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Performance Study on Switch and Network
Published in Naoaki Yamanaka, High-Performance Backbone Network Technology, 2020
Because the multiplexing units are different from each other (cell vs. frame), differences in performance are expected in terms of delay and jitter. For services containing delay-sensitive or jitter-sensitive applications such as VoIP (Voice over IP), QoS control is a crucial issue. We compared the delay and jitter performance using the system configuration shown in Fig. 8. Test traffic and load traffic share a 5-Mb/s output link. We used ping packets to measure delay and jitter on IP layer. Also we generated 1500-byte-long ping packets to measure the performance for long packets. The load traffic has a constant bit rate and the frame size is 1500 bytes. The load-input rate is 90% of that of output link, or 4.5 Mb/s. Assigning different priorities between test and load, ping responses were measured for 1000 trials. The results are shown in Fig. 9.
Quality of Service-Sensitive MAC Protocols in Wireless Sensor Networks
Published in Ankur Dumka, Sandip K. Chaurasiya, Arindam Biswas, Hardwari Lal Mandoria, A Complete Guide to Wireless Sensor Networks, 2019
Ankur Dumka, Sandip K. Chaurasiya, Arindam Biswas, Hardwari Lal Mandoria
With the demand for bandwidth and competition in the market, quality of service (QoS) has become a benchmark in wireless sensor networks. QoS has been defined by the International Telecommunication Union (ITU) as the “totality of characteristics of a telecommunication service that bear on its ability to satisfy stated and implied needs of the user of the service.” Earlier QoS was about conserving resources rather than providing service quality. QoS is now used for assigning various priorities for users, applications, and data flow to ensure efficient and effective service implementation. QoS can be implemented by means of controlling resource sharing to ensure a higher performance level by means of setting various measurable parameters like jitter, delay, packet loss, and available bandwidth.
Utility Optimization-Based Resource Allocation for Soft QoS Traffic
Published in Liansheng Tan, Resource Allocation and Performance Optimization in Communication Networks and the Internet, 2017
In telecommunication networks, QoS refers to several related aspects that allow the transport of traffic with special requirements. QoS is the ability to provide different priority to different applications or to guarantee a certain level of performance to a data flow. For example, a required bit rate, delay, jitter, packet dropping probability, and/or bit error rate may be guaranteed. QoS guarantees are important if the network capacity is insufficient, especially for real-time streaming multimedia applications such as voice over Internet protocol (IP), online games and Internet protocol Television (IP-TV), and in networks where the capacity is a limited resource, for example, in cellular data communication.
Wireless body area networks: a comprehensive survey
Published in Journal of Medical Engineering & Technology, 2020
Bahae Abidi, Abdelillah Jilbab, El Haziti Mohamed
The QoS is the ability to communicate under good conditions, in term of availability, transmission delays, packet loss rate. It is a gestion concept to optimise the network resources and guarantee the best performances of the application who will be different depending on the nature of the used biosensor nodes in WBAN. For example, in Sondhi and Sood [43], the process of sending data to their destination, the network must balance the QoS metrics such as energy efficiency, bandwidth [44], delay, fault tolerance. In the most project, the network lifetime is given more importance than data quality so in this case the energy-aware routing protocols have been used. Also, the reliability of data transmission between source and destination is a critical issue and in order to assure the monitored data we should deliver in reasonable time and received correctly by an authorised person [42]. The requirements of QoS are categorised into: network based QoS where the QoS requisites depend on the data distribution model and application based QoS. Also, the data traffic can be classified in Djenouri and Balasingham [45], Razzaque et al. [46] into ordinary data traffic for temperature, critical data traffic for ECG and EEG, reliability sensitive data traffic for vital signals monitoring and finally delay sensitive data traffic for video streaming.
Fog Computing-Based Smart Health Monitoring System Deploying LoRa Wireless Communication
Published in IETE Technical Review, 2019
Jeevan Kharel, Haftu Tasew Reda, Soo Young Shin
Some devices with little computing capability, storage, and network connectivity can act as a “Fog node”. These fog nodes can be placed anywhere and they enable end-user devices to collaborate for accomplishing certain tasks of management, communication, and storage. Having similarity with cloud server, the fog server can store sensor readings, local information such as maps, availability of shops, restaurants, and contents like audios and videos. In our case, it is the health data from the WBS or any kind of wearable device. A simple FC architecture is shown in Figure 1. Having such capabilities, it is suitable for IoT which generates tremendous amount of data. Due to its capability of minimizing latency, it is also preferable for networks requiring better Quality of Service (QoS). In future, the application of IoT is going to be massive due to which tremendous sending and receiving of data are carried out on the edge of a network. In such cases, FC can handle these data without the involvement of cloud which helps save internet bandwidth too. Having such features, an efficient network architecture that minimizes cloud's burden, provides higher service rate, better system response time, and higher QoS can be built utilizing FC. Hence, the application of FC can be a driving force for better communication infrastructure, IoT services, and IT convergence.
Integration of sparse singular vector decomposition and statistical process control for traffic monitoring and quality of service improvement in mission-critical communication networks
Published in IISE Transactions, 2018
Recent years have witnessed a significant increase in the use of wireless communication networks across private and public sectors. Mission-Critical Communication Networks (MCCNs) are those whose malfunction or failure will result in serious impact and even catastrophes (Baker and Hoglund, 2008). MCCNs are used widely in both civil and military settings. For example, public-safety first responders, such as police officers, firefighters, and paramedics use MCCNs to keep connected with each other and with the control center when responding to emergencies such as accidents, natural disasters, and terrorist attacks. Soldiers in a battlefield use MCCNs to communicate with each other and with the command center to acquire situational awareness and make tactical decisions. The nature of MCCNs puts an extremely high standard on the Quality of Service (QoS) these networks must provide. QoS refers to the performance of a communication network that is perceived by the users (International Telecommunication Union, 1993). A network with poor QoS delivers traffic data with delay, jitter, loss, and/or errors. QoS assurance for MCCNs is critically important for public safety, economic vitality, and national security.