QoS Classes Research Articles

QCI Optimization to Minimize Latency and Enhance User Experience

Limited QCIs (QoS Class Identifiers) restrict the handling different service types with varying quality requirements. This necessitates research on QoS management to minimize latency and improve user experience, particularly for real-time applications like video conferencing and online gaming. This paper proposes a combined optimization scheme targeting QCI 3 to reduce latency. The approach involves disabling DRX, optimizing pre-allocation, and reducing the PDCP discard timer. The optimization performance is studied by taking the case of an e-sport game that demands low network latency, affecting the quality of the players' experience. The optimization scheme was validated through functionality, resource allocation, and air interface latency tests conducted under actual e-sport gaming conditions. Network latency was measured every minute to evaluate the impact of optimization on esports games running under QCI 7, QCI 3, and optimized QCI 3. In addition, air interface latency for optimized QCI 3 under networks with poor coverage and very high-capacity networks was compared to latency under QCI 8 (basic), QCI 7, and regular QCI 3. The optimization strategy demonstrated a significant reduction in air interface latency, up to 19% improvement compared to non-optimized QCI 3. It has reduced air interface latency's maximum, minimum, and standard deviation values during gameplay. The strategy also ensured concurrent operation with multiple QCI values without compromising other application’s throughput. The proposed optimization strategy effectively enhances the user experience by significantly reducing average latency and jitter.

SDFog-Mesh: A software-defined fog computing architecture over wireless mesh networks for semi-permanent smart environments

Large public congregation of short period such as Kumbh Mela, Hajj, open fairs, outdoor musical concerts etc. require temporary to semi-permanent communication and computation infrastructure to provide IoT based smart services. For these use cases, wireless mesh networks (WMN) present themselves as an elegant underlying communication substrate for designing IoT-based smart infrastructures where the wired network is not a cost-effective solution. Further, the mesh network devices such as wireless routers, access points, and gateways can also be utilized to support in-network computing for installation and execution of microservices dynamically. This paper presents the design and implementation of a software-defined wireless fog infrastructure for IoT-based semi-permanent smart infrastructure. Our proposed controller ”SDFog-Mesh” can be deployed quickly to support in-network computing over wireless network devices. Further, this controller also assists in choosing the fog nodes which are best suited for executing the desired microservice. However, the interesting challenge is to create an execution environment on fog nodes and to redirect the IoT traffic towards the deployed micro-services on-the-fly. The “SDFog-Mesh” architecture utilizes P4 language to insert/delete flow rules dynamically on the fog nodes for different classes of IoT traffic such as IoT to Fog (IF), Fog to Fog (FF), Fog to Cloud (FC) and IoT to Cloud (IC). We have considered MQTT-based IoT application as a demonstrative example to enable IF, FF, FC, and IC communication within a fog environment. The microservices of various QoS classes are deployed over our implemented testbed to evaluate our approach. Our proposed architecture has also been emulated with more devices using Mininet-Wifi for the same microservices classes for evaluating the scalability. We have considered parameters like setup time, flow creation time in data path devices, microservice service time, QoS constraints, and maintenance overhead for evaluation. The gathered results establish the applicability of our proposed solution.

History-based classification of encrypted traffic into QOS class with self-update

History-based classification of encrypted traffic into QOS class with self-update

Augmenting DiffServ operations with dynamically learned classes of services

In this work, we provide a Machine Learning framework for augmenting the Differentiated Services (DiffServ) protocol with fine-grained dynamic traffic classification. The framework is called L-DiffServ. It is composed of two classification algorithms able to detect the QoS classes of incoming packets only looking at three packet header fields; the first algorithm, referred to as Inter-L-DiffServ, is a semi-supervised classification procedure able to replicate DiffServ classification; the second one, referred to as Intra-L-DiffServ, is an unsupervised algorithm for intra-class classification, useful for classes taking large portions of the overall traffic. We apply the latter to the low priority best-effort class. The performance evaluation shows that our solution is able to dynamically classify packets and to detect new QoS sub-classes hence adapting to traffic aggregate characteristics. We also show that network resource management can be improved exploiting the new generated QoS sub-classes: two active queue management algorithms based on WRED and CHOKe show a reduction of the number of sessions affected by packet losses up to 40% with respect to the legacy DiffServ procedure.

