Itcm a real time internet traffic classifier monitorijcsit
The continual growth of high speed networks is a challenge for real-time network analysis systems. The
real time traffic classification is an issue for corporations and ISPs (Internet Service Providers). This work
presents the design and implementation of a real time flow-based network traffic classification system. The
classifier monitor acts as a pipeline consisting of three modules: packet capture and pre-processing, flow
reassembly, and classification with Machine Learning (ML). The modules are built as concurrent processes
with well defined data interfaces between them so that any module can be improved and updated
independently. In this pipeline, the flow reassembly function becomes the bottleneck of the performance. In
this implementation, was used a efficient method of reassembly which results in a average delivery delay of
0.49 seconds, approximately. For the classification module, the performances of the K-Nearest Neighbor
(KNN), C4.5 Decision Tree, Naive Bayes (NB), Flexible Naive Bayes (FNB) and AdaBoost Ensemble
Learning Algorithm are compared in order to validate our approach.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
This document summarizes a study on the performance of LTE networks. The researchers conducted passive and active measurements on a commercial LTE network with over 300,000 users to analyze network characteristics and resource utilization. They found that while LTE provides higher bandwidth than 3G, TCP flows often underutilize available bandwidth due to factors like limited receive windows. On average, flows used only 52% of available bandwidth, lengthening transfers and wasting energy. The researchers developed techniques to estimate bandwidth and identify inefficient application behaviors to recommend protocol and design improvements.
We predict train delays caused by bad weather using ML. The model is trained with weather observation and then employed to weather forecast output to predict upcoming delays. The prediction can be done 2 days ahead with 1 hour interval.
Impact of Packet Inter-arrival Time Features for Online Peer-to-Peer (P2P) Cl...IJECEIAES
Identification of bandwidth-heavy Internet traffic is important for network administrators to throttle high-bandwidth application traffic. Flow features based classification have been previously proposed as promising method to identify Internet traffic based on packet statistical features. The selection of statistical features plays an important role for accurate and timely classification. In this work, we investigate the impact of packet inter-arrival time feature for online P2P classification in terms of accuracy, Kappa statistic and time. Simulations were conducted using available traces from University of Brescia, University of Aalborg and University of Cambridge. Experimental results show that the inclusion of inter-arrival time (IAT) as an online feature increases simulation time and decreases classification accuracy and Kappa statistic.
A Multipath Connection Model for Traffic MatricesIJERA Editor
Peer-to-Peer (P2P) applications have witnessed an increasing popularity in recent years, which brings new challenges to network management and traffic engineering (TE). As basic input information, P2P traffic matrices are of significant importance for TE. Because of the excessively high cost of direct measurement. In this paper,A multipath connection model for traffic matrices in operational networks. Media files can share the peer to peer, the localization ratio of peer to peer traffic. This evaluates its performance using traffic traces collected from both the real peer to peer video-on-demand and file-sharing applications. The estimation of the general traffic matrices (TM) then used for sending the media file without traffic. Share the media file, source to destination traffic is not occur. So it give high performance and short time process.
Traffic Dynamics in Virtual Routing Multi Topology SystemIOSR Journals
The document proposes an Adaptive Multipath Routing system to handle unpredicted traffic dynamics in a network. The system consists of two components: 1) A Weight Computation component that sets link weights to produce maximum path diversity across multiple virtual routing topologies. 2) A Traffic Splitting component that adaptively splits traffic across the topologies based on traffic conditions to balance loads. The system also uses Multiple Routing Configurations to allow packet forwarding on pre-configured alternative paths upon node or link failures, improving quality of service and network performance.
This paper outlines the need for traffic matrices and describes how Demand Deduction works. You will learn what a traffic matrix is and how Demand Deduction creates reliable traffic matrices; Demand Deduction as a proven accurate, complete, and useful traffic simulation.
More Information: http://cisco.com/go/quantum
Itcm a real time internet traffic classifier monitorijcsit
The continual growth of high speed networks is a challenge for real-time network analysis systems. The
real time traffic classification is an issue for corporations and ISPs (Internet Service Providers). This work
presents the design and implementation of a real time flow-based network traffic classification system. The
classifier monitor acts as a pipeline consisting of three modules: packet capture and pre-processing, flow
reassembly, and classification with Machine Learning (ML). The modules are built as concurrent processes
with well defined data interfaces between them so that any module can be improved and updated
independently. In this pipeline, the flow reassembly function becomes the bottleneck of the performance. In
this implementation, was used a efficient method of reassembly which results in a average delivery delay of
0.49 seconds, approximately. For the classification module, the performances of the K-Nearest Neighbor
(KNN), C4.5 Decision Tree, Naive Bayes (NB), Flexible Naive Bayes (FNB) and AdaBoost Ensemble
Learning Algorithm are compared in order to validate our approach.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
This document summarizes a study on the performance of LTE networks. The researchers conducted passive and active measurements on a commercial LTE network with over 300,000 users to analyze network characteristics and resource utilization. They found that while LTE provides higher bandwidth than 3G, TCP flows often underutilize available bandwidth due to factors like limited receive windows. On average, flows used only 52% of available bandwidth, lengthening transfers and wasting energy. The researchers developed techniques to estimate bandwidth and identify inefficient application behaviors to recommend protocol and design improvements.
We predict train delays caused by bad weather using ML. The model is trained with weather observation and then employed to weather forecast output to predict upcoming delays. The prediction can be done 2 days ahead with 1 hour interval.
Impact of Packet Inter-arrival Time Features for Online Peer-to-Peer (P2P) Cl...IJECEIAES
Identification of bandwidth-heavy Internet traffic is important for network administrators to throttle high-bandwidth application traffic. Flow features based classification have been previously proposed as promising method to identify Internet traffic based on packet statistical features. The selection of statistical features plays an important role for accurate and timely classification. In this work, we investigate the impact of packet inter-arrival time feature for online P2P classification in terms of accuracy, Kappa statistic and time. Simulations were conducted using available traces from University of Brescia, University of Aalborg and University of Cambridge. Experimental results show that the inclusion of inter-arrival time (IAT) as an online feature increases simulation time and decreases classification accuracy and Kappa statistic.
