This document discusses best practices in network planning. It recommends starting with a simple approach using link statistics and estimation to determine traffic demand matrices, then verifying predictions against reality. If needed, more data from NetFlow or MPLS statistics can be added incrementally. Simulation is used to analyze working and failure scenarios to determine capacity requirements while meeting SLAs with a modest overprovisioning factor of around 10%.
SDN traffic engineering provides a simpler and more optimal approach compared to traditional offline and on-device traffic engineering. It uses segment routing to encode paths, push-based telemetry for real-time traffic matrices, and an SDN controller running a traffic engineering application to optimize paths network-wide in a centralized manner. This approach alleviates congestion, uses as few tunnels as necessary, and easily adapts to failures or network changes.
Neural Approximate Dynamic Programming for On-Demand Ride-Poolingivaderivader
This document summarizes a research paper on using neural approximate dynamic programming (NeurADP) to solve the ride-pooling matching problem (RMP) of optimally assigning passenger requests to vehicles. The key contributions are developing NeurADP, which uses a neural network to approximate the value function within an ADP framework, and connecting it to reinforcement learning. This allows NeurADP to handle the complex RMP involving partially filled vehicles better than prior methods. The researchers test NeurADP on New York City taxi data and find that changing constraints like maximum wait time and vehicle capacity affects NeurADP's ability to serve more requests while avoiding myopic assignments.
A fundamental problem before carriers today is to optimize network cost
and performance by better resource allocation to traffic demands. This is especially
important with the packet infrastructure becoming a critical business resource.
The key to achieving this is traffic engineering (TE), the process of
systematically putting traffic where there is capacity, and backbone
capacity management, the process of ensuring that there is enough network
capacity to meet demand, even at peak times and under failure conditions,
without significant queue buildups.
In this talk, we first focus on the TE techniques and approaches used
in the networks of two large carriers: Global Crossing and
Sprint, which represent the two ends of the traffic engineering spectrum.
We do so by presenting a snapshot of their TE philosophy, deployment strategy,
and network design principles and operation.
We then present the results of an empirical study of backbone traffic
characteristics that suggests that Internet traffic is not self-similar at
timescales relevant to QoS. Our non-parametric approach requires minimal
assumptions (unlike much of the previous work), and allows
us to formulate a practical process for ensuring QoS using backbone
capacity management.
(This latter work is joint with Thomas Telkamp, Global Crossing Ltd. and Arman
Maghbouleh, Cariden Technologies, Inc.)
The document discusses how application architects traditionally focused on solving IO bottlenecks in servers by offloading processing to intelligent network interface cards. With modern distributed applications spanning thousands of servers, application architects now must consider network topology, segmentation, and control plane protocols to optimize latency and bandwidth. The rise of virtualization and cloud computing has changed traffic patterns in datacenters from north-south traffic to dominant east-west traffic between servers. This requires new datacenter fabric designs beyond the traditional three-tiered topology.
This document discusses how content delivery networks (CDNs) like Akamai use DNS to route users to optimal servers based on their location. It explains that while this works well when users use their ISP's DNS, third-party DNS resolvers like Google DNS make accurate mapping difficult since the CDN only sees the resolver IP, not the user's. The document then introduces EDNS0 client-subnet, an extension that allows resolvers to include the user's IP prefix in queries, enabling more precise mapping by CDNs. It addresses privacy, security and implementation considerations, and shows how the technique improves performance for OpenDNS users in India.
A Survey of Recent Advances in Network Planning/Traffic Engineering (TE) ToolsVishal Sharma, Ph.D.
Designing & managing operational IP networks is a complex, multi-dimensional
task. A fundamental problem before carriers today
is to optimize network performance by better resource allocation to traffic demands.
This requires a systematic evaluation of options, a thorough scenario analysis,
and foolproof verification of network designs, all of which are increasingly
possible only with help from automated TE and planning tools.
In the past few years, significant advances have been made in enhancing existing
tools and developing new ones that help providers rapidly identify potential
performance problems, experiment with solutions, and develop robust designs.
Several techniques from optimization theory, linear programming, and
models of effective bandwidth calculation have been incorporated in such
tools, as have detailed models of several vendor systems.
We present a comparative analysis and an overview of key features of some key
commercially available network planning/TE tools, and outline how
they could be leveraged by carrier network engineering/planning
organizations to perform detailed network analysis, proactive/reactive
TE, and network design.
We first give an overview of the architecture, design philosophy, and canonical
features of modern design tools, and then focus on new enhancements to some
popular tools
as well as key distinguishing features of some newly developed ones.
In particular, we focus on decision support tools for IP network planning
and network analysis, including the latest versions from
WANDL, OPNET, Cariden..
We also present a perspective on current outstanding carrier requirements
for TE/planning tools that was synthesized by our conversations with
several leading Tier 1 and Tier 2 carriers.
Frank Brockners' presentation from the 2017 Open Networking Summit.
While troubleshooting or planning, did you ever wish to get full insight into which paths *all* your packets take in your network, understand whether your SLA is really in place, or were you ever asked to prove that your traffic really follows the path you specified by service chaining or traffic engineering? We approach this problem by adding meta-data to *all* packets. In-band OAM adds forwarding path information and other information/stats to every data packet - as opposed to relying on probe packets, which is the traditional method that tools like ping or traceroute use. This session will introduce In-band OAM, explain the technology and outline the reference implementation in FD.io/VPP and OpenDaylight using a example demos.