QoE-Aware Traffic Aggregation Using Preference Logic for Edge Intelligence

Traffic flows with different requirements of quality of service (QoS requirements) are aggregated into different QoS classes to provide differentiated services (Diffserv) and better quality of experience (QoE) for users. The existing aggregation approaches/QoS mapping methods are based on quantitative QoS requirements and static QoS classes. However, they are typically qualitative and time-varying at the edge of the beyond fifth generation (B5G) networks. Therefore, the artificial intelligence technology of preference logic is applied in this paper to achieve an intelligent method for edge computing, called the preference logic based aggregation model (PLM), which effectively groups flows with qualitative requirements into dynamic classes. First, PLM uses preferences to describe QoS requirements of flows, and thus can deal with both quantitative and qualitative cases. Next, the potential conflicts in these preferences are eliminated. According to the preferences, traffic flows are finally mapped into dynamic QoS classes by logic reasoning. The experimental results show that PLM presents better performance in terms of QoE satisfaction compared with the existing aggregation methods. Utilizing preference logic to group flows, PLM implements a novel way of edge intelligence to deal with dynamic classes and improves the Diffserv for massive B5G traffic with quantitative and qualitative requirements.

QoS for best‐effort batch jobs in container‐based cloud

SummaryThe resource orchestrators in the cloud provide different QoS classes. Existing studies have mainly focused on resource guarantee for high‐priority class jobs, but yet to consider delicate QoS control of low‐priority jobs in the cloud. In this paper, we propose the differentiated shares that provide weighted CPU scheduling for low‐priority batch jobs in container‐based cloud. To implement the differentiated shares, we extend resource reservation interfaces provided by Kubernetes and suggest an algorithm that maps the resource management attributes of Kubernetes into those of Linux. The proposed differentiated shares can avoid worsening interference with high‐priority containers by exploiting the hierarchical resource sharing of task groups in Linux. In addition, we suggest a node scoring policy to provide efficient inter‐node job scheduling with the consideration of the differentiated shares. The performance measurement results show that the differentiated shares can provide weighted CPU scheduling for best‐effort batch containers without interference with high‐priority containers (less than 3% with respect to application‐level performance).

Extension of Modified Joint Uplink and Downlink Scheduling Algorithm for LTE-A in Femtocell Networks

Aim: The 5G LTE-Advanced (LTE-A) intended to provide increased peak data rates for the mobile users with the use of Carrier Aggregation (CA) technology. Due to need of uninterrupted bi-directional communication between the eNodeB and User Equipment (UE) in LTEA, Joint Scheduling Algorithm is considered as central research topic. Objective: A modified joint Uplink/ Downlink (UL/DL) Scheduling algorithm to meet on demands service request from the UEs is proposed in this paper. Methods: CA is used for calculate the weight factors for the bandwidth allocation among the mobile users based on the QoS Class Identifier (QCI). However due the huge amount of data flow in the indoor coverage yield introduction of the small cell called femtocells. Femtocells are randomly deployed in macro cell area in order to improve indoor coverage as well capacity enhancement. Result: Mixed types of traffic are considered ranging from real time to non real time flows and quality of service is evaluated in term of throughput, packet loss ratio, fairness index and spectral efficiency. The proposed modified joint user scheduling algorithm results better in delay among the end users due the reduction in the traffic load of the macro cell base station. Conclusion: Simulation results shows that, the proposed methodology suits best for the small scale network architecture with increased spectral efficiency and throughput among the UEs.

Performance Evaluation of Priority Load-Aware Scheduling (PLAS) Algorithm for IEEE802.16 Networks

In recent years, there has been an increase in the transmission of multimedia services due to the emergence of wireless broadband (WiBB) technologies such as WiMAX. WiMAX supports multiple QoS classes for transmission of different multimedia applications. However, satisfying the requirements of these applications with the often-limited resources has been a major challenge, which requires an efficient scheduling scheme such as PLAS. PLAS is a variant of LAWRR designed to reduce queuing delay of real-time traffics in WiBB networks. Several simulation experiments were conducted to evaluate the performance of PLAS against the LAWRR algorithm. The results revealed that PLAS outperforms the other scheme in terms of average delay for low input traffic. However, the metric (delay) used and the traffics generated for the simulation are not adequate to realistically evaluate the performance of a scheduling algorithm in a typical metropolitan area network. In this study, we further evaluated the performance of PLAS and LAWRR under varying higher input traffics, and an additional performance metric, using discrete event simulation. The results demonstrated that the PLAS achieved better results in terms of queuing delay and throughput compared to LAWRR. The improved performance will lead to better user experience, which will increase the number of subscribers and consequently increase revenue for service providers.

