it optimizes the chip. The goal of
floorplanning is to find a floorplan such that no module overlaps with other, optimize the interconnection between
the modules, optimize the area of the floorplan and minimize the dead space. In this Paper, Simulated Annealing (SA)
algorithm has been employed to shrink dead space to optimize area and interconnect of VLSI floorplanning problem.
Sequence pair representation is employed to perturb the solution. The outcomes received after the application of SA
on different benchmark files are compared with the outcomes of different algorithms on same benchmark files and
the comparison suggests that the SA gives the better result. SA is effective and promising in VLSI floorplan design.
Matlab simulation results show that our approach can give better results and satisfy the fixed-outline and nonoverlapping
constraints while optimizing circuit performance.
The world has many natural systems that are so complex to be understood easily. This creates a need to have simple
principles or systems that capture the complexity of the world. The simple systems make it easier for many people to
understand the world by representing the complex world in a more straightforward way (Stefan, 2003). Many objects
and projects are seen to be a network of processes or substances. Graphs and networks have been used widely in
different projects for different reasons by project managers mostly. There are techniques such as critical path analysis
that make use of graphs and networks and are applied by project managers and all the staff involved in projects. These
methods are used to ensure smooth planning and control of projects. However, the techniques have to be applied
correctly to achieve the desired objective. This paper looks at the impact of graphs and networks in minimizing the costs
of a project or product. From this research, it can be inferred that the techniques such as critical path method, that make
use of graphs and networks, play a significant role in determining and hence reducing the product cost. This is done by
making the right decisions regarding the resources and time most appropriate for a project. The paper shows clearly
how these techniques are applied in a project to determine project duration and hence minimize the cost.
New implementations for concurrent computing applications of 3D networks using corresponding nano and field-emission controlled-switching components are introduced. The developed implementations are performed within 3D lattice-based systems to perform the required concurrent computing. The introduced 3D systems utilize recent findings in field-emission and nano applications to implement the function of the basic 3D lattice networks using nano controlled-switching. This includes ternary lattice computing via carbon nanotubes and carbon field-emission techniques. The presented realization of lattice networks can be important for several reasons including the reduction of power consumption, which is an important specification for the system design in several future and emerging technologies, and in achieving high performance and reliability realizations. The introduced implementations for 3D lattice computations, with 2D lattice networks as a special case, are also important for the design within modern technologies that require optimal design specifications of high speed, high regularity and ease-of-manufacturability, such as in highly-reliable error-correcting signal processing applications.
A Dependent Set Based Approach for Large Graph AnalysisEditor IJCATR
Now a day’s social or computer networks produced graphs of thousands of nodes & millions of edges. Such Large graphs
are used to store and represent information. As it is a complex data structure it requires extra processing. Partitioning or clustering
methods are used to decompose a large graph. In this paper dependent set based graph partitioning approach is proposed which
decomposes a large graph into sub graphs. It creates uniform partitions with very few edge cuts. It also prevents the loss of
information. The work also focuses on an approach that handles dynamic updation in a large graph and represents a large graph in
abstract form.
An experimental evaluation of similarity-based and embedding-based link predi...IJDKP
The task of inferring missing links or predicting future ones in a graph based on its current structure
is referred to as link prediction. Link prediction methods that are based on pairwise node similarity
are well-established approaches in the literature and show good prediction performance in many realworld graphs though they are heuristic. On the other hand, graph embedding approaches learn lowdimensional representation of nodes in graph and are capable of capturing inherent graph features,
and thus support the subsequent link prediction task in graph. This paper studies a selection of
methods from both categories on several benchmark (homogeneous) graphs with different properties
from various domains. Beyond the intra and inter category comparison of the performances of the
methods, our aim is also to uncover interesting connections between Graph Neural Network(GNN)-
based methods and heuristic ones as a means to alleviate the black-box well-known limitation.
Short Term Load Forecasting Using Bootstrap Aggregating Based Ensemble Artifi...Kashif Mehmood
Short Term Load Forecasting (STLF) can predict load from several minutes to week plays
the vital role to address challenges such as optimal generation, economic scheduling, dispatching and
contingency analysis. This paper uses Multi-Layer Perceptron (MLP) Artificial Neural Network
(ANN) technique to perform STFL but long training time and convergence issues caused by bias,
variance and less generalization ability, unable this algorithm to accurately predict future loads. This
issue can be resolved by various methods of Bootstraps Aggregating (Bagging) (like disjoint
partitions, small bags, replica small bags and disjoint bags) which helps in reducing variance and
increasing generalization ability of ANN. Moreover, it results in reducing error in the learning process
of ANN. Disjoint partition proves to be the most accurate Bagging method and combining outputs of
this method by taking mean improves the overall performance. This method of combining several
predictors known as Ensemble Artificial Neural Network (EANN) outperform the ANN and Bagging
method by further increasing the generalization ability and STLF accuracy.