Hisham Zahoor is seeking a position as an RF Post Processing Engineer and has over 3 years of experience in the telecom industry. He has in-depth knowledge of GSM, UMTS, LTE networks and experience conducting drive tests, analyzing network data, and producing reports to optimize network performance. His professional experience includes projects with Zain, STC, and Bharti Telecom where he performed tasks such as site audits, drive testing, post processing analysis, and troubleshooting to resolve network issues.
SDN traffic engineering provides a simpler and more optimal approach compared to traditional offline and on-device traffic engineering. It uses segment routing to encode paths, push-based telemetry for real-time traffic matrices, and an SDN controller running a traffic engineering application to optimize paths network-wide in a centralized manner. This approach alleviates congestion, uses as few tunnels as necessary, and easily adapts to failures or network changes.
Neural Approximate Dynamic Programming for On-Demand Ride-Poolingivaderivader
This document summarizes a research paper on using neural approximate dynamic programming (NeurADP) to solve the ride-pooling matching problem (RMP) of optimally assigning passenger requests to vehicles. The key contributions are developing NeurADP, which uses a neural network to approximate the value function within an ADP framework, and connecting it to reinforcement learning. This allows NeurADP to handle the complex RMP involving partially filled vehicles better than prior methods. The researchers test NeurADP on New York City taxi data and find that changing constraints like maximum wait time and vehicle capacity affects NeurADP's ability to serve more requests while avoiding myopic assignments.
A fundamental problem before carriers today is to optimize network cost
and performance by better resource allocation to traffic demands. This is especially
important with the packet infrastructure becoming a critical business resource.
The key to achieving this is traffic engineering (TE), the process of
systematically putting traffic where there is capacity, and backbone
capacity management, the process of ensuring that there is enough network
capacity to meet demand, even at peak times and under failure conditions,
without significant queue buildups.
In this talk, we first focus on the TE techniques and approaches used
in the networks of two large carriers: Global Crossing and
Sprint, which represent the two ends of the traffic engineering spectrum.
We do so by presenting a snapshot of their TE philosophy, deployment strategy,
and network design principles and operation.
We then present the results of an empirical study of backbone traffic
characteristics that suggests that Internet traffic is not self-similar at
timescales relevant to QoS. Our non-parametric approach requires minimal
assumptions (unlike much of the previous work), and allows
us to formulate a practical process for ensuring QoS using backbone
capacity management.
(This latter work is joint with Thomas Telkamp, Global Crossing Ltd. and Arman
Maghbouleh, Cariden Technologies, Inc.)
The document discusses how application architects traditionally focused on solving IO bottlenecks in servers by offloading processing to intelligent network interface cards. With modern distributed applications spanning thousands of servers, application architects now must consider network topology, segmentation, and control plane protocols to optimize latency and bandwidth. The rise of virtualization and cloud computing has changed traffic patterns in datacenters from north-south traffic to dominant east-west traffic between servers. This requires new datacenter fabric designs beyond the traditional three-tiered topology.
This document discusses how content delivery networks (CDNs) like Akamai use DNS to route users to optimal servers based on their location. It explains that while this works well when users use their ISP's DNS, third-party DNS resolvers like Google DNS make accurate mapping difficult since the CDN only sees the resolver IP, not the user's. The document then introduces EDNS0 client-subnet, an extension that allows resolvers to include the user's IP prefix in queries, enabling more precise mapping by CDNs. It addresses privacy, security and implementation considerations, and shows how the technique improves performance for OpenDNS users in India.
A Survey of Recent Advances in Network Planning/Traffic Engineering (TE) ToolsVishal Sharma, Ph.D.
Designing & managing operational IP networks is a complex, multi-dimensional
task. A fundamental problem before carriers today
is to optimize network performance by better resource allocation to traffic demands.
This requires a systematic evaluation of options, a thorough scenario analysis,
and foolproof verification of network designs, all of which are increasingly
possible only with help from automated TE and planning tools.
In the past few years, significant advances have been made in enhancing existing
tools and developing new ones that help providers rapidly identify potential
performance problems, experiment with solutions, and develop robust designs.
Several techniques from optimization theory, linear programming, and
models of effective bandwidth calculation have been incorporated in such
tools, as have detailed models of several vendor systems.
We present a comparative analysis and an overview of key features of some key
commercially available network planning/TE tools, and outline how
they could be leveraged by carrier network engineering/planning
organizations to perform detailed network analysis, proactive/reactive
TE, and network design.
We first give an overview of the architecture, design philosophy, and canonical
features of modern design tools, and then focus on new enhancements to some
popular tools
as well as key distinguishing features of some newly developed ones.
In particular, we focus on decision support tools for IP network planning
and network analysis, including the latest versions from
WANDL, OPNET, Cariden..
We also present a perspective on current outstanding carrier requirements
for TE/planning tools that was synthesized by our conversations with
several leading Tier 1 and Tier 2 carriers.
Frank Brockners' presentation from the 2017 Open Networking Summit.
While troubleshooting or planning, did you ever wish to get full insight into which paths *all* your packets take in your network, understand whether your SLA is really in place, or were you ever asked to prove that your traffic really follows the path you specified by service chaining or traffic engineering? We approach this problem by adding meta-data to *all* packets. In-band OAM adds forwarding path information and other information/stats to every data packet - as opposed to relying on probe packets, which is the traditional method that tools like ping or traceroute use. This session will introduce In-band OAM, explain the technology and outline the reference implementation in FD.io/VPP and OpenDaylight using a example demos.