Perancangan dan Analisa Implementasi LTE Home pada Jaringan 4G LTE di Frekuensi 2300 Mhz

Design and analysis of lte home implementation on 4g lte networks in 2300mhz frequency . The demand for data connections for customers is currently increasing. FTTx as one of the Fix broadband technology (FBB) has several weaknesses, especially when applied to rural areas. LTE Home as a smart home technology is a form of WTTx 4G LTE technology service that is expected to be able to meet the data needs of customers. This study aims to design and analyze the implementation of LTE home by measuring the value of QoS Class Identifier (QCI) and the value of Radio Frequency Key Performance Indicator (RF KPI) to improve network reliability for voice and data communication services. Some parameters measured are packet loss, delay, jitter, throughput for QCI values and Radio Signal Received Power (RSRP) and Radio Signal Received Quality (RSRQ) for RF KPI values.The results of RF KPI Measurement show that the value for RSRP is -89dBm. This value is quite good because it matches the predetermined KPI standard, which is between -70 to -90 dBm. For RSRQ values obtained for -11dBM, this result is classified as good according to the KPI standard which is <-8 dBm. These results indicate that the quality of 4GLTE network services provided for LTE Home implementation services has met RF KPI standard values. Whereas for the QCI parameters obtained results that both voice call and video streaming, the value still meets the standard Good for the User Experience KPI (QCI) value that is packet loss <5%, delay <150 ms and jitter <75 ms Key w ord s: LTE home, RF KPI. QCI, RSRP, RSCP,packet loss, jitter

QoS-Aware Energy and Jitter-Efficient Downlink Predictive Scheduler for Heterogeneous Traffic LTE Networks

Energy-efficient communications have become one fundamental aspect for today's cutting-edge wireless technologies due to its valuable impact on the environment. In this paper, we augment our earlier study for the user equipment's (UE) energy efficiency (EE) in the long-term evolution (LTE) downlink by looking at real-time heterogeneous traffic QoS requirements. In particular, we utilize the previously proposed cloud radio access network (C-RAN) and ray tracing (RT)-based scheduling model to optimize both of the EE and the packet delay jitter for real-time applications with fixed packet delay budget subject to other traffic types requirements. Using the utility-based scheduling approach, we formulate the resource allocation problem as a weighted sum binary integer programming (BIP) problem. Due to the inherent complexity of the problem formulation which hinders finding its solution directly, four heuristic algorithms are proposed to solve the optimization problem. Numerical simulations are conducted on three different traffic types each belonging to one of the popular QoS classes; best-effort class, rate, and delay-constrained classes. The obtained results demonstrate a substantial improvement in the system's performance achieved by our proposed schemes compared to other existing schemes.

QoS-guaranteed scheduling for small cell networks

Abstract This paper proposes a QoS-guaranteed scheduling algorithm that considers the available resources and traffic load of small cell. Even though the available resources are scarce or traffics to be scheduled are overloaded, Guaranteed Bit Rate (GBR) traffic such as VoIP and video should be supported. The proposed algorithm provides a flexible weight ratio between GBR and Non-GBR traffic according to resources and traffic load. Furthermore, since QoS is considered by simple QoS Class Identifier (QCI), low complexity is achieved. Simulation results show that the proposed algorithm improves QoS including delay and Packet Loss Rate (PLR) performance effectively.

On Demand Resource Allocation for LTE Uplink Transmission Based on Logical Channel Groups

It is a hard task to allocate wireless resources for uplink transmission in LTE system. The main goals of previous research aimed at maximizing system throughput or fairness among UEs, while the real requirements of UEs were not considered. The result is that Resource Blocks (RBs) allocated by eNB are usually wasted and the requirements of UEs are not satisfied. We proposed an AAG-2 scheduling scheme, which can ensure the QoS of Guaranteed Bit Rate (GBR) bearers and at the same time efficiently allocate RBs to non-GBR bearers so as to improve resource utilization. In order to facilitate the management of bearers, the 3GPP (3rd Generation Partnership Project) suggested dividing bearers into four Logical Channel Groups (LCGs), rather than just GBR and non-GBR bearers. So far, 3GPP has not specified the mapping between LCGs and bearers of different QoS Class Identifiers (QCIs), but leaves the decision to system operators. In this paper, we propose a new scheme, AAG-LCG, wherein bearers are classified into four LCGs with different priority levels. With the proposed scheme, eNB can efficiently allocate RBs to meet the QoS requirements of various LCG bearers while maintaining sound overall system performance.