Dual Tree Complex Wavelet Transform, Probabilistic Neural Network and Fuzzy C...IJAEMSJORNAL
The venture suggests an Adhoc technique of MRI brain image classification and image segmentation tactic. It is a programmed structure for phase classification using learning mechanism and to sense the Brain Tumor through spatial fuzzy clustering methods for bio medical applications. Automated classification and recognition of tumors in diverse MRI images is enthused for the high precision when dealing with human life. Our proposal employs a segmentation technique, Spatial Fuzzy Clustering Algorithm, for segmenting MRI images to diagnose the Brain Tumor in its earlier phase for scrutinizing the anatomical makeup. The Artificial Neural Network (ANN) will be exploited to categorize the pretentious tumor part in the brain. Dual Tree-CWT decomposition scheme is utilized for texture scrutiny of an image. Probabilistic Neural Network (PNN)-Radial Basis Function (RBF) will be engaged to execute an automated Brain Tumor classification. The preprocessing steps were operated in two phases: feature mining by means of classification via PNN-RBF network. The functioning of the classifier was assessed with the training performance and classification accuracies.
A Modified Diagonal Mesh Shuffle Exchange Interconnection Network IJECEIAES
Interconnection network is an important part of the digital system. The interconnection mainly describes the topology of the network along with the routing algorithm and flow control mechanism. The topology of the network plays an important role on the performance of the system. Mesh interconnection network was the simplest topology, but has the limited bisection bandwidth on the other hand torus and diagonal mesh was having long links. The Modified diagonal mesh network tried to replace the torodial links but was having more average path length so in proposed topology we have tried to improve the average distance using shuffle exchange network over the boundary node. In this paper, we propose the architecture of Modified Diagonal Mesh Shuffle Exchange Interconnection Network. This Modified Diagonal Mesh Shuffle Exchange Interconnection network have been compared with four popular topologies that are simple 2D Mesh, 2D Torus, Diagonal Mesh and Modified Diagonal Mesh Interconnection Network on the four traffic patterns such as Bit Complement traffic, Neighbor traffic, Tornado traffic and Uniform traffic are used for comparisonand performance analysis. We have performed the analysis with a 5% and 10% of hotspot on the Uniform Traffic. The simulation results shows that the proposed topology is performed better on bit complement traffic and can also handle the other traffic up to certain level.
New implementations for concurrent computing applications of 3D networks using corresponding nano and field-emission controlled-switching components are introduced. The developed implementations are performed within 3D lattice-based systems to perform the required concurrent computing. The introduced 3D systems utilize recent findings in field-emission and nano applications to implement the function of the basic 3D lattice networks using nano controlled-switching. This includes ternary lattice computing via carbon nanotubes and carbon field-emission techniques. The presented realization of lattice networks can be important for several reasons including the reduction of power consumption, which is an important specification for the system design in several future and emerging technologies, and in achieving high performance and reliability realizations. The introduced implementations for 3D lattice computations, with 2D lattice networks as a special case, are also important for the design within modern technologies that require optimal design specifications of high speed, high regularity and ease-of-manufacturability, such as in highly-reliable error-correcting signal processing applications.
A Dependent Set Based Approach for Large Graph AnalysisEditor IJCATR
Now a day’s social or computer networks produced graphs of thousands of nodes & millions of edges. Such Large graphs
are used to store and represent information. As it is a complex data structure it requires extra processing. Partitioning or clustering
methods are used to decompose a large graph. In this paper dependent set based graph partitioning approach is proposed which
decomposes a large graph into sub graphs. It creates uniform partitions with very few edge cuts. It also prevents the loss of
information. The work also focuses on an approach that handles dynamic updation in a large graph and represents a large graph in
abstract form.
An experimental evaluation of similarity-based and embedding-based link predi...IJDKP
The task of inferring missing links or predicting future ones in a graph based on its current structure
is referred to as link prediction. Link prediction methods that are based on pairwise node similarity
are well-established approaches in the literature and show good prediction performance in many realworld graphs though they are heuristic. On the other hand, graph embedding approaches learn lowdimensional representation of nodes in graph and are capable of capturing inherent graph features,
and thus support the subsequent link prediction task in graph. This paper studies a selection of
methods from both categories on several benchmark (homogeneous) graphs with different properties
from various domains. Beyond the intra and inter category comparison of the performances of the
methods, our aim is also to uncover interesting connections between Graph Neural Network(GNN)-
based methods and heuristic ones as a means to alleviate the black-box well-known limitation.