A Multipath Connection Model for Traffic MatricesIJERA Editor
Peer-to-Peer (P2P) applications have witnessed an increasing popularity in recent years, which brings new challenges to network management and traffic engineering (TE). As basic input information, P2P traffic matrices are of significant importance for TE. Because of the excessively high cost of direct measurement. In this paper,A multipath connection model for traffic matrices in operational networks. Media files can share the peer to peer, the localization ratio of peer to peer traffic. This evaluates its performance using traffic traces collected from both the real peer to peer video-on-demand and file-sharing applications. The estimation of the general traffic matrices (TM) then used for sending the media file without traffic. Share the media file, source to destination traffic is not occur. So it give high performance and short time process.
Traffic Dynamics in Virtual Routing Multi Topology SystemIOSR Journals
The document proposes an Adaptive Multipath Routing system to handle unpredicted traffic dynamics in a network. The system consists of two components: 1) A Weight Computation component that sets link weights to produce maximum path diversity across multiple virtual routing topologies. 2) A Traffic Splitting component that adaptively splits traffic across the topologies based on traffic conditions to balance loads. The system also uses Multiple Routing Configurations to allow packet forwarding on pre-configured alternative paths upon node or link failures, improving quality of service and network performance.
This paper outlines the need for traffic matrices and describes how Demand Deduction works. You will learn what a traffic matrix is and how Demand Deduction creates reliable traffic matrices; Demand Deduction as a proven accurate, complete, and useful traffic simulation.
More Information: http://cisco.com/go/quantum
(Slides) A demand-oriented information retrieval method on MANETNaoki Shibata
Enomoto, M., Shibata, N., Yasumoto, K., Ito, M. and Higashino, T.: A demand-oriented information retrieval method on MANET, International Workshop on Future Mobile and Ubiquitous Information Technologies (FMUIT'06).
http://ito-lab.naist.jp/themes/pdffiles/060510.makoto-e.fmuit06.pdf
In urban areas including shopping malls and stations
with many people, it is important to utilize various information
which those people have obtained. In this paper, we
propose a method for information registration and retrieval
in MANET which achieves small communication cost and
short response time. In our method, we divide the whole application
field into multiple sub-areas and classify records
into several categories so that mobile terminals in an area
holds records with a category. Each area is associated with
a category so that the number of queries for the category
becomes the largest in the area. Thus, mobile users search
records with a certain category by sending a query to nodes
in the particular area using existing protocol such as LBM
(Location-Based Multicast). Through simulations supposing
actual urban area near Osaka station, we have confirmed
that our method achieves practical communication
cost and performance for information retrieval in MANET.
Call Admission Control Scheme With Multimedia Scheduling Service in WiMAX Net...Waqas Tariq
WiMAX network introduces a multimedia data scheduling service with different quality of service (QoS) requirements. Transmission opportunities are scheduled by the service according to the types of traffic data for the different connections or users. In the paper, we first propose a uniform definition of QoS level for the multimedia data types in the service. The QoS level of a connection are determined by the type of data of the connection and its allocated resources. Based on these QoS levels, we propose a call admission control (CAC) scheme for the entry admission of a new connection without degrading the network performance and the QoS of ongoing connections. The key idea of this scheme is to regulate the arriving traffic of the network such that the network can work at an optimal point, given under a heavy load traffic. Taking advantage of the simulation experiments, we confirm the fact that the proposed scheme can achieve better trade-off between the overall performance of network system and the QoS level of individual connection.
IRJET- Simulation Analysis of a New Startup Algorithm for TCP New RenoIRJET Journal
This document presents a simulation analysis of a new startup algorithm for TCP New Reno to improve responsiveness for short-lived applications. The proposed TCP SYN Loss (TSL) startup algorithm uses a less conservative congestion response than standard TCP when connection setup packets are lost. Simulations are conducted using the ns-2 network simulator to evaluate the performance of TSL variants under different levels of congestion. The main results show that TSL variants can achieve an average latency gain of 15 round-trip times compared to standard TCP at up to 90% link utilization with a packet loss rate of 1%.
Communications made easy_spectrumtechnologiesParveen Sultana
This document provides an overview of topics within the unit on communication systems, including characteristics of communication systems, examples of systems, transmitting and receiving processes, other information processes, and issues related to systems. The topics are divided into subsections that describe components like protocols, network hardware, and specific issues around messaging, internet use, and telecommuting.
This document summarizes a review paper on congestion control approaches for real-time streaming applications on the Internet. It discusses how TCP is not well-suited for real-time streaming due to its reliance on packet loss and variable bitrates. The paper reviews different end-to-end and active queue management approaches for congestion control that aim to reduce latency and jitter. It covers issues with single and shared bottlenecks on the Internet that can lead to congestion and the need for new transport protocols and congestion control for real-time media streaming.
This document evaluates shallow and deep network models for analyzing Secure Shell (SSH) traffic. It describes extracting flow feature statistics from network traffic and inputting them into recurrent neural networks (RNNs) and long short-term memory (LSTM) models for classification. The models are tested on public and private network trace datasets for their ability to classify SSH traffic and background applications over SSH versus non-SSH traffic. Deep learning models performed better than machine learning algorithms at traffic classification across different training and testing dataset configurations.
FORECASTING THE WIMAX TRAFFIC VIA MODIFIED ARTIFICIAL NEURAL NETWORK MODELSijaia
This paper attempts to present a new approach of forecasting the WiMAX traffic by exploiting Artificial
Neural Networks (ANN). To develop the model, actual data is gathered from the LibyaMax network that spans the duration of 180 days in total. Traffic data is separated into three cases based on the base stations involved (A, B and AB). The model implements traffic prediction by emphasizing on the maximum and minimum number of online user whereby two different learning algorithms are tested upon. to find the optimal one. Overall, the experimentation shows promising results of which the most severe error of prediction is not more than 0.0014. This indicates the feasibility of making accurate forecasting of both daily and weekly traffic of the WiMAX network based solely on the maximum and minimum number of users online.
Research Report - Merging Interstate Transportation Networks for routing Haza...Andrew Emerson
The document discusses merging the transportation network database used by Oak Ridge National Laboratory's Center for Transportation Analysis (CTA) with the open-source OpenStreetMap (OSM) network. This was done to improve the accuracy and update interstate routes in the CTA network. The process involved manipulating OSM data to match CTA classifications, creating "SuperLink" datasets of interstate segments, assigning geometric attributes to SuperLinks, and designating hazardous material routes by comparing intersections with the CTA network. The result was an accurate, updated version of the CTA network using OSM's more precise geospatial data.