On the packet allocation of multi-band aggregation wireless networks

The use of heterogeneous networks with multiple radio access technologies (RATs) is a system concept that both academia and industry are studying. In such system, integrated use of available multiple RATs is essential to achieve beyond additive throughput and connectivity gains using multi-dimensional diversity. This paper considers an aggregation module called opportunistic multi-MAC aggregation (OMMA). It resides between the IP layer and the air interface protocol stacks, common to all RATs in the device. We present a theoretical framework for such system while considering a special case of multi-RAT systems, i.e., a multi-band wireless LAN (WLAN) system. An optimal packet distribution approach is derived which minimizes the average packet latency (the sum of queueing delay and serving delay) over multiple bands. It supports multiple user terminals with different QoS classes simultaneously. We further propose a packet scheduling algorithm, OMMA Leaky Bucket, which minimizes the packet end-to-end delay, i.e., the sum of average packet latency and average packet reordering delay. We also describe the system architecture of the proposed OMMA system, which is applicable for the general case of the multi-RAT devices. It includes functional description, discovery and association processes, and dynamic RAT update management. We finally present simulation results for a multi-band WLAN system. It shows the performance gains of the proposed OMMA Leaky Bucket scheme in comparison to other existing packet scheduling mechanisms.

Power optimization for multiple QoS, delay, and BER classes relying on finite-delay information theory

Future communication systems will include diffierent types of messages requiring diffierent transmission rates, packet lengths, and service qualities. We address the power-optimization issues of communication systems conveying multiple message types based on finite-delay information theory. Given both the normalized transmission rate and the packet length of a system, the actual residual decoding error rate is a function of the transmission power. We propose a generalized power allocation framework for multiple message types. Two diffierent optimization cost functions are adopted: the number of service-quality violations encountered and the sum log ratio of the residual decoding error rate. We provide the optimal analytical solution for the former cost function and a heuristic solution based on a genetic algorithm for the latter one. Finally, the performance of the proposed solutions are evaluated numerically.

Retraction Notice: A Multi-Wireless Bandwidth Aggregation Mechanism in SDN Networks

Nowadays, the popularity of smart mobile devices drives the mobile data traffic into a faster growth. For han- dling the extreme growth of mobile data traffic, the mobile telecommunication operator tries to upgrade the core network equipment to expand the data capacity of services, but compare with the exponentially growing mobile data traffic, the ef- fect is limited. In addition, most of the current multi-RAT integration researches need protocols supported by both the cli- ents and servers, or have the transmission efficiency bottleneck problem caused by the packet reordering. Therefore, this paper proposes the SDN-based multi-RAT bandwidth aggregation mechanism for handling the transmission path selection and switching among LTE, Wi-Fi, and other multi-RAT. The proposed multi-RAT online access software, aggregation control application, and data flow analysis application are installed in the UE terminal and SDN network terminal respec- tively for handling the multi-RAT bandwidth aggregation. The UE only needs to install the multi-RAT online access software through the proposed mechanism, while the application services executed in the UE terminal do not need to be modified under the proposed approach. When a single network could not satisfy the QoS requirements of UE (e.g., the UE executes several application services which require different QoS classes simultaneously), the proposed SDN-based multi- RAT bandwidth aggregation mechanism can transmit the routing device, satisfy the network QoS requirements of the UE terminal and improve the utilized efficiency of whole network according to the current network transmission efficiency and the characteristics of the service flows transmitted by the UE.

A Multi-Wireless Bandwidth Aggregation Mechanism in SDN Networks

Nowadays, the popularity of smart mobile devices drives the mobile data traffic into a faster growth. For han- dling the extreme growth of mobile data traffic, the mobile telecommunication operator tries to upgrade the core network equipment to expand the data capacity of services, but compare with the exponentially growing mobile data traffic, the ef- fect is limited. In addition, most of the current multi-RAT integration researches need protocols supported by both the cli- ents and servers, or have the transmission efficiency bottleneck problem caused by the packet reordering. Therefore, this paper proposes the SDN-based multi-RAT bandwidth aggregation mechanism for handling the transmission path selection and switching among LTE, Wi-Fi, and other multi-RAT. The proposed multi-RAT online access software, aggregation control application, and data flow analysis application are installed in the UE terminal and SDN network terminal respec- tively for handling the multi-RAT bandwidth aggregation. The UE only needs to install the multi-RAT online access software through the proposed mechanism, while the application services executed in the UE terminal do not need to be modified under the proposed approach. When a single network could not satisfy the QoS requirements of UE (e.g., the UE executes several application services which require different QoS classes simultaneously), the proposed SDN-based multi- RAT bandwidth aggregation mechanism can transmit the routing device, satisfy the network QoS requirements of the UE terminal and improve the utilized efficiency of whole network according to the current network transmission efficiency and the characteristics of the service flows transmitted by the UE.