Short Term Load Forecasting Using Bootstrap Aggregating Based Ensemble Artifi...Kashif Mehmood
Short Term Load Forecasting (STLF) can predict load from several minutes to week plays
the vital role to address challenges such as optimal generation, economic scheduling, dispatching and
contingency analysis. This paper uses Multi-Layer Perceptron (MLP) Artificial Neural Network
(ANN) technique to perform STFL but long training time and convergence issues caused by bias,
variance and less generalization ability, unable this algorithm to accurately predict future loads. This
issue can be resolved by various methods of Bootstraps Aggregating (Bagging) (like disjoint
partitions, small bags, replica small bags and disjoint bags) which helps in reducing variance and
increasing generalization ability of ANN. Moreover, it results in reducing error in the learning process
of ANN. Disjoint partition proves to be the most accurate Bagging method and combining outputs of
this method by taking mean improves the overall performance. This method of combining several
predictors known as Ensemble Artificial Neural Network (EANN) outperform the ANN and Bagging
method by further increasing the generalization ability and STLF accuracy.
Dual Tree Complex Wavelet Transform, Probabilistic Neural Network and Fuzzy C...IJAEMSJORNAL
The venture suggests an Adhoc technique of MRI brain image classification and image segmentation tactic. It is a programmed structure for phase classification using learning mechanism and to sense the Brain Tumor through spatial fuzzy clustering methods for bio medical applications. Automated classification and recognition of tumors in diverse MRI images is enthused for the high precision when dealing with human life. Our proposal employs a segmentation technique, Spatial Fuzzy Clustering Algorithm, for segmenting MRI images to diagnose the Brain Tumor in its earlier phase for scrutinizing the anatomical makeup. The Artificial Neural Network (ANN) will be exploited to categorize the pretentious tumor part in the brain. Dual Tree-CWT decomposition scheme is utilized for texture scrutiny of an image. Probabilistic Neural Network (PNN)-Radial Basis Function (RBF) will be engaged to execute an automated Brain Tumor classification. The preprocessing steps were operated in two phases: feature mining by means of classification via PNN-RBF network. The functioning of the classifier was assessed with the training performance and classification accuracies.
A Modified Diagonal Mesh Shuffle Exchange Interconnection Network IJECEIAES
Interconnection network is an important part of the digital system. The interconnection mainly describes the topology of the network along with the routing algorithm and flow control mechanism. The topology of the network plays an important role on the performance of the system. Mesh interconnection network was the simplest topology, but has the limited bisection bandwidth on the other hand torus and diagonal mesh was having long links. The Modified diagonal mesh network tried to replace the torodial links but was having more average path length so in proposed topology we have tried to improve the average distance using shuffle exchange network over the boundary node. In this paper, we propose the architecture of Modified Diagonal Mesh Shuffle Exchange Interconnection Network. This Modified Diagonal Mesh Shuffle Exchange Interconnection network have been compared with four popular topologies that are simple 2D Mesh, 2D Torus, Diagonal Mesh and Modified Diagonal Mesh Interconnection Network on the four traffic patterns such as Bit Complement traffic, Neighbor traffic, Tornado traffic and Uniform traffic are used for comparisonand performance analysis. We have performed the analysis with a 5% and 10% of hotspot on the Uniform Traffic. The simulation results shows that the proposed topology is performed better on bit complement traffic and can also handle the other traffic up to certain level.
5G Coupler Design for Intelligent Transportation System (ITS) Application IJECEIAES
Aiming to achieve 3-dB coupling, operating in fifth generation (5G) technologies, this paper introduces a new design of tight coupling coupler that will be operated in 5G technologies. Two stubs and two slots have been implemented into the 3-dB coupler design in order to achieve impedance matching between the ports and to give better coupling performances, respectively. Moreover, a study on the stubs’ and slots’ effects towards the S31 of the 3-dB coupler has also been presented in this paper. The proposed coupler is designed on Rogers RO4003C substrate. The simulation results and the analytical study on the stubs and slots implementation show that both stubs and slots affect the performance of the coupling coefficient.
