A logic for graphs with qos

What Is QoS? Meaning and Best Quality of Service Tools 2020

Bandwidth and power hungry applications are proliferating in mobile networks at a rapid pace. In addition, the mobile ecosystem is currently heterogeneous and comprises a plethora of networks with different technologies such as LTE, Wi-Fi, and WiMaX.

Hence, an issue must be addressed to ensure that quality of experience QoE is provided for the users in this scenario: an energy-efficient strategy that is designed to extend the battery lifetime of mobile devices. This paper proposes an architecture which provides an intelligent decision-making support system based on Fuzzy Logic for saving the energy of mobile devices within an integrated LTE and Wi-Fi network.

The simulated experiments show the benefits of the solution this architecture can provide by using QoE metrics. The increasing demand for new services, technologies, and content is changing the way users obtain access to the Internet. The popularization of the use of multimedia applications, together with the increase in the number of mobile users, makes it essential to supply services with a high transmission rate and improved quality.

Both in the current climate and in the future, the wireless network environment will be based on the coexistence of multiple networks that provide access to a wide range of technologies such as Bluetooth, Wi-Fi, WiMAX, and LTE.

This will be a place where mobile users, equipped with devices supporting multiple network interfaces, will be able to obtain access to multimedia services through different access networks by means of the radio. In other words, the heterogeneity of a wireless environment provides the opportunity to assess and select the best network from a range of others, on the basis of the required conditions of a multimedia service.

a logic for graphs with qos

In light of this, handover is a procedure that allows a mobile device to be disconnected from a network so that it can be connected to another. Its goal is to allow mobile users to be always connected ABC, Always Best Connected [ 2 ] to a network, so that their application can keep operating while they are relocating between different places.

When the decoupling and connection involve the same network technologies, the phenomenon is called horizontal handover, whereas vertical handover involves the use of different technologies. Since users want a better multimedia experience in their mobile devices, the delivery of video of a high quality is a more challenging task in wired networks.

This is also owing to restrictions and mobility behavior and the environment of heterogeneous wireless networks itself; however, it mainly lies in the challenge of meeting the required conditions for multimedia applications with regard to the transfer of data and ensuring low latency and an insignificant loss.

The decision of when and where to carry out the handover will depend on several factors or attributes such as the following: QoS Quality of ServiceRSS Received Signal Strengthbandwidth, the battery consumption rate, and mobile user speed. The concept of Quality of Experience QoE is becoming a key factor because it can measure the degree of quality of a multimedia service through the perception of the user.

In other words, the satisfaction of the user can be measured through required conditions based on social psychology, cognitive science, and engineering science [ 3 ]. Expectations about satisfaction for different services and application vary among different users. The traditional concept of QoS fails to take account of the fact that the satisfactions of the user should be used as an indicator, or, rather, it is only concerned with the network properties through metrics designed for the delivery of content [ 14 — 16 ].

This means that QoE should be an important attribute to take into account in the handover decision-making process.We suggest a formal model to represent and solve the multicast routing problem in multicast networks. To attain this, we model the network adapting it to a weighted and-or graph, where the weight on a connector corresponds to the cost of sending a packet on the network link modelled by that connector.

Then, we use the Soft Constraint Logic Programming SCLP framework as a convenient declarative programming environment in which to specify related problems. In particular, we show how the semantics of an SCLP program computes the best tree in the corresponding and-or graph: this result can be adopted to find, from a given source node, the multicast distribution tree having minimum cost and reaching all the destination nodes of the multicast communication.

The costs on the connectors can be described also as vectors multidimensional costseach component representing a different Quality of Service metric value. Therefore, the construction of the best tree may involve a set of criteria, all of which are to be optimized multi-criteria probleme.

Location of Repository. Provided by: CiteSeerX. Suggested articles.The sheer volume of applications and devices on the market, paired with the rise of social media, has led to a flood of network traffic, putting network performance in jeopardy. As a result, IT departments are bombarded with service requests regarding pesky delays, broken images, dropped calls, and fragmented video conferences, all of which bring productivity to a standstill.

This is where QoS, meaning quality of service, in networking comes into play. Folded into most network monitoring tools is the ability to manage and monitor network traffic by a class of service methods. These QoS monitoring tools can empower system administrators to determine whether the QoS policies they have in place are effectively prioritizing traffic and providing a positive end-user experience.

