Network data packet processing

Sensors, 2021

One of the most challenging tasks for network operators is implementing accurate per-packet monitoring, looking for signs of performance degradation, security threats, and so on. Upon critical event detection, corrective actions must be taken to keep the network running smoothly. Implementing this mechanism requires the analysis of packet streams in a real-time (or close to) fashion. In a softwarized network context, Stream Processing Systems (SPSs) can be adopted for this purpose. Recent solutions based on traditional SPSs, such as Storm and Flink, can support the definition of general complex queries, but they show poor performance at scale. To handle input data rates in the order of gigabits per seconds, programmable switch platforms are typically used, although they offer limited expressiveness. With the proposed approach, we intend to offer high performance and expressive power in a unified framework by solely relying on SPSs for multicores. Captured packets are translated into...

A method of supporting mobility in an Internet Protocol (IP)-based data network. The method comprises the steps of generating a first stateful IP autoconfiguration message at a mobile node, whereby the message includes an address capable of use for routing maintenance. The mobile node transmits the generated message to a first access node, which incorporates its address and forwards the message to a dynamic host configuration protocol (DHCP) Server. The DHCP Server and access node analyze the message to determine a route to deliver data to and/or from the mobile node. One or more route update message are triggered from said access node and said DHCP server to a number of network elements between said access node and said DHCP server in the IP based data network to support mobility in an IP domain with minimum bandwidth use and minimum tunneling required.

for computer communication

Proceedings of the 4th ACM/IEEE Symposium on Architectures for Networking and Communications Systems - ANCS '08, 2008

Mostly emerging network applications comprise deep packet inspection and/or stateful capabilities. Stateful workloads present limitations that reduce the exploitation of parallelism, unlike other network applications that show marginal dependencies among packets. In addition, differences among packet processing lead to significant negative interaction between threads, especially in the memory hierarchy. We propose MultiLayer Processing (MLP) as an execution model to properly exploit the levels of parallelism of stateful applications. The goal of MLP is to increase the system throughput by increasing the synergy among threads in the memory hierarchy, and alleviating the contention in critical sections of parallel workloads. We show that MLP presents about 2.4x higher throughput than other execution models with large processor architectures.

Data communications refers to the transmission of this digital data between two or more computers and a computer network or data network is a telecommunications network that allows computers to exchange data. The physical connection between networked computing devices is established using either cable media or wireless media. The best-known computer network is the Internet.

2002

sion protocols used. These protocols operate on the so-called network layer of communication. At the network layer data is fragmented into packets. Each packet is equipped with a header. Among other things, the header describes its sender, its receiver, and possibly its relative or absolute position within the entity it came from. The network layer of communication operates on top of the physical layer, which is responsible for sending the individual bits of the data. I will not talk about the pysical layer in this note.

Proceedings of the June 7-10, 1976, national computer conference and exposition on - AFIPS '76, 1976

Public packet switching networks are at various stages of development around the world, notably in the U.S., Canada, France, the United Kingdom and Japan. The success of these networks is highly dependent on the use of an agreed-upon standard device-independent interface between the packet networks and the user devices operating in the packet-mode. This interface consists of far more than the data link control procedure (Le., HDLC), which administers the physical transmission medium between the data terminal equipment (DTE) and the network. The specification of the packet-mode interface defines a set of conventions governing the manner in which DTEs establish, maintain and clear calls, format control information and data into packets and manage the flow of data for many calls over a single circuit to and from the packet network. This paper describes the International Packet-Mode Interface, developed jointly by Telenet Communications Corp., the Trans-Canada Telephone System (TCTS), the United Kingdom Post Office and the French PTT. This interface has been designed to enable DTEs such as computers, programmable terminal controllers and intelligent terminals to gain access to public packet networks throughout the world. The present status of international standardization of this interface within the CCITT is also covered. Standardization of the International Packet-Mode Interface is to the advantage of teleprocessing users, 477 manufacturers of data processing and terminal equipment and common carriers.

IEEE Communications Surveys & Tutorials, 2018

The exponential growth of data traffic, which is not expected to stop anytime soon, brought about a vast amount of advancements in the networking field. Latest network interfaces support data rates in the range of 40Gbps and higher. This, however, does not guarantee higher packet processing speeds which are limited due to the overheads imposed by the architecture of the network stack. Nevertheless, there is a great need for a speedup in the forwarding engine, which is the most important part of a high-speed router. For this reason, many softwarebased and hardware-based solutions have emerged recently with a goal of increasing packet processing speeds. An operating system's networking stack is conceived for general purpose communications rather than high-speed networking applications. In this paper, we investigate multiple approaches that attempt to improve packet processing performance on serverclass network hosts, either by using software, hardware, or the combination of the two. We survey various solutions, among which some are based on the Click modular router, which offloads its functions on different types of hardware like GPUs, FPGAs or different cores among different servers with parallel execution. Furthermore, we explore other software solutions which are not based on the Click modular router. We compare them in terms of the domain in which they operate (user-space or kernelspace). Then we compare them based on their use of zerocopy techniques, batch packet processing and parallelism. We also discuss different hardware solutions and compare them additionally in terms of the type of hardware that they use, their usage of CPU and how they connect with it. Furthermore, we discuss the integration possibilities in virtualized environments of the described solutions, their constraints and their requirements. At last, we discuss the latest approaches and the future directions in the field of fast packet processing.

The different stages in Data Processing are as follows: 1) Collection is the first stage of the cycle, and is very crucial, since the quality of data collected will impact heavily on the output. The collection process needs to ensure that the data gathered are both defined and accurate, so that subsequent decisions based on the findings are valid. This stage provides both the baseline from which to measure, and a target on what to improve. Some types of data collection include census (data collection about everything in a group or statistical population), sample survey (collection method that includes only part of the total population), and administrative by-product (data collection is a byproduct of an organization's day-today operations). 2) Preparation is the manipulation of data into a form suitable for further analysis and processing. Raw data cannot be processed and must be checked for accuracy. Preparation is about constructing a dataset from one or more data sources to be used for further exploration and processing. Analyzing data that has not been carefully screened for problems can produce highly misleading results that are heavily dependent on the quality of data prepared. 3) Input is the task where verified data is coded or converted into machine readable form so that it can be processed through a computer. Data entry is done through the use of a keyboard, digitizer, scanner, or data entry from an existing source. This time-consuming process requires speed and accuracy. Most data need to follow a formal and strict syntax since a great deal of processing power is required to breakdown the complex data at this stage. Due to the costs, many businesses are resorting to outsource this stage. 4) Processing is when the data is subjected to various means and methods of manipulation, the point where a computer program is being executed, and it contains the program code and its current activity. The process may be made up of multiple threads of execution that simultaneously execute instructions, depending on the operating system. While a computer program is a passive collection of instructions, a process is the actual execution of those