Hisham Zahoor is seeking a position as an RF Post Processing Engineer and has over 3 years of experience in the telecom industry. He has in-depth knowledge of GSM, UMTS, LTE networks and experience conducting drive tests, analyzing network data, and producing reports to optimize network performance. His professional experience includes projects with Zain, STC, and Bharti Telecom where he performed tasks such as site audits, drive testing, post processing analysis, and troubleshooting to resolve network issues.
This document is a resume for Adeel Ahmed, a 2G/3G/LTE RF engineer with almost 4 years of experience in network optimization and planning for cellular networks. It lists his contact information and objective, followed by a work history summarizing his roles optimizing networks for various telecom companies in Pakistan and the UAE. It also provides details of his educational background and technical skills.
Prefix Filtering Design Issues and Best Practise by Nurul IslamMyNOG
The document discusses best practices for prefix filtering design when receiving prefixes from upstream networks. It outlines four options for handling prefixes from customers: single-homed with non-portable prefixes, single-homed with portable prefixes, multi-homed with non-portable prefixes, and multi-homed with portable prefixes. For each option, it describes considerations for route filtering policies at the internet service provider and customer networks to filter routes and traffic appropriately based on the prefix and source autonomous system.
Improving Traffic Prediction Using Weather Data with Ramya RaghavendraSpark Summit
As common sense would suggest, weather has a definite impact on traffic. But how much? And under what circumstances? Can we improve traffic (congestion) prediction given weather data? Predictive traffic is envisioned to significantly impact how driver’s plan their day by alerting users before they travel, find the best times to travel, and over time, learn from new IoT data such as road conditions, incidents, etc. This talk will cover the traffic prediction work conducted jointly by IBM and the traffic data provider. As a part of this work, we conducted a case study over five large metropolitans in the US, 2.58 billion traffic records and 262 million weather records, to quantify the boost in accuracy of traffic prediction using weather data. We will provide an overview of our lambda architecture with Apache Spark being used to build prediction models with weather and traffic data, and Spark Streaming used to score the model and provide real-time traffic predictions. This talk will also cover a suite of extensions to Spark to analyze geospatial and temporal patterns in traffic and weather data, as well as the suite of machine learning algorithms that were used with Spark framework. Initial results of this work were presented at the National Association of Broadcasters meeting in Las Vegas in April 2017, and there is work to scale the system to provide predictions in over a 100 cities. Audience will learn about our experience scaling using Spark in offline and streaming mode, building statistical and deep-learning pipelines with Spark, and techniques to work with geospatial and time-series data.
Enabling Active Flow Manipulation (AFM) in Silicon-based Network Forwarding E...Tal Lavian Ph.D.
Programmable Internet:
Enhance internetworking functions.
Move computations into the network for value added services.
Manage the network more capably than possible with SNMP.
More quickly introduce Diffserv or Inserv to support new multimedia applications
Implement traffic control algorithms to support QoS.
The document is a resume for Akhilesh Kumar Pandey summarizing his qualifications and experience as an RF Optimization Engineer with over 9 years of experience in GSM, WCDMA, and LTE networks. It provides details of his current role as a Senior Network Engineer with Ericsson India along with previous roles and responsibilities handling RF optimization, planning, and performance monitoring. Technical skills and tools used are also listed.
With the rapid growth of IP networks in South-Asia in the past
few years, and the advent of new services and applications -- be they
wireless/wireline broadband Internet access, cable telephony, VoIP, remote
teleconferencing, e-governance, or mobile entertainment -- a key
issue before carriers is how to design and operate their networks as
methodically and as efficiently as possible to maximize both customer
retention and profits.
While several best practices typically emerge from each provider\'s
unique situation and cumulative experience (the "art" of network design), there
are certain operational precepts that systematize and streamline the
complex, multi-dimensional task of designing and managing modern, operational
IP networks (the "science" of network design).
In this talk, we first discuss the overall network design process and the
manner in which control over the network must be exercised at varying
timescales to achieve efficient operation. Next we discuss the
functions that the operational, engineering, and planning teams at a
carrier must typically execute, their inter-relationships, and
the importance/rationale for performing them to optimize network
performance.
We then outline some network design best practices that have evolved
over the past decade, drawing upon examples of carriers such as
Sprint, Global Crossing, AT&T, NTT, and Reliance. We conclude with
a look at some automated traffic engineering and planning tools,
and how they enable carriers to rapidly identify potential
performance problems, rigorously experiment with/evaluate design
options, perform thorough scenario and network analysis, and
develop robust designs.
DIY Netflow Data Analytic with ELK Stack by CL LeeMyNOG
This document discusses using the ELK stack (Elasticsearch, Logstash, Kibana) to analyze netflow data. It describes IP ServerOne's infrastructure managing over 5000 servers across multiple data centers. Netflow data is collected and sent to Logstash for processing, then stored in Elasticsearch for querying and visualization in Kibana. Examples are given of how the data can be used, such as identifying top talkers, traffic profiling by ASN, and troubleshooting with IP conversation history. The ELK stack is concluded to be a powerful yet not difficult tool for analyzing netflow traffic.