This document discusses the need for network simulation tools to test telecom network components before they are deployed. It describes the key requirements for building an efficient simulation tool that can accurately model a complex telecom network, including 3G and UMTS networks. Specifically, it discusses the need to generate realistic traffic patterns and loads, model protocols and interfaces, and consider physical layer factors like RF path loss and power control mechanisms. The document provides details on using semi-Markovian models to generate traffic according to different states and distributions. It also outlines the overall architecture of a packet load generator tool to simulate network elements and evaluate their performance under different traffic scenarios.
Performance Evaluation of Routing Protocols in University Networkijtsrd
In an enterprise network, multiple dynamic routing protocols are used for forwarding packets with the best routes. Therefore, performance of the network is based on routing protocols and the route redistribution is an important issue in an enterprise network that has been configured by multiple different routing protocols in its routers. So, aim of the system is to analyze the performance and comparison of different Interior Gateway routing protocols. Routing is depended on many parameters critical such as network convergence time, Ethernet delay, throughput, end to end delay, jitter, packet delivery, security and bandwidth, etc. In this paper, the analysis of characteristics and the performance of the different routing protocols as Routing Information Protocol RIP , Open Shortest Path First OSPF and Enhanced Interior Gateway Routing Protocol EIGRP are evaluated in a university network. The performance evaluation are based on end to end packet delay, network convergence time, packet delay variation and administrative distance, etc. The analysis focuses on the performance of the routing protocols with its routing table in a simulator. The Simulation software can be used to evaluate and compare the performance of the routing protocols. The simulator return the routing table for each node or router in the university network which would contain the best path to reach the remote destination on the metric chosen based on the routing protocol implemented. The simulation software give results used to evaluate the performance of routing protocols, the performance of different routing protocols will be compared, and to analyze the convergence time and administrative distance of routing protocols. Kyaw Zay Oo "Performance Evaluation of Routing Protocols in University Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26582.pdfPaper URL: https://www.ijtsrd.com/engineering/information-technology/26582/performance-evaluation-of-routing-protocols-in-university-network/kyaw-zay-oo
Performance Analysis of Data Traffic Offload Scheme on Long Term Evolution (L...TELKOMNIKA JOURNAL
One of new mobile technology is being developed by 3GPP is Long Term Evolution (LTE). LTE
usually used by user because provide high data rate. Many traffic sending over LTE, makes several users
didn’t get good Quality of Service (QoS). Traffic diversion is needed to increasing QoS value. It can be
done with offloading data method from LTE to Wi-Fi network. This paper using 802.11ah standard to
evaluate Wi-Fi network. IEEE 802.11ah have 1000 meters coverage area and efficiency energy
mechanism, which is proposed for M2M in 5G techonology. Some research has proven that traffic
diversion with offloading can increasing network performance. The contribution of this paper is to evaluate
the impact of traffic offload between LTE and IEEE 802.11ah standard. This paper propose two scenarios
using increment number of user and increment mobility speed of user to evaluate throughput and delay
value before and after the offload process. The simulation will simulate using Network Simulator-3. We can
conclude that network performance after offloading is better for every scenario. For increment number of
user scenario, throughput value increasing 29.08%, and delay decreasing 8.12%. Scenario with increment
mobility speed of user obtain throughput value increasing 37,57%, and delay value decreasing 27.228%.
Study on Performance of Simulation Analysis on Multimedia NetworkIRJET Journal
This document summarizes a study that simulated voice communication over wired networks using the NS-2 network simulator. The study modeled VoIP traffic between nodes using the SCTP protocol and added background traffic to evaluate its effects. Key findings from the simulation included:
1) Average latency was 0.98 seconds and 98 packets were dropped, indicating degraded performance when background traffic was added.
2) Average jitter (packet delay variation) was calculated to be 0.006 seconds, showing instability in the network with changing traffic patterns.
3) A graph of latency over time demonstrated increased delays and bottlenecks as background traffic overloaded network links.
Summarize for Principles of Statistics (ٍStat 500) and it's Lectures for students of Computer Science in Institute of Statistical Studies and Research - Cairo University
Summarize for Principles of Statistics (ٍStat 500) . it's Lectures for students of Computer Science and especially students of graduate studies of the Institute of Statistical Studies and Research - Cairo University
(Slides) A demand-oriented information retrieval method on MANETNaoki Shibata
Enomoto, M., Shibata, N., Yasumoto, K., Ito, M. and Higashino, T.: A demand-oriented information retrieval method on MANET, International Workshop on Future Mobile and Ubiquitous Information Technologies (FMUIT'06).
http://ito-lab.naist.jp/themes/pdffiles/060510.makoto-e.fmuit06.pdf
In urban areas including shopping malls and stations
with many people, it is important to utilize various information
which those people have obtained. In this paper, we
propose a method for information registration and retrieval
in MANET which achieves small communication cost and
short response time. In our method, we divide the whole application
field into multiple sub-areas and classify records
into several categories so that mobile terminals in an area
holds records with a category. Each area is associated with
a category so that the number of queries for the category
becomes the largest in the area. Thus, mobile users search
records with a certain category by sending a query to nodes
in the particular area using existing protocol such as LBM
(Location-Based Multicast). Through simulations supposing
actual urban area near Osaka station, we have confirmed
that our method achieves practical communication
cost and performance for information retrieval in MANET.
Call Admission Control Scheme With Multimedia Scheduling Service in WiMAX Net...Waqas Tariq
WiMAX network introduces a multimedia data scheduling service with different quality of service (QoS) requirements. Transmission opportunities are scheduled by the service according to the types of traffic data for the different connections or users. In the paper, we first propose a uniform definition of QoS level for the multimedia data types in the service. The QoS level of a connection are determined by the type of data of the connection and its allocated resources. Based on these QoS levels, we propose a call admission control (CAC) scheme for the entry admission of a new connection without degrading the network performance and the QoS of ongoing connections. The key idea of this scheme is to regulate the arriving traffic of the network such that the network can work at an optimal point, given under a heavy load traffic. Taking advantage of the simulation experiments, we confirm the fact that the proposed scheme can achieve better trade-off between the overall performance of network system and the QoS level of individual connection.
IRJET- Simulation Analysis of a New Startup Algorithm for TCP New RenoIRJET Journal
This document presents a simulation analysis of a new startup algorithm for TCP New Reno to improve responsiveness for short-lived applications. The proposed TCP SYN Loss (TSL) startup algorithm uses a less conservative congestion response than standard TCP when connection setup packets are lost. Simulations are conducted using the ns-2 network simulator to evaluate the performance of TSL variants under different levels of congestion. The main results show that TSL variants can achieve an average latency gain of 15 round-trip times compared to standard TCP at up to 90% link utilization with a packet loss rate of 1%.