Probability Density Functions of the Packet Length for Computer Networks With...IJCNCJournal
The research on Internet traffic classification and identification, with application on prevention of attacks
and intrusions, increased considerably in the past years. Strategies based on statistical characteristics of
the Internet traffic, that use parameters such as packet length (size) and inter-arrival time and their
probability density functions, are popular. This paper presents a new statistical modeling for packet length,
which shows that it can be modeled using a probability density function that involves a normal or a beta
distribution, according to the traffic generated by the users. The proposed functions has parameters that
depend on the type of traffic and can be used as part of an Internet traffic classification and identification
strategy. The models can be used to compare, simulate and estimate the computer network traffic, as well
as to generate synthetic traffic and estimate the packets processing capacity of Internet routers
Interoperator Dynamic Spectrum Sharing (Analysis, Costs and Implications)CSCJournals
This paper addresses Dynamic Spectrum Sharing (DSS) between two wireless operators. The Universal Mobile Telecommunication System (UMTS) network is used as a case study. The proposed protocol is evaluated under the uniform and non-uniform traffic conditions. The underlying principles of the algorithm can be deployed in the UMTS extension Band (2500MHz-2690MHz) which is yet to be allocated or the re-farmed GSM spectrum (900MHz/1800MHz). The simulation results for the proposed protocol shows that significant spectrum sharing gains can be obtained. However such spectrum efficiency gain need to be carefully balanced with the complexity in terms of latency (delays) and additional overhead it brings to the network. The results show that significant spectrum sharing gain of 4.0 % and 2.0 % can be obtained under uniform and non-uniform traffic conditions
Wireless Mesh Networks Based on MBPSO Algorithm to Improvement Throughput IJECEIAES
Wireless Mesh Networks can be regarded as a type of communication technology in mesh topology in which wireless nodes interconnect with one another. Wireless Mesh Networks depending on the semi-static configuration in different paths among nodes such as PDR, E2E delay and throughput. This study summarized different types of previous heuristic algorithms in order to adapt with proper algorithm that could solve the issue. Therefore, the main objective of this study is to determine the proper methods, approaches or algorithms that should be adapted to improve the throughput. A Modified Binary Particle Swarm Optimization (MBPSO) approach was adapted to improvements the throughput. Finally, the finding shows that throughput increased by 5.79% from the previous study.
Analysis of Hill Road Network Structure in Developing CountriesIJRTEMJOURNAL
The purpose of this paper is to identify the critical road links and intersections in a road
network which have a great influence on the road network. A framework of road network structure
measurement model is proposed. The node importance number and the link importance number are introduced
in this model to define road network structure. Using this model, the critical components of the road network
can be identified. Then, necessary interventions in a road network can be designed to improve its structure
either adding a new link/s or upgrading the properties of the existing link/s or node/s (e.g. geometry, safety,
capacity). The road network of the hill town of Tansen in Nepal is analyzed by using this model. The network
structure measurement method proposed in this paper can be generalized to hill road network in developing
countries.
Reconfigurable intelligent surface passive beamforming enhancement using uns...IJECEIAES
Reconfigurable intelligent surfaces (RIS) is a wireless technology that has the potential to improve cellular communication systems significantly. This paper considers enhancing the RIS beamforming in a RIS-aided multiuser multi-input multi-output (MIMO) system to enhance user throughput in cellular networks. The study offers an unsupervised/deep neural network (U/DNN) that simultaneously optimizes the intelligent surface beamforming with less complexity to overcome the non-convex sum-rate problem difficulty. The numerical outcomes comparing the suggested approach to the near-optimal iterative semi-definite programming strategy indicate that the proposed method retains most performance (more than 95% of optimal throughput value when the number of antennas is 4 and RIS’s elements are 30) while drastically reducing system computing complexity.
A NOVEL ROBUST AND LOW-COMPLEXITY SPACETIME CODES FOR INDUSTRY 4.0 SYSTEMSijwmn
This paper proposes different robust and low-complexity space time codes which provide more reliability for industrial automation. An innovative synchronized uplink system configuration for an Industrial Environment is proposed. Mathematical framework for estimating the channel phase of each Slave Node (SN) is developed. Furthermore, the channel is practically estimated based on an innovative method using
parallel sequence spread spectrum (PSSS) implemented in Universal Software Radio Peripheral (USRP). The proposed space time codes are applied in the uplink of an industrial communication system where the channel is modelled using Quasi Deterministic Radio Channel Generator (Quadriga) which follows a geometry-based stochastic approach. Simulation results exposed that the proposed codes surpass Alamouti
code for Industrial Automation. The bit error rate (BER) performance demonstrates that the achieved coding gain for the proposed codes is higher than Alamouti code leading to more robust communication. Furthermore, a low complexity decoders based on minimum mean squared error (MMSE) and zero forcing (ZF) algorithms are designed at the receiver side. The proposed codes give a predominant execution against the state-of-the-art space time codes for Industry 4.0.