To truly understand the role of quality of service in networking, we must look at the meaning of QoS in general. I like to think of QoS as a form of traffic control.

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If delayed, FTP packets will still arrive intact. A delayed VoIP packet, on the other hand, runs the risk of arriving fragmented, ultimately resulting in disjointed video calls and ineffective business meetings.

To better manage the mountainous amount of data packets traveling across a network, QoS policing has developed. Think of QoS policies as the traffic cop directing drivers during a busy 5K road race. In the same way, a traffic cop evaluates when to prioritize drivers versus runners, QoS policies allow network administrators to prioritize which applications should receive delivery preference over others.

QoS policies are required for any company relying on latency-sensitive applications—think media streaming, host video calls, and so on—within their daily operations. Without QoS policies in place, the quality of the data delivered can be greatly compromised. QoS helps system administrators optimize their network performance and remain compliant by performing several key functions, including:.

Integrative services IntServ and differentiated services DiffServ models empower administrators to put QoS into play and manage their network traffic.

With IntServ, applications must request a resource reservation such as bandwidth for each data flow before sending data. If accepted, the application data can flow as long as it remains within the initially requested traffic profile. One word of warning: while IntServ is an effective method of QoS policing, it consumes numerous network resources and thus is not recommended for companies looking to scale their operations.

DiffServ is probably the most common QoS model. Unlike IntServ, DiffServ can easily be scaled, making it the go-to choice for many system administrators. Both DiffServ and IntServ rely on QoS mechanisms to perform their optimization duties and fulfill application requirements. To reap the full benefits of QoS models and mechanisms prioritizing network traffic, system administrators must keep their finger on the pulse of their network.

Network performance analyzers provide IT teams with a comprehensive view of their network traffic in real-time, so they can quickly pinpoint issues and take proactive measures to prevent them from reoccurring. The following are my favorite QoS tools of This comprehensive traffic monitoring platform captures data from network traffic streams and translates it into easy-to-digest charts and graphs, empowering system administrators with actionable information pertaining to their network health and performance.

With NetFlow Traffic Analyzer, administrators can quickly discover traffic patterns, identify applications hogging the bandwidth, and gain clear visibility into traffic types, helping them spot corrupted traffic from cyberattackers more readily.

This is critical for those seeking to analyze the success of their QoS policy and ensure all existing policies are performing effectively. Having this information at hand will allow the administrator to more quickly remedy the issue and prevent it from reoccurring, boosting the end-user experience.

NetFlow Traffic Analyzer is highly intuitive while still providing in-depth and highly valuable insights. I recommend giving the day free trial a try.

Having access to this level of data helps IT technicians maintain their network performance and keep traffic flowing smoothly.

QoS Marking on Cisco IOS Router

With PRTG, system administrators can glean an inclusive view of their network traffic, packets, applications, devices, bandwidth, IPs, and more, making this a great tool for those who are looking for a full suite of services.This article describes how to perform network traffic monitoring based on business criteria.

First it describes the underlying principle, then it introduces some example business logic and finally the whole application is monitored using Wireshark network protocol analyser. The basic idea of the fine-grained business-oriented network traffic monitoring is to pair specific business logic with a specific network address. In this example we'll pair individual business feeds with specific TCP ports.

Let's say we want to distribute messages from a stock exchange to the traders. We'll consider only three distinct message feeds. Stock quotes are messages meant to inform trader about the current prices of the stock. Order confirmations let the trader know that his orders to buy or sell the stock were accepted by the exchange. Trades are notifications that the orders were executed i.

Each of these message feeds will be associated with a specific TCP port number. In our example code stock quotes are transferred on portorder confirmations on port and trades on port IP port number being a part of TCP packet header is easy to monitor even on the lowest layers of the stack either hardware of software.

Monitoring program or hardware device simply checks two bytes at exact offset in each TCP packet "source port" field and updates the statistics accordingly. While this approach seems simple and self-evident, most business messaging solutions are incapable of it. For a discussion of traditional vs. In this example we will use two simple test programs simulating the communication between stock exchange and trader. There can be several instances of monrecv stock trader running in parallel:.

What follows is the monsend code. All the messages are 10 bytes long. We don't even care to fill in the message body as it's just an example so exact content of the message is irrelevant. Also note the sleep period after each message 1ms. The intent is to get decent data flows to monitor rather then completely congested environment. As for the monrecv program, it's even simpler. It receives from all three message feeds.