Communications made easy_spectrumtechnologiesParveen Sultana
This document provides an overview of topics within the unit on communication systems, including characteristics of communication systems, examples of systems, transmitting and receiving processes, other information processes, and issues related to systems. The topics are divided into subsections that describe components like protocols, network hardware, and specific issues around messaging, internet use, and telecommuting.
This document summarizes a review paper on congestion control approaches for real-time streaming applications on the Internet. It discusses how TCP is not well-suited for real-time streaming due to its reliance on packet loss and variable bitrates. The paper reviews different end-to-end and active queue management approaches for congestion control that aim to reduce latency and jitter. It covers issues with single and shared bottlenecks on the Internet that can lead to congestion and the need for new transport protocols and congestion control for real-time media streaming.
This document evaluates shallow and deep network models for analyzing Secure Shell (SSH) traffic. It describes extracting flow feature statistics from network traffic and inputting them into recurrent neural networks (RNNs) and long short-term memory (LSTM) models for classification. The models are tested on public and private network trace datasets for their ability to classify SSH traffic and background applications over SSH versus non-SSH traffic. Deep learning models performed better than machine learning algorithms at traffic classification across different training and testing dataset configurations.
FORECASTING THE WIMAX TRAFFIC VIA MODIFIED ARTIFICIAL NEURAL NETWORK MODELSijaia
This paper attempts to present a new approach of forecasting the WiMAX traffic by exploiting Artificial
Neural Networks (ANN). To develop the model, actual data is gathered from the LibyaMax network that spans the duration of 180 days in total. Traffic data is separated into three cases based on the base stations involved (A, B and AB). The model implements traffic prediction by emphasizing on the maximum and minimum number of online user whereby two different learning algorithms are tested upon. to find the optimal one. Overall, the experimentation shows promising results of which the most severe error of prediction is not more than 0.0014. This indicates the feasibility of making accurate forecasting of both daily and weekly traffic of the WiMAX network based solely on the maximum and minimum number of users online.
Research Report - Merging Interstate Transportation Networks for routing Haza...Andrew Emerson
The document discusses merging the transportation network database used by Oak Ridge National Laboratory's Center for Transportation Analysis (CTA) with the open-source OpenStreetMap (OSM) network. This was done to improve the accuracy and update interstate routes in the CTA network. The process involved manipulating OSM data to match CTA classifications, creating "SuperLink" datasets of interstate segments, assigning geometric attributes to SuperLinks, and designating hazardous material routes by comparing intersections with the CTA network. The result was an accurate, updated version of the CTA network using OSM's more precise geospatial data.
This document discusses the need for network simulation tools to test telecom network components before they are deployed. It describes the key requirements for building an efficient simulation tool that can accurately model a complex telecom network, including 3G and UMTS networks. Specifically, it discusses the need to generate realistic traffic patterns and loads, model protocols and interfaces, and consider physical layer factors like RF path loss and power control mechanisms. The document provides details on using semi-Markovian models to generate traffic according to different states and distributions. It also outlines the overall architecture of a packet load generator tool to simulate network elements and evaluate their performance under different traffic scenarios.
Performance Evaluation of Routing Protocols in University Networkijtsrd
In an enterprise network, multiple dynamic routing protocols are used for forwarding packets with the best routes. Therefore, performance of the network is based on routing protocols and the route redistribution is an important issue in an enterprise network that has been configured by multiple different routing protocols in its routers. So, aim of the system is to analyze the performance and comparison of different Interior Gateway routing protocols. Routing is depended on many parameters critical such as network convergence time, Ethernet delay, throughput, end to end delay, jitter, packet delivery, security and bandwidth, etc. In this paper, the analysis of characteristics and the performance of the different routing protocols as Routing Information Protocol RIP , Open Shortest Path First OSPF and Enhanced Interior Gateway Routing Protocol EIGRP are evaluated in a university network. The performance evaluation are based on end to end packet delay, network convergence time, packet delay variation and administrative distance, etc. The analysis focuses on the performance of the routing protocols with its routing table in a simulator. The Simulation software can be used to evaluate and compare the performance of the routing protocols. The simulator return the routing table for each node or router in the university network which would contain the best path to reach the remote destination on the metric chosen based on the routing protocol implemented. The simulation software give results used to evaluate the performance of routing protocols, the performance of different routing protocols will be compared, and to analyze the convergence time and administrative distance of routing protocols. Kyaw Zay Oo "Performance Evaluation of Routing Protocols in University Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26582.pdfPaper URL: https://www.ijtsrd.com/engineering/information-technology/26582/performance-evaluation-of-routing-protocols-in-university-network/kyaw-zay-oo
Performance Analysis of Data Traffic Offload Scheme on Long Term Evolution (L...TELKOMNIKA JOURNAL
One of new mobile technology is being developed by 3GPP is Long Term Evolution (LTE). LTE
usually used by user because provide high data rate. Many traffic sending over LTE, makes several users
didn’t get good Quality of Service (QoS). Traffic diversion is needed to increasing QoS value. It can be
done with offloading data method from LTE to Wi-Fi network. This paper using 802.11ah standard to
evaluate Wi-Fi network. IEEE 802.11ah have 1000 meters coverage area and efficiency energy
mechanism, which is proposed for M2M in 5G techonology. Some research has proven that traffic
diversion with offloading can increasing network performance. The contribution of this paper is to evaluate
the impact of traffic offload between LTE and IEEE 802.11ah standard. This paper propose two scenarios
using increment number of user and increment mobility speed of user to evaluate throughput and delay
value before and after the offload process. The simulation will simulate using Network Simulator-3. We can
conclude that network performance after offloading is better for every scenario. For increment number of
user scenario, throughput value increasing 29.08%, and delay decreasing 8.12%. Scenario with increment
mobility speed of user obtain throughput value increasing 37,57%, and delay value decreasing 27.228%.
Study on Performance of Simulation Analysis on Multimedia NetworkIRJET Journal
This document summarizes a study that simulated voice communication over wired networks using the NS-2 network simulator. The study modeled VoIP traffic between nodes using the SCTP protocol and added background traffic to evaluate its effects. Key findings from the simulation included:
1) Average latency was 0.98 seconds and 98 packets were dropped, indicating degraded performance when background traffic was added.