Use of Geographic Information Systems to Build and Management a Geometric Net...ijtsrd
The main goal of this paper is to use the geometric network in the ArcGIS system to build and management the distribution of the electricity network in the College of Engineering at Sudan University of Science and Technology, which includes load distribution control and management, maintenance, new extensions and decision support. The major source data is a 10 cm spatial resolution aerial photograph of the research region, as well as network data obtained in the field, which comprises transformers, supply sub stations, distribution keys and cables from various portions of the electrical network. Different thematic layers, such as building, vegetation and electrical network parts, were created to meet the papers goal. A digital map of the electrical network, including underground cables, was created and the loads for various sectors were estimated to manage maintenance and new extensions and to determine the networks weaknesses. The ArcGIS systems geometric network was proven to be useful and has the potential to be used in electricity network analysis and management the flow directions of electricity power in the network. Sahar I. M. Abd Elrahman "Use of Geographic Information Systems to Build and Management a Geometric Network for Electricity" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49528.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/49528/use-of-geographic-information-systems-to-build-and-management-a-geometric-network-for-electricity/sahar-i-m-abd-elrahman
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After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
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Speakers:
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Charlie Greenberg, Host
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
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Synthesis and performance analysis of network topology using graph theory
1. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
www.iiste.org
Synthesis and Performance Analysis of Network Topology using
Graph Theory
U N Bassey1* K N Bassey2 E N Bassey3
1 Department of Mathematics, University of Ibadan, Ibadan, Nigeria
2 IT/Telecom Infrastructure Projects, Shell Nig. P. O. Box 1259, Warri, Nigeria
3 Department of Chemical Engineering, Akwa Ibom State University, Ikot Akpaden.
P. O. Box 3864, Uyo,Nigeria
*
E-mail of the corresponding author: un.bassey@ui.edu.ng
Abstract
In this work, the peculiarities of network topology have been explored to evolve techniques for the solution of
practical problems which manifest in the form of graphs. They also give insight into the scope and possible
areas for improvement of existing networks and as well the cost implication of incorporating efficiciency factors
into new designs. The shortest route algorithm was applied in defining the topology that maximizes reliability
during resource transmission. The algorithm was implemented using TORA Software on an Excel platform.
Key words: topology, graphs, vertices, nodes, edges, telecommunication network
1. Introduction
1.1 Network Topology as a Graph
Large Scale Systems encountered in the industries constitute a network of related physical units and their
interconnections. The structure of such arrangements is referred to as Network Topology. The practical network
problems that generally conform to a graph structure include the following (Beasley 2004):
• Communication Networks- telecommunication systems, the internet among others
• Oil /Gas and Water Pipelines
• Road and Rail Networks etc.
1.2 Challenges
As the world economy is becoming very competitive there is a great drive to streamline and integrate
information flows between diverse businesses to achieve excellence and improved profitability. This has
therefore brought a tremendous pressure on the information and communication infrastructure leading to
occasional congestion, interferences, and sometimes outright failure. Again since at the moment, the Nigerian
economy derives the largest portion of its revenue from the oil and gas sector, the related infrastructure for the
operation of this sector is of paramount importance with respect to costs efficiencies and systems sustainability.
It may be noted that these systems are often complex by virtue of the large number of units involved and their
interactions. The complexity usually associated with practical
systems may be illustrated as in Figure 1 which shows an IT Integration Network in an oil and gas environment
where infrastructure like VSAT, Routers, Switches, Workstations etc are linked and integrated (Bassey 2001).
So the challenge the Engineer is constantly facing is the task of searching for innovative configurations to ensure
that the systems work together as desired, perform optimally and meet the requirements of the customers at
minimum costs. Consequently, the problems which must be overcome include creating models which are
amenable to computer manipulation, evolving algorithms for their implementation, and evaluating the
information flows for efficiency (Bassey 2000; Bassey et al. 2005). The relationship between network topology
and the associated information flows if explored, offers useful principles for tackling these problems.
1.3 Concepts of Graph
The synthesis and optimisation of practical networks can be greatly enhanced by simulating the network
topologies using graph models. Information flows represent the values of the variables in the models and are the
function of the network topology.
A graph is a set of vertices, V(v1, v2, …vn) -, nodes (N), points, elements, units subsystems, events etc. and a set
of lines joining the nodes called edges, E(e1, e2…en) – communication links, flows, streams etc. (Koryachko et al,
1970). Graphs can be directed (digraphs) or undirected.