PLNOG 7: Ferenc Csorba - What’s new at the RIPE NCC?PROIDEA
This document provides an overview and update on various initiatives at the RIPE NCC, including: the depletion of IPv4 addresses, which is nearing exhaustion; updates to IPv6 policies and statistics showing growing IPv6 adoption; new tools like RIPEstat for analyzing registry data and RIPE Atlas for internet measurements; and changes to IPv4 and IPv6 allocation policies as resources dwindle. Key points include the RIPE NCC transitioning to allocating the final remaining /8 of IPv4 addresses and emphasizing IPv6 adoption and assignments.
Life in the Fast Lane: A Line-Rate Linear RoadAJAY KHARAT
Network hardware was simple and fixed.
Cannot change the underlying code.
As new generation of programmable switches which match the performance of fixed function devices has become commercially available
like consensus protocols, in-network caching etc..
One common feature of all these applications is that they depend on stateful computations.
If this trend continues—as appears likely—then it is worth identifying which abstractions are needed to support a more general form of stateful processing. How?
This document discusses segment routing and its benefits for incremental deployment in networks. It describes how segment routing uses MPLS or IPv6 routing headers to encode paths as ordered lists of segments. Segment routing allows more control over traffic paths compared to traditional IGP routing. It can enable traffic engineering and service chaining while maintaining network and control plane simplicity. The document argues segment routing is useful for scaling datacenters and simplifying peering relationships.
RouteFlow & IXPs
This talk will discuss the architecture of RouteFlow which is a leading OpenFlow based virtual router. It will focus on the new projects based upon RouteFlow which are finding traction in Internet eXchange Points (IXPs) - Cardigan being one of the most popular one. Some common aspects of IXPS will be shown. The talk will conclude with a list of future projects and vision of SDN routing.
About Raphael Vincent Rosa
Raphael is a Communications Network Engineer. He finished his MS in Computer Science working with intra datacenter routing, contributing to open source SDN projects such as Ryu network controller and RouteFlow platform. Currently he is pursuing PhD research under the guidance of Dr. Christian Esteve Rothenburg with main interests in SDN and Distributed-NFV topics.
Segment routing is a network technology focused on addressing the pain points of existing IP and Multiprotocol Label Switching (MPLS) networks in terms of simplicity, scale, and ease of operation. It’s a foundation for application engineered routing because it prepares the networks for new business models where applications can direct network behavior.
Segment routing seeks the right balance between distributed intelligence and centralized optimization and programming. It was built for the software-defined networking (SDN) era.
Segment routing enables enhanced packet forwarding behavior. It enables a network to transport unicast packets through a specific forwarding path, other than the normal shortest path that a packet usually takes. This capability benefits many use cases, and you can build those specific paths based on application requirements.
Segment routing uses the source routing paradigm. A node, usually a router but it can also be a switch, a trusted server, or a virtual forwarder running on a hypervisor, steers a packet through an ordered list of instructions, called segments. A segment can represent any instruction, topological or service-based. A segment can have a local semantic to a segment-routing node or global within a segment-routing network. Segment routing allows you to enforce a flow through any topological path and service chain while maintaining per-flow state only at the ingress node to the segment-routing network. To be aligned with modern IP networks, segment routing supports equal-cost multipath (ECMP) by design, and the forwarding within a segment-routing network uses all possible paths, when desired.
As a Performance Management Solution Platform specifically designed for Mobile Networks, both Focus and FocusWeb increase the visibility of all mobile network layer performance (RAN/UTRAN, Transport, Core) through a vendor-free environment, and support all access technologies (GSM, WCDMA and LTE). All-in-one features move Focus and FocusWeb ahead of their competitors.
Wide ranging functionalities including alerts, trends, degraded node data and trend templates make possible to track expert-level technically detailed information and oversee management level information, supported with GIS reporting.
This document summarizes the DevoFlow paper, which proposes techniques to scale flow management for high-performance networks. It finds that per-flow management in OpenFlow introduces high overheads. DevoFlow aims to balance network control, statistics collection, and switch overhead by devolving most flow control to switches while maintaining partial visibility of significant flows. Simulation results show DevoFlow can reduce flow scheduling overheads compared to per-flow control, while still achieving high performance.
Traffic Engineering in Software-Defined NetworksHai Dinh Tuan
1. The document discusses new opportunities and challenges for traffic engineering (TE) in software-defined networks (SDN). It outlines several research directions for TE techniques in SDN, including efficient flow management, fast recovery mechanisms, consistency during network updates, and low-overhead traffic analysis.
2. Specific TE techniques discussed include switch and controller load balancing for flow management, reactive and proactive data plane restoration for fault tolerance, and adaptive monitoring for traffic analysis. Consistency during network changes can be achieved using configuration versioning.
3. While SDN enables simpler, more flexible and reliable TE, open challenges remain around hybrid SDN implementations, incremental adoption, and the need for continued collaboration between academia and industry.
Mohammad Waqas Khan has over 5 years of experience as a 2G, 3G, and LTE RF engineer with ZTE in Pakistan, where he has led rollout projects and optimized networks through drive testing, parameter tuning, and troubleshooting issues. He has expertise in tools like TEMS, NETNUMEN, and CNO for measurements, analysis, and planning across various mobile technologies. Khan is looking for a role where he can further develop his engineering and management skills.
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)Apache Apex
This presentation will introduce usage of Apache Apex for Time Series & Data Ingestion Service by General Electric Internet of things Predix platform. Apache Apex is a native Hadoop data in motion platform that is being used by customers for both streaming as well as batch processing. Common use cases include ingestion into Hadoop, streaming analytics, ETL, database off-loads, alerts and monitoring, machine model scoring, etc.