2) Average jitter (packet delay variation) was calculated to be 0.006 seconds, showing instability in the network with changing traffic patterns.
3) A graph of latency over time demonstrated increased delays and bottlenecks as background traffic overloaded network links.
Summarize for Principles of Statistics (ٍStat 500) and it's Lectures for students of Computer Science in Institute of Statistical Studies and Research - Cairo University
Summarize for Principles of Statistics (ٍStat 500) . it's Lectures for students of Computer Science and especially students of graduate studies of the Institute of Statistical Studies and Research - Cairo University
The document discusses Saudi Arabia's 2016 budget and economic outlook amid low oil prices. It announces planned spending cuts, subsidy reforms, and taxation to address a projected $87 billion deficit. Saudi Arabia will need $4 trillion in investments by 2030 to diversify its oil-dependent economy. The construction sector is highlighted as a focus for maintaining investment. Several major building and infrastructure projects expected to begin in 2016 are outlined, with total estimated values provided.
1) The document discusses the development of a traffic data fusion methodology that intelligently combines multiple data sources to obtain more accurate and complete traffic information than any single source can provide alone.
2) Different data sources have strengths and weaknesses depending on traffic conditions, and understanding these strengths and weaknesses helps to resolve differences between sources.
3) Intelligent data fusion using quality measures from multiple sources can provide near-complete traffic coverage and high quality information, improving transport network management and planning.
Traffic analysis for Planning, Peering and Security by Julie LiuMyNOG
This document discusses how xFlow technology can provide value to internet service providers (xSPs) through traffic visibility, peering analysis, and infrastructure security. It describes how xFlow data collection and analysis can generate traffic matrices for capacity planning, peering analysis, and anomaly detection. The document also explains how flow-based learning and detection techniques can identify infrastructure security threats like DDoS attacks. Finally, it discusses how cloud-based mitigation techniques like RTBH, BGP FlowSpec, and out-of-path traffic cleaning can divert anomalous traffic to protect networks and services.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Traffic Profiles and Management for Support of Community NetworksSmartenIT
The document analyzes traffic profiles and management for community networks. It finds that:
1) Traffic is dominated by YouTube, Facebook, and file uploads. Flows vary significantly by application in rate, volume, duration and round trip delays.
2) Content delivery currently relies on long paths through CDNs or P2P overlays rather than local caching due to lack of cooperation between networks and providers.
3) IETF groups are developing standards like CDNI and ALTO to optimize traffic and encourage localized content delivery through more cooperative approaches.
Prototype Implementation of a Demand Driven Network Monitoring ArchitectureAugusto Ciuffoletti
The document summarizes a prototype implementation of an on-demand network monitoring architecture. The architecture features clients that submit monitoring requests, sensors that perform the monitoring, and agents that route requests and streams. The prototype implements the key components in Java and uses SOAP, UDP, and LDAP. It was developed over three months as a proof of concept for an on-demand approach to network monitoring at Internet scale.
Jamming aware traffic allocation for multiple-path routing using portfolio se...Saad Bare
Multiple-path source routing protocols allow a data source node to distribute the total traffic among available paths. we consider the problem of jamming-aware source routing in which the source node performs traffic allocation based on empirical jamming statistics at individual network nodes. We formulate this traffic allocation as a lossy network flow optimization problem using portfolio selection theory from financial statistics. We show that in multisource networks, this centralized optimization problem can be solved using a distributed algorithm based on decomposition in network utility maximization (NUM). We demonstrate the network's ability to estimate the impact of jamming and incorporate these estimates into the traffic allocation problem. Finally, we simulate the achievable throughput using our proposed traffic allocation method in several scenarios.
The document describes the OSI model, which has 7 layers: Physical, Data Link, Network, Transport, Session, Presentation, and Application. Each layer defines a set of functions for data communication and passes data to the next layer. The layers work together to encapsulate and de-encapsulate data as it travels from its source to its destination in a network.
My talk at the Winter School on Big Data in Tarragona, Spain.
Abstract: We have made much progress over the past decade toward harnessing the collective power of IT resources distributed across the globe. In high-energy physics, astronomy, and climate, thousands work daily within virtual computing systems with global scope. But we now face a far greater challenge: Exploding data volumes and powerful simulation tools mean that many more--ultimately most?--researchers will soon require capabilities not so different from those used by such big-science teams. How are we to meet these needs? Must every lab be filled with computers and every researcher become an IT specialist? Perhaps the solution is rather to move research IT out of the lab entirely: to leverage the “cloud” (whether private or public) to achieve economies of scale and reduce cognitive load. I explore the past, current, and potential future of large-scale outsourcing and automation for science, and suggest opportunities and challenges for today’s researchers.
Delivering Application-Layer Traffic Optimization (ALTO) Services based on ...Danny Alex Lachos Perez
Application-Layer Traffic Optimization (ALTO) is an IETF standardized protocol that provides abstract network topology and cost maps in addition to endpoint information services that can be consumed by applications in order to become network-aware and take optimized decisions regarding traffic flows. In this work, we propose a public service based on the ALTO specification using public routing information available at the Brazilian Internet eXchange Points (IXPs). Our ALTO server prototype takes the acronym of AaaS (ALTO-as-a-Service) and is based on over 2.5GB of real BGP data from the 25 Brazilian IX.br public IXPs. We evaluate our proposal in terms of functional behaviour and performance via proof of concept experiments which point to the potential benefits of applications being able to take smart endpoint selection decisions when consuming the developer-friendly ALTO APIs.
This document discusses network flow analysis of traffic data from the Internet2 Abilene network. It provides an overview of Netflow data collection and analysis techniques, along with some preliminary results. Future work is proposed to further examine the dynamics, structure, and anomalies within the large-scale network flow data.
This document discusses network flow analysis of traffic data from the Internet2 Abilene network. It provides an overview of Netflow data collection and analysis techniques, along with some preliminary results. Future work is proposed to further analyze the dynamics, structure, and anomalies within the large-scale network flow data.
This document summarizes the key aspects of routing protocols for mobile ad hoc networks (MANETs). It discusses three categories of routing protocols: proactive, reactive, and hybrid protocols. Proactive protocols maintain routing tables through regular table updates, while reactive protocols find routes on demand through route discovery. Common proactive protocols described include DSDV and OLSR, while reactive protocols like AODV are now more widely used due to lower overhead. Hybrid routing protocols incorporate aspects of both approaches.