1.4 Useful Properties of Graphs
The network structure affects the information flows within the system (i.e. network performance, throughput,
costs, etc). It is therefore necessary to keep the link as simple as possible, and also make connections, which
present the least operating costs. Various properties of graphs are helpful in the study of practical systems, and of
particular importance to a variety of networks are the properties such as Isomorphism, Subgraphs and Tree
Structures.
46
2. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
www.iiste.org
1.4.1 ISOMORPHISM
a1
a 1’
a2
a 2’
Figure 2, Isomorphic Graphs, a1 ≡ a1’ and a2 ≡ a2’
Two graphs G = (V, E) and G’ = (V’, E’) are Isomorphic when there is a one to one correspondence: ie V →V’,
E →E’ such that if (vi , vj ) ∈ V, (vi’, vj’) ∈ V’ then the edge
e = (ei, ej ) ∈ E, e’ = (ei’, ej’) ∈ E’. Figure 2, illustrates Isomorphic Graphs.
Isomorphism forms the basis for representing physical objects (or systems) such as telephone, process, data
communication networks, etc by graph models.
1.4.2 Subgraphs
Subgraphs (Kafarov et al. 1974) consist of subsets of vertices and subsets of edges both belonging to a
complete graph G. Thus for a graph, G = (V, E), G’ = (V’, E’) is the subgraph if : V’ ⊆ U and E’ ⊆ E and the
edges link the vertices V. Figure 3 shows the subgraphs G1 and G2 of the complete graph G.
G
G1
G2
Figure 3. Graph, G and its Subgraphs G1 and G2
To break a graph into its component parts is to split it at its cut vertex since at the cut vertex, there is minimum
interaction between the component parts. Subgraphs are particularly useful in establishing the concept of
decomposing systems into subsystems; links and nodes into segments, etc where each subsystem or segment can
be treated as an independent structure. Examples abound in the industry, for instance in the telecommunication
system, cut vertex may be the Port Interface Modules (PIM) where station transmission /signal cards are
interfaced. In process systems, cut vertex may be the boundaries between the individual units or operations.
1.4.3
Cyclic Graph and Tree Formation
Another property of importance is that every cyclic graph contains at least one loop, and that a graph without
loops is called a tree. The tree that links all the nodes
T2
T1
Figure 4. Cyclic Graph G1 and its Spanning Trees T1 and T2.
without allowing loops is called a spanning tree, (Linnhoff et al., 1979). Figure 4 shows a
tree structure G and its spanning trees T1 and T2 formed by breaking some edges. The spanning tree forms the
basis for the design of minimum cost networks expressed mathematically as follows:
E = V-1.
(1)
where: E , V – number of edges and vertices respectively in the network.
1.4.3
Graph Matrix
The Boolean Matrix is another interesting property of a graph by which information embodied in the graph can
easily be decoded and converted into a machine language (Scheid 1983; Aspen 2000).
Of particular interest in this work, is the Incidence Matrix which is shown in relation to the graph structure, G =
(V, E) in Figure 5.
G
47
3. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
A =
www.iiste.org
0
1
1
0
0
1
0
1
0
0
G
1
1
1
1
0
0
0
1
0
1
0
0
0
1
0
Figure 5. Graph and its Incidence Matrix.
The Incidence Matrix, of a graph, G with V vertices may be defined as │V│ by │V│ matrix , A = aij, whose
entries are chosen such that the entry, aij = 1 if ith vertex is joined by an edge to jth vertex in G, and 0 if
otherwise, (Nozari, et al. 1981). Other criteria (Ahuja 1982; Koryachko 1970; Kafarov 1974) for generating the
graph matrix may also apply. The Adjacency Matrix is a veritable tool in the development of simple solution
approaches to network problems.
2. Application of Graph Theory to Network Problems
The graph concepts allow for the configuration of units into a network and the reconfiguration of the existing
network into minimum cost or more reliable structure (Ahuja 1982; Steward 1987; Lucey 2002). It may also
permit the decomposition of networks into subsystems for better and easier analysis. In practical terms the
structures so evolved are known as network topologies. Thus network topologies may change with time via
addition or subtraction of nodes or links to allow for determination of suitable information routes or
implementation of flow control. Furthermore changes may occur on account of temporary failure of some nodes
or due to link congestion (Ahuja 1982). Various algorithms have therefore been developed to serve as tools for
appropriately defining network topologies depending on the specific problem objectives. These include minimal
spanning tree, shortest - route algorithm, maximum flow algorithm, minimum – cost capacitated network
algorithm. Application of these methods has been reported widely and may be found in the works of Wayne
(1999), Taha (2008) and Beasley (2004) for transportation, foreign exchange/multinational tax planning
networks, Nozari et al. (1981) for computerized facility layout etc.