Then it retrieves the messages and drops them immediately as they arrive:. First, run monsend application. Then run monrecv application. The code above is written to use loopback interface so both applications have to be run on the same box. At this point the application is running, passing messages from monsend to monrecv. We can start monitoring the traffic. Run Wireshark monitoring tool and start capturing packets on the loopback interface "lo".

Open the statistics window Statistics IO Graphs. Fill in appropriate filters to show the three feeds we are interested in - stock quotes at portorder confirmations at porttrades at port Red line represents stock quotes, green line represents order confirmations, blue line represents trades. The statistics are charted using bytes per 0. Results obtained by the monitoring can be used simply to be informed of the actual bandwidth requirements of the application.

However, you can use them as well to analyse and improve overall design of the application data flow. For example, we may be concerned about the bandwidth consumed by stock quotes red line. The fact can make us consider using PGM reliable multicast protocol instead of TCP for stock quotes - multicast would use constant amount of network bandwidth no matter how many instances of monrecv are running.This article shows how you can work with data in your logic apps by adding actions for these tasks and more:.

If you don't find the action you want here, try browsing the many various data manipulation functions that Azure Logic Apps provides. These tables summarize the data operations you can use and are organized based on the source data types that the operations work on, but each description appears alphabetically.

An Azure subscription. If you don't have a subscription, sign up for a free Azure account.

a logic for graphs with qos

If you're new to logic apps, review What is Azure Logic Apps? A trigger as the first step in your logic app. Data operations are available only as actions, so before you can use these actions, start your logic app with a trigger and include any other actions required for creating the outputs you want.

a logic for graphs with qos

To construct a single output such as a JSON object from multiple inputs, you can use the Compose action. You can then use the output in actions that follow after the Compose action. The Compose action can also save you from repeatedly entering the same inputs while you build your logic app's workflow.

For example, you can construct a JSON message from multiple variables, such as string variables that store people's first names and last names, and an integer variable that stores people's ages.

Here, the Compose action accepts these inputs:. To try an example, follow these steps by using the Logic App Designer. Or, if you prefer working in the code view editor, you can copy the example Compose and Initialize variable action definitions from this article into your own logic app's underlying workflow definition: Data operation code examples - Compose. This example uses the Azure portal and a logic app with a Recurrence trigger and several Initialize variable actions. These actions are set up for creating two string variables and an integer variable.

When you later test your logic app, you can manually run your app without waiting for the trigger to fire. Select the plus sign, and then select Add an action. Under Choose an actionin the search box, enter compose as your filter. From the actions list, select the Compose action.

For this example, when you click inside the Inputs box, the dynamic content list appears so you can select the previously created variables:.

For more information about this action in your underlying workflow definition, see the Compose action.

To confirm whether the Compose action creates the expected results, send yourself a notification that includes output from the Compose action. In your logic app, add an action that can send you the results from the Compose action.

In that action, click anywhere you want the results to appear.We suggest a formal model to represent and solve the multicast routing problem in multicast networks. To attain this, we model the network adapting it to a weighted and-or graph, where the weight on a connector corresponds to the cost of sending a packet on the network link modelled by that connector. Then, we use the Soft Constraint Logic Programming SCLP framework as a convenient declarative programming environment in which to specify related problems.

a logic for graphs with qos

In particular, we show how the semantics of an SCLP program computes the best tree in the corresponding and-or graph: this result can be adopted to find, from a given source node, the multicast distribution tree having minimum cost and reaching all the destination nodes of the multicast communication.

The costs on the connectors can be described also as vectors multidimensional costseach component representing a different Quality of Service metric value. Therefore, the construction of the best tree may involve a set of criteria, all of which are to be optimized multi-criteria probleme.

Documents: Advanced Search Include Citations. Abstract We suggest a formal model to represent and solve the multicast routing problem in multicast networks. Powered by:.You can follow this link to learn more about the boolean logic. The modules on this site are automatically indexed from npm. If you have a concern about this module, please let us know.

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Or from the Node-RED's palette, search for "node-red-contrib-bool-gate". The boolean logic is a way to determine a condition regarding to the input. Node Info Version: 1. View on npm. Downloads 46 in the last day. Keywords node-red logic and or not xor bool boolean gate. Maintainers truc. Report this module The modules on this site are automatically indexed from npm. Please provide some details about the module:. Cancel Report. Node-RED : Low-code programming for event-driven applications.

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