The document outlines the units and topics to be covered in a course on computer networks. Unit 1 will cover introductions to data communications, networks, protocols and standards, as well as the physical layer and transmission media. Unit 2 focuses on the data link layer, including error detection, error correction, framing, and flow control. Unit 3 discusses design issues like routing algorithms, while Unit 4 examines congestion control and internetworking. The final units cover protocols like TCP and UDP, as well as application layer topics such as DNS and name servers.
Checkspeed.org is a website that provides tools to check internet speed. It uses both active and passive techniques to monitor bandwidth. Active techniques involve sending probe packets into the network to gather data, while passive techniques analyze existing network traffic. The site offers internet speed checking tools that users can access at http://www.checkspeed.org to test their bandwidth and see if any optimizations can be made to improve speed. Internet service providers also use monitoring to track bandwidth usage on their networks and ensure connections are performing adequately.
6-OSI Model - ISO - Organization for Standardization.vedhatrioathi100
The OSI model consists of 7 layers that define the functions of network communication. Each layer has a specific role and passes data to the next layer. The network layer is responsible for logical addressing, routing packets between networks, and delivering packets to their destination across multiple networks using protocols like IP.
Computer networks Module 3 Transport layerclaudle200415
The document discusses the transport layer and provides an overview of key concepts. It introduces transport layer services including multiplexing, demultiplexing, and reliable data transfer. It describes the two main Internet transport protocols - UDP which provides connectionless unreliable data transfer, and TCP which provides connection-oriented reliable transfer. The document outlines the concepts that will be covered in more detail, including multiplexing, demultiplexing, the transport protocols UDP and TCP, and congestion control.
This document proposes a technique for detecting network traffic anomalies through analyzing packet header data. It focuses on monitoring outgoing traffic at an egress router to detect attacks and anomalies close to their source. The existing approaches rely on multiple data sources or established rules, while the proposed method analyzes a single link's destination addresses and port numbers using discrete wavelet transform and statistical analysis. It aims to reduce network traffic by preventing the transmission of large files through ingress and egress routing.
The document provides an introduction to computer networks. It discusses what a network is, why networks are needed, and how they are classified based on scale, connection method, and relationship. The key types of networks covered are personal area networks, local area networks, campus area networks, metropolitan area networks, wide area networks, and virtual private networks. Basic network hardware components are also introduced.
Agata provides high speed cyber solutions including a full featured Forensics suite with Meta Data and tens of thousands of dynamic policy rules, Layer-7 Intelligence, Network Analytics, filtered sessions and traffic recording.
Backed by 20 years of specialized research and development of traffic management and security solutions for top tier customers, Agata is able to provide best in class high-end technological products. Agata appliances allow enterprises to secure networks using state of the art cyber solutions. Agata DPI empowers the user to find, record, analyze and track security events and vulnerabilities including Zero-Day exploits.
The overview presentation includes a use case and a description of the different applications for Agata DPI.
AN ADVANCED QOS ANALYSIS AND EVALUATION METHOD FOR MOBILE INTERNET ACCESS ijwmn
The paper proposes a new method for the analysis and evaluation of the Quality of Service (QoS) in a
mobile Internet access scenario. In particular, the paper proposes a throughput evaluation method based
on PathChirp algorithm. The end-to-end bandwidth was estimated by means of the Self Loading of Periodic
Streams (SloPS) technique. The obtained measurements were then analyzed by estimating the degree of
correlation with other parameters that characterize the data transmission such as power, round trip time,
etc. Finally, in order to have greater spatial resolution performance guaranteed by an Internet service
provider, a 3D reconstruction method based on using drones is proposed and some preliminary results are
discussed.
Similar to Internet measurement (Presentation) (20)
The document describes the RoboCupRescue 2006 Robot League Team from Iran called MRL. It discusses three rescue robots they have designed - two for indoor use and one for outdoor/rough terrain. Their goal is to develop practical rescue robots that can help with search and rescue operations during earthquakes, which frequently occur in Iran. Team members are from the Mechatronics Research Laboratory and are working on various research areas related to autonomous mobile robots like localization, mapping, navigation, and search algorithms.
The document presents research on measuring video quality based on network traffic. It proposes using both application and network level metrics to estimate distortion and quality. At the application level, motion intensity is measured using I, P, and B frame sizes. At the network level, packet loss effects are estimated based on GOP properties and structure. Distortion is estimated as the product of motion intensity and loss effect, and quality is estimated as 1 minus the distortion. The research was evaluated using software like VLC and QPSNR, and results were validated by comparing to other quality metrics and calculating the coefficient of variation and RMSE for different packet error rates. Benefits of the approach include simplicity, minimal overhead, online evaluation, non-reference nature, and
This document is the final project report for a degree in computer engineering from the Islamic Azad University of Qazvin. The project involved mapping an environment using an autonomous rescue robot. It thanks various individuals and groups for their support and guidance during the project, including the student's parents, the university president, and the project advisor and laboratory director. The document contains the typical sections of an engineering project report such as introduction, design and implementation, results, and conclusions.
The advent of social media has revolutionized communication, transforming the way people connect, share, and interact globally. At the forefront of this digital revolution are visionary entrepreneurs who recognized the potential of the internet to foster social connections and create communities. This essay explores the founders of some of the most influential social media platforms, their journeys, and the lasting impact they have made on society.
Mark Zuckerberg, along with his college roommates Eduardo Saverin, Andrew McCollum, Dustin Moskovitz, and Chris Hughes, founded Facebook in 2004. Initially created as a social networking site for Harvard University students, Facebook rapidly expanded to other universities and eventually to the general public. Zuckerberg's vision was to create an online directory that connected people through their real-life social networks.
Twitter, founded in 2006 by Jack Dorsey, Biz Stone, and Evan Williams, brought a new dimension to social media with its microblogging platform. Dorsey envisioned a service that allowed users to share short, real-time updates, limited to 140 characters (now 280). This concise format encouraged rapid sharing of information and fostered a culture of brevity and immediacy.
Kevin Systrom and Mike Krieger co-founded Instagram in 2010, focusing on photo and video sharing. Systrom, who studied photography, wanted to create an app that made mobile photos look professional. The app's unique filters and easy-to-use interface quickly gained popularity, amassing over a million users within two months of its launch.