2.1 Telecommunication Network Case Study
A typical telecommunication system (Bassey 2001), used for linking some oil and gas operational centres is
illustrated in Figure 6. It consists of a set of nodes which are the equipment such as radios, duplexers,
multiplexers, PABX, switches, bridges etc and edges which are links used for voice or data communication. The
designed link capacities are as given on the left hand side corners of the nodes where the nodes 1, 2 and 3 are
terminal concentrators. Figure 3, emphasizes the operational topology of the network for the connections at node
1 in which possible loops 1,4,5,1; 1,8,9,1 and 1,2,3,1 are indicated. Such loops are capable of causing
information recycle resulting in inefficient operation of the network. Figure 8 further shows the architecture of
the base case network when all the nodes are interconnected and the distances between the nodes are as indicated
on the edges
The objective of this paper, was to carry out performance analysis of the base case telecommunication network
and there from synthesize topology for the network which shall be the least prone to failure.
2.2 Performing the Analysis
It is always the desire of System designers /analysts to thrive to select the most effective architecture or design
constraints which drive a system to maximum performance. Network performance is concerned with measuring
or estimating the parameters that represent
the network behavior which in most cases is the benchmark of what a system is capable of doing. The
parameters of general interest are the network delays, throughput, link utilization etc. These parameters can
consequently be measured in terms of transmission efficiency / reliability and operational cost of the network
topology (Leino et al. 2006; Ekpenyong et al. 2009).
48
4. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
www.iiste.org
2.3 Estimating Network Parameters
2.3.1 Network Delay
This is estimated as the delay prior to start of transmission of information as well as the delay incurred in
processing same through the link and is given by the expression (Ahuja 1982) in equation (1):
M
T = ∑ ƛiƔ-1[1/(uLi - ƛi)]
i=1
(2)
where:
T - network delay, s
ƛi - information traffic in ith link, bits/s
Ɣ- total information traffic in the network (throughput), bits/s
Li-Link capacity, bits/s
1/u-average size of information, bits
M- total number of links
2.3.2 Network Throughput
Throughput may be defined as the magnitude of information in bits per second received correctly and it is
expressed as shown in equation (2):
N N
Ɣ =∑ ∑ Ɣjk
(3)
j=1 k=1
where:
Ɣ - network throughput, bits/s
Ɣjk - average traffic from node j to node k, bits/s
N - total number of nodes from j to k
2.3.3 Link Utilization
The Link Utilisation p, can be estimated by using the expression in equation (3):
p = ƛi/uLi
(4)
where all the notations remain as earlier defined.
2.3.4 Network Cost
Assuming the distance matrix D = djk, of dimension NxN for all the nodes of the assigned region and the cost
C(x), of communicating between the nodes j and k is proportional to the distance between the nodes, djk. Then
introducing Boolean variables we have as follows:
xj =
1, if the link djk,is within the network topology
(5)
0, if otherwise
N N
C(x) = ∑ ∑ djk xjk
j=1 k=1
(6)
Under the constraints:
N
N
∑xjk = 1, ∑ xjk =1,
j=1
k=1
j, k = 1,2,3…N
xjk =0 or1
(7)
3. Synthesis of Network Topology
From the analysis above it may be observed that synthesis of the network to evolve the topology that will satisfy
the needed objective shall invariably translate into estimating the variables, xjk ∈ {0,1} using a chosen criterion
that will minimize the goal function in equation (5) (Koryachko et al., 1970).
Assuming the associated probabilities for routes with successful transmission are P1, P2, … Pk, then probability
of successful transmission through the network is the product ∏Pi = P1 . P2 . … . Pk . By using the shortest route
algorithm this problem can be solved by converting elements of log∏Pi into log P1 + log P2 +…+ log Pk = ∑ log
Pk. (Taha, 2008).
For the most reliable topology, the objective is therefore to select the routes which maximize the probabilities of
successful transmission through the network. However since log Pk ≤ 0, then the maximization of log Pk is
replaced by the minimization of – log Pk`, which values are positive.
49
5. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
www.iiste.org
Accordingly, Table 1 gives the probability matrix for the network shown in Figure 8. These were obtained from
estimates of the operation statistics for the telecommunication
network in Figure 6. The figures in brackets in Table 1 are the – log Pk values for the links.