Abstract: Predix is an General Electric platform for Internet of Things. It helps users develop applications that connect industrial machines with people through data and analytics for better business outcomes. Predix offers a catalog of services that provide core capabilities required by industrial internet applications. We will deep dive into Predix Time Series and Data Ingestion services leveraging fast, scalable, highly performant, and fault tolerant capabilities of Apache Apex.
Speakers:
- Venkatesh Sivasubramanian, Sr Staff Software Engineer, GE Predix & Committer of Apache Apex
- Pramod Immaneni, PPMC member of Apache Apex, and DataTorrent Architect
IPv4 addresses delegated in Indonesia have steadily increased from 2005 to 2015. As of 2015, Indonesia has received over 5 million IPv4 addresses. IPv4 address transfers allow addresses to be moved between organizations, with over 30 transfers processed for Indonesian organizations. Key requirements for transfers include the addresses being administered by APNIC and the recipient justifying their needs. Transfers can occur between APNIC members, other RIR members, and between APNIC and other NIRs.
Early-stage topological and technological choices for TSN-based communication...RealTime-at-Work (RTaW)
A main issue in the design of automotive communication architectures is that the most important design choices pertaining to the topology of the networks and the technologies to use (protocols, data rate, hardware) have to be made at a time when the communication requirements are not entirely known. Indeed, many functions only becomes available along the development cycle, and vehicle platforms have to support incremental evolutions of the embedded system that may not be fully foreseeable at the time design choices are made. The problem is becoming even more difficult and crucial with the introduction of dynamically evolving communication requirements requiring network re-configuration at run-time.
We present how the use of synthetic data, that is data generated programmatically based on past vehicle projects and what can be foreseen for the current project, enables the designers to make such early stage choices based on quantified metrics. The proposals are applied to Groupe Renault's FACE service-oriented E/E architecture with the use of the “Topology Stress Test” feature implemented in RTaW-Pegase.
This document summarizes a presentation on analyzing network traffic characteristics of data centers. Some key findings include:
- 75% of traffic stays within a single rack, showing applications are not uniformly placed;
- Half of all packets are small (<200B), indicating keep-alive traffic is important for applications;
- At most 25% of core network links are highly utilized, suggesting better routing could reduce utilization;
- Assumptions about needing more bandwidth between network switches (bisection) or that traffic is unpredictable may not always hold true.
This document is a resume for Adeel Ahmed, a 2G/3G/LTE RF engineer with almost 4 years of experience in network optimization and planning for cellular networks. It lists his contact information and objective, followed by a work history summarizing his roles optimizing networks for various telecom companies in Pakistan and the UAE. It also provides details of his educational background and technical skills.
Prefix Filtering Design Issues and Best Practise by Nurul IslamMyNOG
The document discusses best practices for prefix filtering design when receiving prefixes from upstream networks. It outlines four options for handling prefixes from customers: single-homed with non-portable prefixes, single-homed with portable prefixes, multi-homed with non-portable prefixes, and multi-homed with portable prefixes. For each option, it describes considerations for route filtering policies at the internet service provider and customer networks to filter routes and traffic appropriately based on the prefix and source autonomous system.
Improving Traffic Prediction Using Weather Data with Ramya RaghavendraSpark Summit
As common sense would suggest, weather has a definite impact on traffic. But how much? And under what circumstances? Can we improve traffic (congestion) prediction given weather data? Predictive traffic is envisioned to significantly impact how driver’s plan their day by alerting users before they travel, find the best times to travel, and over time, learn from new IoT data such as road conditions, incidents, etc. This talk will cover the traffic prediction work conducted jointly by IBM and the traffic data provider. As a part of this work, we conducted a case study over five large metropolitans in the US, 2.58 billion traffic records and 262 million weather records, to quantify the boost in accuracy of traffic prediction using weather data. We will provide an overview of our lambda architecture with Apache Spark being used to build prediction models with weather and traffic data, and Spark Streaming used to score the model and provide real-time traffic predictions. This talk will also cover a suite of extensions to Spark to analyze geospatial and temporal patterns in traffic and weather data, as well as the suite of machine learning algorithms that were used with Spark framework. Initial results of this work were presented at the National Association of Broadcasters meeting in Las Vegas in April 2017, and there is work to scale the system to provide predictions in over a 100 cities. Audience will learn about our experience scaling using Spark in offline and streaming mode, building statistical and deep-learning pipelines with Spark, and techniques to work with geospatial and time-series data.
Enabling Active Flow Manipulation (AFM) in Silicon-based Network Forwarding E...Tal Lavian Ph.D.
Programmable Internet:
Enhance internetworking functions.
Move computations into the network for value added services.
Manage the network more capably than possible with SNMP.
More quickly introduce Diffserv or Inserv to support new multimedia applications
Implement traffic control algorithms to support QoS.
The document is a resume for Akhilesh Kumar Pandey summarizing his qualifications and experience as an RF Optimization Engineer with over 9 years of experience in GSM, WCDMA, and LTE networks. It provides details of his current role as a Senior Network Engineer with Ericsson India along with previous roles and responsibilities handling RF optimization, planning, and performance monitoring. Technical skills and tools used are also listed.