Instagram's emphasis on visual content has had a significant cultural impact. It has popularized the concept of influencers, giving rise to a new industry where individuals can monetize their popularity and reach. The platform has also revolutionized digital marketing, enabling brands to connect with consumers in more authentic and engaging ways. Acquired by Facebook in 2012, Instagram continues to be a dominant force in social media, shaping trends and cultural norms.
Reid Hoffman founded LinkedIn in 2002 with the goal of creating a professional networking platform. Unlike other social media sites focused on personal connections, LinkedIn was designed to connect professionals, facilitate job searches, and foster business relationships. The platform allows users to create professional profiles, network with colleagues, and share industry insights.
LinkedIn has become an indispensable tool for job seekers, recruiters, and businesses. It has transformed the job market by making it easier to find and connect with potential employers and employees. LinkedIn's influence extends beyond job searches; it has become a hub for professional development, thought leadership, and industry news. Hoffman's vision has significantly impacted how professionals manage their careers and build their networks.
Jan Koum and Brian Acton co-founded WhatsApp in 2009, aiming to create a simple, reliable..
Ethics guidelines for trustworthy AI (HIGH-LEVEL EXPERT GROUP ON ARTIFICIAL I...prb404
On 8 April 2019, the High-Level Expert Group on AI presented Ethics Guidelines for Trustworthy Artificial Intelligence. This followed the publication of the guidelines' first draft in December 2018 on which more than 500 comments were received through an open consultation.
According to the Guidelines, trustworthy AI should be:
(1) lawful - respecting all applicable laws and regulations
(2) ethical - respecting ethical principles and values
(3) robust - both from a technical perspective while taking into account its social environment
Enhancing Security with Multi-Factor Authentication in Privileged Access Mana...Bert Blevins
In the ever-evolving landscape of cybersecurity, safeguarding sensitive data and critical systems has become paramount. As cyber threats grow in sophistication, organizations are constantly seeking innovative methods to fortify their defenses. Multi-Factor Authentication (MFA) stands out as a potent tool within the security arsenal, particularly when integrated with Privileged Access Management (PAM).
Privileged access management encompasses the methods, protocols, and tools employed to regulate and monitor access to privileged accounts within an organization. These accounts wield elevated privileges, enabling users to execute vital operations such as system configuration, access to sensitive data, and management of network infrastructure. However, if these privileges fall into the wrong hands, they pose a significant security risk. MFA adds an additional layer of protection by requiring users to provide multiple forms of verification before gaining access to a system or application. Key components of MFA in PAM include biometric verification, passwords, security tokens, and one-time passcodes. Deploying MFA within a PAM environment necessitates meticulous planning and consideration of various factors to ensure robust security.
Empowering Learning Through Digital Educationmalialisha063
Welcome to our presentation on Digital Education. Today, we will explore how digital tools and resources are transforming the landscape of education, making learning more accessible, engaging, and effective for students of all ages.
Enhancing Your Workflow Automation with Power AutomateBert Blevins
Efficiency stands as a paramount concern in today’s swiftly evolving digital landscape. Whether you oversee a large corporation, a small enterprise, or simply your personal tasks, streamlining processes through automation can bolster productivity, reduce errors, and save valuable time. This is where tools like Power Automate step in to offer invaluable assistance.
What is Power Automate?
Microsoft has developed Power Automate, a robust tool tailored for workflow automation needs. This platform, previously known as Microsoft Flow, empowers users to automate tasks across their preferred applications and services, facilitating tasks like file synchronization, notification management, data aggregation, and more, all without requiring extensive coding knowledge.
How Does Power Automate Operate?
At its core, Power Automate operates on a simple principle: when a certain condition is met, an action follows. Users construct workflows, termed “flows,” comprising triggers and actions. Triggers, such as receiving an email or adding a file to a folder, kickstart the flow in response to specific events. Actions denote the tasks executed as a consequence of the trigger, such as sending an email, updating a spreadsheet, or posting a message on a chat platform.
Key Highlights of Power Automate
Power Automate seamlessly integrates with a plethora of Microsoft and third-party apps like Office 365, SharePoint, Dynamics 365, and Salesforce, facilitating automation across diverse platforms and services. The mobile app ensures accessibility from any location, enabling users to create, monitor, and manage workflows directly from their mobile devices. Power Automate offers robust analytics tools for monitoring workflow performance, pre-built templates for common scenarios, and extensive customization options, allowing users to tailor processes to suit their specific requirements.
Empowering Your Workflow Automation with Power AutomateBert Blevins
Understanding Power Automate
Efficiency is critical in the fast-paced digital environment of today. Whether you’re trying to manage a major organization, a small business, or just your own personal tasks, automating processes can help you increase productivity, cut down on errors, and save time. This is where Power Automate and other such technologies are useful.
What is Power Automate?
Microsoft created Power Automate, a potent tool for workflow automation. With Power Automate, formerly known as Microsoft Flow, users can automate processes between their preferred apps and services to synchronize files, receive notifications, gather statistics, and more without having to know a lot of code.
How Does Power Automate Work?
Fundamentally, Power Automate works on the straightforward tenet that something should happen if this does. Workflows, or “flows,” made up of triggers and actions, can be created by users. Triggers, such as getting an email or adding a file to a folder, start the flow in response to a particular occurrence. Actions are the tasks performed as a result of the trigger, such as sending an email, updating a spreadsheet, or posting a message to a chat platform.
Key Features of Power Automate
Power Automate seamlessly integrates with a plethora of Microsoft and third-party apps like Office 365, SharePoint, Dynamics 365, and Salesforce, facilitating automation across diverse platforms and services. The mobile app ensures accessibility from any location, enabling users to create, monitor, and manage workflows directly from their mobile devices. Power Automate offers robust analytics tools for monitoring workflow performance, pre-built templates for common scenarios, and extensive customization options, allowing users to tailor processes to suit their specific requirements.
Use Cases for Power Automate
Automated Email Responses: Set up a flow to automatically respond to incoming emails with predefined messages, freeing up time for more important tasks.
Document Approval Workflows: Streamline the approval process by automating notifications and tracking for document reviews.
Social Media Management: Automate posts and interactions across multiple social media platforms.
Data Collection and Analysis: Aggregate data from various sources and automate report generation.
Task Management: Automatically create, assign, and track tasks within your project management tools.
Conclusion
For automating operations in a variety of apps and services, Power Automate provides an easy-to-use and adaptable solution. Power Automate may help you save time, minimize errors, and concentrate on what really matters whether you’re a project manager trying to increase productivity, a business owner trying to optimize operations, or an individual trying to simplify daily duties. Power Automate’s user-friendly interface, multitude of integration possibilities, and potent customization features enable customers to automate their way to increased success.
