Comparison Data Traffic Scheduling Techniques for Classifying QoS over 5G Mobile Networks

Enhancing Quality of Service (QoS) in mobile networks is the key aim for mobile operators. Mobile networks transport several forms of data traffic for real-time applications (i.e., video monitoring). These applications need to get the advantage of QoS adaptation. Numerous scheduling techniques are utilized at the router to assure the QoS of the mobile networks. Upcoming 5G mobile networks will be launched; hence, Human-Type-Communication (HTC) and Machine-to-Machine (M2M) data traffic are expected to increase dramatically over mobile networks, which results in growing the capacity and raising high data rates. These networks are expected to face challenges in cases of Radio Access Network (RAN) overload and congestion due to the massive smart devices data traffic with various QoS requirements. This paper presents a comparison for data traffic scheduling techniques, which are Priority Queuing (PQ), First-In-First-Out (FIFO) and Weighted Fair Queuing (WFQ). We consider to select a suitable data traffic scheduling technique in terms of QoS provisioning and helping 5G network, also we propose models and algorithms for efficiently utilized the smallest unit of a RAN in a relay node by aggregating and slicing the data traffic of several M2M devices

Penerapan dan Analisis Perbandingan Metode Antrian Jaringan (Network Queuing) Pada Jaringan Local Area Network Fakultas Teknik Universitas Tadulako

The flood of content that is accessed by the academic community in a campus environment demands reliable network performance, especially in handling high data traffic loads. Often what happens is that when the data traffic load increases, the quality of data services that can be provided will decrease. This of course has a bad impact, especially communication services that require high reliability such as VoIP or video conferencing services. To overcome this, it is necessary to apply a data queuing method that is able to regulate the distribution of data traffic loads effectively and is able to work well in all traffic load conditions. This study will simulate a local computer network located at the Faculty of Engineering, Tadulako University using three types of data traffic queuing methods, namely First In First Out (FIFO), Priority Queueing (PQ), and Weighted Fair Queueing (WFQ) where the three protocols will be tested. to manage three types of services that are often used, including video conferencing services, Voice Over Internet Protocol (VoIP), and Hypertext Transfer Protocol (HTTP) under conditions of high traffic loads. The results of this study indicate that the PQ method has advantages in handling high data traffic loads.Membanjirnya konten yang diakses oleh civitas akademika di lingkungan kampus menuntut kinerja jaringan yang handal, terutama dalam menangani beban trafik data yang tinggi. Seringkali yang terjadi adalah ketika beban trafik data meningkat, kualitas layanan data yang dapat diberikan akan menurun. Hal ini tentu saja berdampak buruk, terutama layanan komunikasi yang membutuhkan kehandalan tinggi seperti layanan VoIP atau video conference. Untuk mengatasi hal tersebut maka perlu diterapkan suatu metode antrian data yang mampu mengatur distribusi beban lalu lintas data secara efektif dan mampu bekerja dengan baik di segala kondisi beban lalu lintas. Penelitian ini akan mensimulasikan jaringan komputer lokal yang berada di Fakultas Teknik Universitas Tadulako menggunakan tiga jenis metode antrian trafik data yaitu First In First Out (FIFO), Priorityt Queuing (PQ), dan Weighted Fair Queuing (WFQ) dimana tiga protokol akan diuji untuk mengelola tiga jenis layanan yang sering digunakan, antara lain layanan konferensi video, Voice Over Internet Protocol (VoIP), dan Hypertext Transfer Protocol (HTTP) dalam kondisi beban trafik tinggi. Hasil penelitian ini menunjukkan bahwa metode PQ memiliki keunggulan dalam menangani beban trafik data yang tinggi

Reduction of HARQ Latency for URLLC 5G Services Based on Network Slicing and Massive MIMO Hybrid Beamforming

Ultra-Reliable and Low-Latency Communications (URLLC)  is one of the three generic 5G services and probably the most challenging one, with strict quality of service requirements of 99.999% or more reliability and <1 milliseconds (ms) radio latency. To achieve latency targets, contributors to latency need to be addressed. Hybrid automatic repeat request (HARQ) retransmissions are major contributor to latency and need to be limited. The objective of this paper is to study the benefit of using Massive MIMO (M-MIMIO) along with radio network slicing to reduce number of HARQ retransmissions. A practical type of M-MIMO beamforming named hybrid beamforming is used. The performance of the proposed system is evaluated with slicing, without slicing and by alternating number of data streams per user. This work highlights the importance of technology enablers, such as M-MIMO and network slicing, in addressing quality-of-service (QoS) latency requirements for URLLC applications