4. Analysis of Results.
The shortest route algorithm due to Dijkstra was employed in solving the problem using the data in Table 1. The
solution output from TORA software (Taha 2005) for transmission from node 1 to node 10 is as shown in Figure
9. From the result, it was found that the most reliable network topology is defined by the links 1-2, 1-3, 1-5-6, 17, 1-4-8, 1-9 and 1-10 with the maximum probability of 84.1 percent.
5. Conclusion
The properties of graphs useful for the analysis and synthesis of practical networks have been enunciated.
Examples of algorithms based on graph structures capable of providing cost effective solutions to the synthesis
of networks as well as permitting incorporation of efficiency factors to drive network performance, have been
given . The study of an existing Telecommunication network where the probabilities for successful transmission
through the links varied from 0.93 to 1, has shown that the most reliable topology that can be synthesized for the
network using Dijkstra’s shortest route algorithm gives a maximum performance probability of 0.841 for a
destination from nodes 1 to 10.
References
Ahuja, V. (1982). Design and Analysis of Computer Communication Networks. Mc Graw - Hill Coy, New York
Aspen – Products – Integration (2000). http:/www.aspenntech.com/index.asp? menuchoice. (December 4.)
Bassey, K. N. (2001). An overview of IT Infrastructure in SPDC: Identification of Bottlenecks and Possible
Solutions. Technical Report -SSIN-TSSW, SPDC Warri.Nigeria.
Bassey, E.N. (2000). Of Process Network Topology and Information Flow: The Theoretical Framework.
Technical Presentation. September Meeting of the Nigerian Society of Chemical Engineers, Warri.
Bassey, E. N., Bassey, O. B., & Bassey, U. N. (2005). The Design and Analysis of Process Networks using
Spanning Tree Technology. Global Journal of Mechanical Engineering, 6, (1), 59-68
Beasley, J. E. (2004). “OR-Notes”. mscmga.ms.ic.ac.uk/jeb/or/graph.html.
Kafarov, V. V. et al. (1974). Principles of Mathematical Modelling of Chemical Process Systems. Khimia,
Moscow
Koryachko, V. et al. (1970) CAD Basics. Mir Publisher, Moscow
Leino, J., Penttinen, A., & Virtamo, J. (2006). “Flow Level Performance Analysis of Wireless DataNetworks: A
Case Study”, Proceedings of the 2006 IEEE International Conference on Communications (Reprint 6 pages)
Linnhoff, B. et al. (1979). “Understanding Heat Exchanger Network”. Computers and Chemical Engineering, 3,
295-302
Lucey, T. (2002 ). Quantitative Technique. (6th Ed.). Thompson Learning High Holborn House, 50-51 Bedford
Row, London WC1R 4LR, 374-413
Nozari, A. and Enscore (Jr), E. E. (1981). “Computerised Facility Layout with Graph Theory”, Computer &
Industrial Engineering. 5, (3), 183-193
Scheid, F. (1983). Theory and Problems of Computers and Programming. Schaum’s Outline Series, McGraw –
Hill Book Company, Singapore
Steward D. V. (1987). Software Engineering with Systems Analysis and Design. Brooks Cole Pub. Coy.
California.
Taha H.A. (2005). Operations Research: An Introduction. (7th ed.). Prentice-Hall of India Private Limited, New
Delhi.
Taha H.A. (2008). Operations Research: An Introduction. (8th Ed.). PHI Learning Private Limited. New Delhi.
Wayne, K. D. (1999). “Generalized Maximum Flow Algorithms”. PhD Dissertation, Cornell University, USA.
Winston, W. L. (1994). Operations Research: Application and Algorithnms. Wordsworth Publishing Coy,
Belmont, California, USA.
50
7. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
www.iiste.org
Figure 7. Structural Configuration of the Base Case Network.
Figure 8. Network Architecture for Base Case with all nodes interconnected
Table1. Probability Matrix for the Telecommunication Network.
From
/ To
1
2
2
3
4
5
6
7
8
9
10
1
[0]
1
[0]
0.99
[0.0044]
0.99
[0.0044]
0.99
[0.0044]
0.90
[0.0458]
0.99
[0.0044]
0.93
[0.0315]
0.97
[0.0132]
0.99
[0.0044]
3
4
5
0.99
[0.0044]
0.95
[0.0223]
0.95
[0.0223]
0.95
[0.0223]
6
0.95
[0.0223]
7
0.99
[0.0044]
8
0.95
[0.0223]
9
0.95
[0.0223]
52
8. Network and Complex Systems
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.7, 2013
www.iiste.org
Figure 9. ‘Tora’ Solution of the most reliable Network Topology
53
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