Trust and Security, presented by Geoff HustonAPNIC
Geoff Huston, Chief Scientist at APNIC delivers a remote presentation on Internet fragmentation and its effect on the trust and security of Internet at VNNIC Internet Conference 2024 held in Hanoi, Vietnam from 4 to 7 June 2024.
An Introduction to AI LLMs & SharePoint For Champions and Super Users Part 1BryanMurray35
This is part 1 of an 8-part introductory course for SharePoint Champions and Superusers focusing on integrating Large Language Models (LLMs) into corporate environments. Section 1 introduces LLMs, covering their definition, history, and capabilities. It explores how LLMs work, their impact across industries, and current limitations. The section also discusses popular LLM examples and future directions in the field, setting the foundation for understanding their potential in SharePoint contexts.
The course then takes a look at using online LLMs, local LLM deployment for corporate use, and the intricate process of installing and configuring these models. It provides detailed guidance on integrating LLMs with SharePoint, exploring various applications such as enhanced search, automated content tagging, and intelligent document processing. The later sections cover best practices and governance for LLM-enhanced SharePoint environments, addressing crucial aspects like data privacy, ethical considerations, and user adoption strategies.
The course concludes by examining future trends and considerations, preparing participants for the evolving landscape of AI-enhanced knowledge management. Throughout, it emphasizes practical applications, challenges, and solutions, equipping SharePoint Champions and Superusers with the knowledge to leverage LLMs effectively within their organizations.
Yes, most of it was written by an LLM.
3. Internet Traffic Measurement 3
Why Measure ?
Although Internet works, it is far from being ideal
Measurements of various aspects of it will:
Help us to better understand why it works the way it does
Help us to diagnose known problems and lead us one step
closer to their solutions
Help us to design new features that the Internet should
provide to enable next-generation application requirements
Simply put, “Internet Measurements is key to the
design of the next-generation Internet”
4. Internet Traffic Measurement 4
What to Measure ?
Physical Properties
Devices (routers, NAT boxes, firewalls, switches),
Links (wired, wireless)
Topology Properties
Various levels – Autonomous Systems (AS),
Points of Presence (PoP), Routers, Interfaces
Traffic Properties
Delays (Transmission, Propagation, Queuing,
Processing etc.), Losses, Throughput, Jitter
7. Internet Traffic Measurement 7
Active Measurement Tools
Methods that involve adding traffic to the network for the
purposes of measurement
Ping: Sends ICMP ECHO_REQUEST and captures ECHO_REPLY
Useful for measuring RTTs
Only sender needs to be under experiment control
Traceroute: Ping nodes with incremental TTL from one
Find Hops between source and destination node
Only sender needs to be under experiment control
There is some care about the result
8. Internet Traffic Measurement 8
Active Measurement Load
Active Measurement inserts considerable load on
network links if attempting a large-scale topology
discovery
Optimizations reduce this load considerably
If single source is used, instead of going from source to
destination, a better approach is to retrace from destination
to source
If multiple sources and multiple destinations are used,
sharing information among these would bring download
considerably
9. Internet Traffic Measurement 9
Passive Measurement
Capture traffic generated by other users and
applications
Routeview collects BGP views (routing tables) from
a large set of ASes
OSPF LSAs can processed to generate router
graphs within an AS
10. Internet Traffic Measurement 10
Fused Measurement
Active Measurement +
Passive Measurement +
Fused Measurement mixed method to use
benefits of each method.
Less Traffic Load
Less Required Storage
More information for decision
11. Internet Traffic Measurement 11
Inference Measurment
Measurement Limitations
Direct access impossible
Topology and link out of reach
How to solve ?
End-to-End Measurement
Tomography: process of inferring network topology, delays,
packet losses etc. using only end-to-end measurements
13. Internet Traffic Measurement 13
Measurement Level
Bit & Bytes (useless)
Packets (High volume)
High volume but valuable data for offline & generate traffic
Flow (limited to flows)
Protocols (Specific Protocol)
TCP, UDP, IP, RTP, ..
Application (Known applications)
HTTP, DNS, MAIL, VOIP, ...
SNMP
14. Internet Traffic Measurement 14
Hidden Pieces - Middleboxes
Firewalls – provide security
Traffic Shapers – assist in traffic management
Proxies – improve performance
NAT boxes – utilize IP address space efficiently
Each of these impedes visibility of network
components.
Example:
firewalls may block active probing requests
NATs hide away the no. of hosts and the structure of the
network on the other side
17. Internet Traffic Measurement 17
Bandwidth Measurment
Bandwidth Measurement
Amount of data the network can transmit per unit time
Three kinds of bandwidth
capacity: max throughput a link can sustain,
available bandwidth: capacity – used bandwidth
bulk transfer capacity: rate that a new single long-lived TCP
connection would obtain over a path
18. Internet Traffic Measurement 18
Path Provisioning by Traceroute
Suppose the path between A and D is to be
determined using traceroute
A
X Y
D
B C
22. Internet Traffic Measurement 22
Traceroute issues
Path Asymmetry (Destination -> Source need
not retrace Source -> Destination)
Unstable Paths and False Edges
Aliases
Measurement Load
23. Internet Traffic Measurement 23
Unstable Paths and False Edges
Inferred path: A -> B -> Y
A
X Y
D
B C
Dest = D
TTL = 1
B: “time
exceeded”
Dest = D
TTL = 2
Y: “time
exceeded”
24. Internet Traffic Measurement 24
Aliases
IP addresses are for interfaces and not
routers
Routers typically have many interfaces, each
with its own IP address
IP addresses of all the router interfaces are
aliases
Traceroute results require resolution of
aliases if they are to be used for topology
building
25. Internet Traffic Measurement 25
Video Quality Measurment
Subjective Evaluation
Variety cause of user experience
Need many user to vote
Objective Evaluation
Data Metrics (PSNR)
Picture Metrics (MPQM ,SSIM)
Packet/Bit stream Metrics (Loss)
Full/Reduced/Non Reference
Visible/Invisible distortion
27. Internet Traffic Measurement 27
Video Quality Measurment
Stream should be packetized
TS(DVB) vs RTP(IPTV)
Passive Measurement
Deep Packet Inspection
Resilience and Error correction
Quality Estimation (Fuzzy, NN, ...)