An Energy Efficient Service Composition Mechanism Using a Hybrid Meta-heuristic Algorithm in a Mobile Cloud Environment

By increasing mobile devices in technology and human life, using a runtime and mobile services has gotten more complex along with the composition of a large number of atomic services. Different services are provided by mobile cloud components to represent the non-functional properties as Quality of Service (QoS), which is applied by a set of standards. On the other hand, the growth of the energy-source heterogeneity in mobile clouds is an emerging challenge according to the energy saving problem in mobile nodes. In order to mobile cloud service composition as an NP-Hard problem, an efficient selection method should be taken by problem using optimal energy-aware methods that can extend the deployment and interoperability of mobile cloud components. Also, an energy-aware service composition mechanism is required to preserve high energy saving scenarios for mobile cloud components. In this paper, an energy-aware mechanism is applied to optimize mobile cloud service composition using a hybrid Shuffled Frog Leaping Algorithm and Genetic Algorithm (SFGA). Experimental results capture that the proposed mechanism improves the feasibility of the service composition with minimum energy consumption, response time, and cost for mobile cloud components against some current algorithms

SLICING-BASED RESOURCE ALLOCATION AND MOBILITY MANAGEMENT FOR EMERGING WIRELESS NETWORKS

The proliferation of smart mobile devices and user applications has continued to contribute to the tremendous volume of data traffic in cellular networks. Moreover, with the feature of heterogeneous connectivity interfaces of these smart devices, it becomes more complex for managing the traffic volume in the context of mobility. To surmount this challenge, service and resource providers are looking for alternative mechanisms that can successfully facilitate managing network resources and mobility in a more dynamic, predictive and distributed manner. New concepts of network architectures such as Software-Defined Network (SDN) and Network Function Virtualization (NFV) have paved the way to move from static to flexible networks. They make networks more flexible (i.e., network providers capable of on-demand provisioning), easily customizable and cost effective. In this regard, network slicing is emerging as a new technology built on the concepts of SDN and NFV. It splits a network infrastructure into isolated virtual networks and allows them to manage network resources based on their requirements and characteristics. Most of the existing solutions for network slicing are facing challenges in terms of resource and mobility management. Regarding resource management, it creates challenges in terms of provisioning network throughput, end-to-end delay, and fairness resources allocation for each slice, whereas, in the case of mobility management, due to the rapid change of user mobility the network slice operator would like to hold the mobility controlling over its clients across different access networks, rather than the network operator, to ensure better services and user experience. In this thesis, we propose two novel architectural solutions to solve the challenges identified above. The first proposed solution introduces a Network Slicing Resource Management (NSRM) mechanism that assigns the required resources for each slice, taking into consideration resource isolation between different slices. The second proposed v solution provides a Mobility Management architecture-based Network Slicing (MMNS) where each slice manages its users across heterogeneous radio access technologies such as WiFi, LTE and 5G networks. In MMNS architecture, each slice has different mobility demands (e.g,. latency, speed and interference) and these demands are governed by a network slice configuration and service characteristics. In addition, NSRM ensures isolating, customizing and fair sharing of distributed bandwidths between various network slices and users belonging to the same slice depending on different requirements of each one. Whereas, MMNS is a logical platform that unifies different Radio Access Technologies (RATs) and allows all slices to share them in order to satisfy different slice mobility demands. We considered two software simulations, namely OPNET Modeler and OMNET++, to validate the performance evaluation of the thesis contributions. The simulation results for both proposed architectures show that, in case of NSRM, the resource blocking is approximately 35% less compared to the legacy LTE network, which it allows to accommodate more users. The NSRM also successfully maintains the isolation for both the inter and intra network slices. Moreover, the results show that the NSRM is able to run different scheduling mechanisms where each network slice guarantee perform its own scheduling mechanism and simultaneously with other slices. Regarding the MMNS, the results show the advantages of the proposed architecture that are the reduction of the tunnelling overhead and the minimization of the handover latency. The MMNS results show the packets delivery cost is optimal by reducing the number of hops that the packets transit between a source node and destination. Additionally, seamless session continues of a user IP-flow between different access networks interfaces has been successfully achieved