With the rapid growth of IP networks in South-Asia in the past
few years, and the advent of new services and applications -- be they
wireless/wireline broadband Internet access, cable telephony, VoIP, remote
teleconferencing, e-governance, or mobile entertainment -- a key
issue before carriers is how to design and operate their networks as
methodically and as efficiently as possible to maximize both customer
retention and profits.
While several best practices typically emerge from each provider\'s
unique situation and cumulative experience (the "art" of network design), there
are certain operational precepts that systematize and streamline the
complex, multi-dimensional task of designing and managing modern, operational
IP networks (the "science" of network design).
In this talk, we first discuss the overall network design process and the
manner in which control over the network must be exercised at varying
timescales to achieve efficient operation. Next we discuss the
functions that the operational, engineering, and planning teams at a
carrier must typically execute, their inter-relationships, and
the importance/rationale for performing them to optimize network
performance.
We then outline some network design best practices that have evolved
over the past decade, drawing upon examples of carriers such as
Sprint, Global Crossing, AT&T, NTT, and Reliance. We conclude with
a look at some automated traffic engineering and planning tools,
and how they enable carriers to rapidly identify potential
performance problems, rigorously experiment with/evaluate design
options, perform thorough scenario and network analysis, and
develop robust designs.
DIY Netflow Data Analytic with ELK Stack by CL LeeMyNOG
This document discusses using the ELK stack (Elasticsearch, Logstash, Kibana) to analyze netflow data. It describes IP ServerOne's infrastructure managing over 5000 servers across multiple data centers. Netflow data is collected and sent to Logstash for processing, then stored in Elasticsearch for querying and visualization in Kibana. Examples are given of how the data can be used, such as identifying top talkers, traffic profiling by ASN, and troubleshooting with IP conversation history. The ELK stack is concluded to be a powerful yet not difficult tool for analyzing netflow traffic.
PLNOG 7: Ferenc Csorba - What’s new at the RIPE NCC?PROIDEA
This document provides an overview and update on various initiatives at the RIPE NCC, including: the depletion of IPv4 addresses, which is nearing exhaustion; updates to IPv6 policies and statistics showing growing IPv6 adoption; new tools like RIPEstat for analyzing registry data and RIPE Atlas for internet measurements; and changes to IPv4 and IPv6 allocation policies as resources dwindle. Key points include the RIPE NCC transitioning to allocating the final remaining /8 of IPv4 addresses and emphasizing IPv6 adoption and assignments.
Life in the Fast Lane: A Line-Rate Linear RoadAJAY KHARAT
Network hardware was simple and fixed.
Cannot change the underlying code.
As new generation of programmable switches which match the performance of fixed function devices has become commercially available
like consensus protocols, in-network caching etc..
One common feature of all these applications is that they depend on stateful computations.
If this trend continues—as appears likely—then it is worth identifying which abstractions are needed to support a more general form of stateful processing. How?
This document discusses segment routing and its benefits for incremental deployment in networks. It describes how segment routing uses MPLS or IPv6 routing headers to encode paths as ordered lists of segments. Segment routing allows more control over traffic paths compared to traditional IGP routing. It can enable traffic engineering and service chaining while maintaining network and control plane simplicity. The document argues segment routing is useful for scaling datacenters and simplifying peering relationships.
RouteFlow & IXPs
This talk will discuss the architecture of RouteFlow which is a leading OpenFlow based virtual router. It will focus on the new projects based upon RouteFlow which are finding traction in Internet eXchange Points (IXPs) - Cardigan being one of the most popular one. Some common aspects of IXPS will be shown. The talk will conclude with a list of future projects and vision of SDN routing.
About Raphael Vincent Rosa
Raphael is a Communications Network Engineer. He finished his MS in Computer Science working with intra datacenter routing, contributing to open source SDN projects such as Ryu network controller and RouteFlow platform. Currently he is pursuing PhD research under the guidance of Dr. Christian Esteve Rothenburg with main interests in SDN and Distributed-NFV topics.
Segment routing is a network technology focused on addressing the pain points of existing IP and Multiprotocol Label Switching (MPLS) networks in terms of simplicity, scale, and ease of operation. It’s a foundation for application engineered routing because it prepares the networks for new business models where applications can direct network behavior.
Segment routing seeks the right balance between distributed intelligence and centralized optimization and programming. It was built for the software-defined networking (SDN) era.
Segment routing enables enhanced packet forwarding behavior. It enables a network to transport unicast packets through a specific forwarding path, other than the normal shortest path that a packet usually takes. This capability benefits many use cases, and you can build those specific paths based on application requirements.
Segment routing uses the source routing paradigm. A node, usually a router but it can also be a switch, a trusted server, or a virtual forwarder running on a hypervisor, steers a packet through an ordered list of instructions, called segments. A segment can represent any instruction, topological or service-based. A segment can have a local semantic to a segment-routing node or global within a segment-routing network. Segment routing allows you to enforce a flow through any topological path and service chain while maintaining per-flow state only at the ingress node to the segment-routing network. To be aligned with modern IP networks, segment routing supports equal-cost multipath (ECMP) by design, and the forwarding within a segment-routing network uses all possible paths, when desired.
As a Performance Management Solution Platform specifically designed for Mobile Networks, both Focus and FocusWeb increase the visibility of all mobile network layer performance (RAN/UTRAN, Transport, Core) through a vendor-free environment, and support all access technologies (GSM, WCDMA and LTE). All-in-one features move Focus and FocusWeb ahead of their competitors.
Wide ranging functionalities including alerts, trends, degraded node data and trend templates make possible to track expert-level technically detailed information and oversee management level information, supported with GIS reporting.
