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Lesson 5 Enhancing performance with QoS
Objective Define how QoS enhances network performance.

Enhancing performance with QoS

Data traffic routed across an IP network might have to travel through a series of routers. By default, each router in the path handles the traffic on a first-come, first-served (best-effort) basis. Time-sensitive streams of data such as video streaming, real-time audio, and video conferencing require a regular flow rate across the network, and will not work properly if their packets have to wait in line at a busy router.
The Windows 2000 implementation of QoS provides selectable bandwidth reservation and priority levels for traffic flows. QoS provides a unidirectional mechanism by which you can manage network resources, whether on the local LAN segment, the core network, or the WAN--to provide the required service levels. QoS can run on any network topology that supports TCP/IP.
The following Slide Show explains when designers can use QoS.
Quality of Service 1
1) Quality of Service 1
Quality of Service 2
2) Quality of Service 2
Quality of Service 3
3) Quality of Service 3
Quality of Service 4
4) Quality of Service 4

QOS Implementation
All routers in the path between a sender and receiver must be able to support QoS, and must validate the bandwidth requirement before a QoS session can be established. Include QoS in your design if:
  1. Bandwidth allocation is required
  2. QoS is supported by your planned applications
  3. All intermediate routers support Resource Reservation Protocol (RSVP)

Network Architect

As a network architect, you need to consider QoS in your design to support high-bandwidth applications in the face of limited available bandwidth on your network. Some applications are highly tolerant of network delays, and function normally within such a context. For example, SMTP mail is quite fault tolerant in the face of high network utilization, and SMTP messages will be delivered without error even when the network bandwidth is over-utilized.
However, if the organization that you are working with plans to implement extensive teleconferencing for mission-critical meetings, you will run up against the limitations of an Ethernet 10/100 network relatively quickly. In this situation, you should include an implementation of QoS in your design document so that the required amount of bandwidth for audio-conferencing applications is available when required. With QoS, you can assign the bandwidth to individuals or group members to ensure that bandwidth is not wasted on non-priority users or groups.

The goal of Internet of Things (IoT) is to bring electronic components online, thereby creating a volume of data that can be used with the existing computing and networking technologies. Therefore, centered cloud isn't ideal for rapidly expanding IoT environmental requirements. Fog computing (FC) moves some portion of the computing load (related to real-time services) from the cloud into edge fog devices. FC is expected to become the subsequent major computing transition and this one has ability to overcome existing cloud limitations. However the key obstacles facing FC are: wide distribution, isolated coupling, quality-of- service (QoS) regulation, adaptability to conditions, and particularly the standardization and normalization is still in phase of development. Software defined networking (SDN) will help fog to solve these obstacles. SDN means unified network control plane (which is separated from data plane), allowing the introduction for advanced traffic control and the orchestration mechanisms of networks and resources. On the grounds of SDN concept, and then combining it with FC, the network type can be modified to resolve all those cloud drawbacks and improve IoT system's QoS. Within this paper, architecture is developed through the combination of independently researched areas of SDN and FC to enhance the QoS in an IoT system. An algorithm (which is dependent on partition the SDN virtually) is presented to support the architecture whose purpose is to select the optimal access point and optimal place to process the data. The main objective of this algorithm is to provide improved QoS by partitioning the corresponding fog devices through the SDN controller. A use case dependent on the presented architecture and algorithm is then provided and assessed this use case's QoS parameter values (network usage, cost, latency and power consumption) using the iFogSim simulator. In contrast to cloud-only deployment, the result indicates a major enhancement of the mentioned QoS parameter values in the deployment of fog with SDN. In addition, once compared to a relative former identical use case; the findings of this paper show improved results for power consumption, network usage and latency. In fact, when compared to a former identical use case, the outcome of this paper shows around 3 times less latency and 2 times less network usage. Finally the ground (IoMT, Industry 4.0, Green IoT, and 5G) that is influenced by this QoS improvement is broadly illustrated in this paper.
The next lesson looks at QoS connections.