This document summarizes the DevoFlow paper, which proposes techniques to scale flow management for high-performance networks. It finds that per-flow management in OpenFlow introduces high overheads. DevoFlow aims to balance network control, statistics collection, and switch overhead by devolving most flow control to switches while maintaining partial visibility of significant flows. Simulation results show DevoFlow can reduce flow scheduling overheads compared to per-flow control, while still achieving high performance.
Traffic Engineering in Software-Defined NetworksHai Dinh Tuan
1. The document discusses new opportunities and challenges for traffic engineering (TE) in software-defined networks (SDN). It outlines several research directions for TE techniques in SDN, including efficient flow management, fast recovery mechanisms, consistency during network updates, and low-overhead traffic analysis.
2. Specific TE techniques discussed include switch and controller load balancing for flow management, reactive and proactive data plane restoration for fault tolerance, and adaptive monitoring for traffic analysis. Consistency during network changes can be achieved using configuration versioning.
3. While SDN enables simpler, more flexible and reliable TE, open challenges remain around hybrid SDN implementations, incremental adoption, and the need for continued collaboration between academia and industry.
Mohammad Waqas Khan has over 5 years of experience as a 2G, 3G, and LTE RF engineer with ZTE in Pakistan, where he has led rollout projects and optimized networks through drive testing, parameter tuning, and troubleshooting issues. He has expertise in tools like TEMS, NETNUMEN, and CNO for measurements, analysis, and planning across various mobile technologies. Khan is looking for a role where he can further develop his engineering and management skills.
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)Apache Apex
This presentation will introduce usage of Apache Apex for Time Series & Data Ingestion Service by General Electric Internet of things Predix platform. Apache Apex is a native Hadoop data in motion platform that is being used by customers for both streaming as well as batch processing. Common use cases include ingestion into Hadoop, streaming analytics, ETL, database off-loads, alerts and monitoring, machine model scoring, etc.
Abstract: Predix is an General Electric platform for Internet of Things. It helps users develop applications that connect industrial machines with people through data and analytics for better business outcomes. Predix offers a catalog of services that provide core capabilities required by industrial internet applications. We will deep dive into Predix Time Series and Data Ingestion services leveraging fast, scalable, highly performant, and fault tolerant capabilities of Apache Apex.
Speakers:
- Venkatesh Sivasubramanian, Sr Staff Software Engineer, GE Predix & Committer of Apache Apex
- Pramod Immaneni, PPMC member of Apache Apex, and DataTorrent Architect
IPv4 addresses delegated in Indonesia have steadily increased from 2005 to 2015. As of 2015, Indonesia has received over 5 million IPv4 addresses. IPv4 address transfers allow addresses to be moved between organizations, with over 30 transfers processed for Indonesian organizations. Key requirements for transfers include the addresses being administered by APNIC and the recipient justifying their needs. Transfers can occur between APNIC members, other RIR members, and between APNIC and other NIRs.
Early-stage topological and technological choices for TSN-based communication...RealTime-at-Work (RTaW)
A main issue in the design of automotive communication architectures is that the most important design choices pertaining to the topology of the networks and the technologies to use (protocols, data rate, hardware) have to be made at a time when the communication requirements are not entirely known. Indeed, many functions only becomes available along the development cycle, and vehicle platforms have to support incremental evolutions of the embedded system that may not be fully foreseeable at the time design choices are made. The problem is becoming even more difficult and crucial with the introduction of dynamically evolving communication requirements requiring network re-configuration at run-time.
We present how the use of synthetic data, that is data generated programmatically based on past vehicle projects and what can be foreseen for the current project, enables the designers to make such early stage choices based on quantified metrics. The proposals are applied to Groupe Renault's FACE service-oriented E/E architecture with the use of the “Topology Stress Test” feature implemented in RTaW-Pegase.
This document summarizes a presentation on analyzing network traffic characteristics of data centers. Some key findings include:
- 75% of traffic stays within a single rack, showing applications are not uniformly placed;
- Half of all packets are small (<200B), indicating keep-alive traffic is important for applications;
- At most 25% of core network links are highly utilized, suggesting better routing could reduce utilization;
- Assumptions about needing more bandwidth between network switches (bisection) or that traffic is unpredictable may not always hold true.
This document discusses key performance indicators (KPIs) for monitoring base station subsystems in EGPRS networks. It introduces EGPRS technology and defines KPI groups for traffic, availability, accessibility, and quality. Laboratory measurements were conducted to examine which BSS KPIs best reflect network performance and end-user experience by comparing application throughput to KPI values. The results showed that RLC throughput accurately described FTP throughput under different radio conditions. Multiple KPIs should be used to analyze radio link quality as one KPI cannot fully capture end-user experience.
Routing, Network Performance, and Role of AnalyticsAPNIC
This document discusses how route analytics can help address challenges in operating software-defined networks (SDNs) and implementing bandwidth scheduling applications. It describes how a naive bandwidth scheduling approach could lead to network congestion issues and outlines how route analytics can provide richer information like traffic demand matrices and routing models to simulate failures and ensure spare bandwidth is not overcommitted. Route analytics is presented as key to developing analytics-driven SDN applications by providing visibility into routing impacts on performance, traffic flows, and failure response.
Google operates 13 global data centers that require massive bandwidth for data replication and storage. Google faced challenges with the inflexible and inefficient architecture of traditional networks. Google implemented a Software Defined Wide Area Network (SDWAN) using OpenFlow and a centralized control approach. The SDWAN includes a global bandwidth broker, traffic engineering server, SDN gateways, and integration with existing routing protocols. This provides optimized traffic routing, faster convergence on failures, and 95% link utilization while connecting all data centers as a single logical network.
The document discusses Juniper's WANDL and NorthStar solutions for network operators. It provides an overview of the key capabilities of each solution, including:
- WANDL's IP/MPLS View allows operators to design, plan, monitor and optimize multi-vendor Layer 3 networks. It provides network modeling, traffic analysis and automated provisioning capabilities.
- NorthStar combines WANDL's path computation with Juniper's dynamic IP control plane to enable stateful traffic engineering. It provides optimized routing using a centralized path computation approach.
- Both solutions help operators improve network performance, redundancy and efficiency through capabilities like failure simulation, capacity planning, high availability assessment and traffic engineering.
IPLC Analytic Dashboard - Mohd Rizal bin Mohd RamlyMyNOG
The document discusses developing an analytic dashboard for analyzing TM Berhad's International Private Leased Circuit (IPLC) capacity. Key objectives are to have a single monitoring dashboard for the network operations center to analyze IPLC capacity needs, perform failure analysis more quickly, and use advanced analytics like clustering and congestion prediction. Currently, analysis is done manually using performance monitoring tools and spreadsheets, which is time-consuming. The proposed dashboard would automate analysis and reporting to help optimize IPLC capacity planning and routing.
This document provides information on the capabilities of Software Quality Leaders (SQL), a telecom solutions group, including:
1. SQL offers indoor/outdoor wireless network planning, design, installation, testing, commissioning, optimization, and support maintenance services for in-building and distributed antenna systems.
2. Their capabilities include in-house engineering and installation teams, radio frequency requirement analysis, propagation modeling, and turnkey project management.
3. SQL also provides Wi-Fi offloading solutions to help mobile operators integrate Wi-Fi access points with their cellular networks to increase capacity and reduce costs.
LinkedIn serves traffic for its 467 million members from four data centers and multiple PoPs spread geographically around the world. Serving live traffic from from many places at the same time has taken us from a disaster recovery model to a disaster avoidance model where we can take an unhealthy data center or PoP out of rotation and redistribute its traffic to a healthy one within minutes, with virtually no visible impact to users. The geographical distribution of our infrastructure also allows us to optimize the end-user's experience by geo routing users to the best possible PoP and datacenter.
This talk provide details on how LinkedIn shifts traffic between its PoPs and data centers to provide the best possible performance and availability for its members. We will also touch on the complexities of performance in APAC, how IPv6 is helping our members and how LinkedIn stress tests data centers verify its disaster recovery capabilities.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Accelerated development in Automotive E/E Systems using VisualSim ArchitectDeepak Shankar
The recent trends and developments in the automotive sector towards fully autonomous diving system and vehicle to vehicle (V2V) communication would mean a drastic increase in the number of sensors, increased number of ECUs, increased concern for safety and security. This calls for the need to perform thorough evaluations on the target system architecture, at all levels - Hardware, Software and Network. During this webinar, we show how we evaluate each of these aspects of the Automotive E/E system and take a closer look at the performance, power and functional correctness of each of the auto subsystems. We will also inject faults into the demo model, which will tell us how the automotive system would perform under failure.
The webinar also showcases various Use case examples, which includes - comparison of TSN Standards, modelling of various topology, task graph modelling, glimpses into TC10 sleep-wakeup standard and integrated software.
The Need for Complex Analytics from Forwarding Pipelines Netronome
Nic Viljoen, Research Engineer, (including Tom Tofigh and Bryan Sullivan form AT&T) presentation from ONS 2016 at Santa Clara Convention Center in Santa Clara, CA.
Network-aware Data Management for Large Scale Distributed Applications, IBM R...balmanme
The document discusses network-aware data management for large-scale distributed applications. It provides an outline for a presentation on this topic, including discussing the performance of VSAN and VVOL storage in virtualized environments, the PetaShare distributed storage system and Stork data scheduler, data streaming in high-bandwidth networks, and several other related topics like network reservations and scheduling. The presenter's background and experience working on data transfer scheduling, distributed storage, and high-performance computing networks is also briefly summarized.
Transport SDN Overview and Standards Update: Industry PerspectivesInfinera
This document provides an overview and update on transport SDN standards. It discusses:
1) The evolving core network landscape including 100Gb coherent technology and bandwidth needs for cloud services.
2) Transport SDN can provide dynamic network programmability and unified control over multi-layer, multi-vendor networks.
3) Key applications for transport SDN include networking as a service, virtual transport networks, and multi-layer orchestration.
Malik MD Nurani has over 10 years of experience in RF planning and optimization for 5G NSA, LTE, VoLTE, WCDMA, and GSM networks. He has expertise in tools such as TEMS, Mentum, ATOLL, MCOM, and ACTIX. Currently he works as a Senior RF Engineer at Vodafone Idea, where his responsibilities include drive test analysis, parameter tuning, and troubleshooting to achieve KPI targets and improve network quality. Previously he held optimization roles at Reliance Jio, Huawei, and ZTE, where he performed activities such as coverage optimization, carrier aggregation deployment, and VoLTE parameter tuning.
Similar to PLNOG 3: John Evans - Best Practices in Network Planning (20)
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.