A Multi-Wireless Bandwidth Aggregation Mechanism in SDN Networks

Nowadays, the popularity of smart mobile devices drives the mobile data traffic into a faster growth. For han- dling the extreme growth of mobile data traffic, the mobile telecommunication operator tries to upgrade the core network equipment to expand the data capacity of services, but compare with the exponentially growing mobile data traffic, the ef- fect is limited. In addition, most of the current multi-RAT integration researches need protocols supported by both the cli- ents and servers, or have the transmission efficiency bottleneck problem caused by the packet reordering. Therefore, this paper proposes the SDN-based multi-RAT bandwidth aggregation mechanism for handling the transmission path selection and switching among LTE, Wi-Fi, and other multi-RAT. The proposed multi-RAT online access software, aggregation control application, and data flow analysis application are installed in the UE terminal and SDN network terminal respec- tively for handling the multi-RAT bandwidth aggregation. The UE only needs to install the multi-RAT online access software through the proposed mechanism, while the application services executed in the UE terminal do not need to be modified under the proposed approach. When a single network could not satisfy the QoS requirements of UE (e.g., the UE executes several application services which require different QoS classes simultaneously), the proposed SDN-based multi- RAT bandwidth aggregation mechanism can transmit the routing device, satisfy the network QoS requirements of the UE terminal and improve the utilized efficiency of whole network according to the current network transmission efficiency and the characteristics of the service flows transmitted by the UE.

QoE preserving resource scheduling for M2M terminals and human users in LTE networks

We study in this paper the impact of supporting a large number of machine to machine M2M communication terminals in the 4th generation 4G long term evolution LTE wireless networks. Our main focus in the study is on how to accommodate the large number of M2M devices without negatively impacting the human subscribers' quality of experience QoE. We propose dividing the available radio resources between human users and M2M devices such that human users' QoE is preserved. Our proposal adds new M2M-specific quality of service QoS class indicators QCIs for classifying M2M traffic bearers. We use the new classes in a new priority-based scheduler to allocate radio resources to preserve human users' QoE and fairly fulfil M2M terminals' communication requests.

Throughput-aware Resource Allocation for QoS Classes in LTE Networks

Abstract In LTE systems, multicast services must be delivered efficiently in response to the need for strong QoS support. However, each class of quality services has its own requirements to be satisfied. These quality constraints limit the scheduling flexibility, and the LTE downlink resource allocating algorithms need to assimilate these con- straints while trying to maximize system performance in terms of fairness and throughput. This paper addresses this fundamental problem of LTE downlink scheduling by adopting the time-domain Knapsack algorithm over the traffic overload patterns. We fine tune the Knapsack algorithm, to overcome this problem and improve system performance objectives. We demonstrate that more efficient performance can be achieved in terms of fairness index and system throughput, which is evaluated using simulation results.

선박 내 유선망에서 차등화 서비스 지원을 위한 패킷 폐기 기술

선내 유선 네트워크에서는 선내의 각종 센서와 제어기를 자율적으로 구성관리하고 원격제어를 제공하는 기능을 수행한다. 이러한 선박 내 유선 통신망에서 차등화서비스가 지원된다면, 우선순위가 높은 실시간 플로우는 최소전송률을 보장 받고 빠르게 전송되어, 지능적인 선박 통신망을 구현할 수 있다. 본 논문에서는 이러한 선박 내 유선 네트워크에서 차등화 서비스를 지원하기 위해, 기존 RIO (RED In and Out) 방식보다 우수한 패킷 폐기 기술을 제안한다. 제안한 패킷 폐기기술은 개별 플로우별로 관리하지 않고 특정한 기준에 따라 몇 개의 플로우 그룹으로 나누어, 그룹별 관리를 통해서 동일 클래스 내 플로우 간 공평성을 제공한다. 시뮬레이션 결과에서는 RIO 방식보다 링크 이용률은 조금 감소하나, 다중 병목 구간을 경유하는 플로우들이 RIO 방식보다 더 많은 전송률을 보장 받음을 알 수 있다. An wired ship area network has functionality of remote control and autonomous management of various sensors and instruments embedded or boarded in a ship. For such environment, the DiffServ (Differentiated Services) realizes that the high-speed real-time flow with the higher priority has the guaranteed minimum data rate and is delivered faster. As a result of this DiffServ effect, the intelligent Ship Area Networks can be implemented. In this paper, an packet drop technique is proposed to outperform the previous RIO (RED In and Out) drop mechanism for DiffServ in ship area networks. the proposed packet drop technique does not manage the individual flows and divides them into several flow groups according to a criterion. And it guarantees the fairness between individual flows in the same QoS class through the group-based control. In simulation results of the proposed packet drop technique, the link utilization decreases than RIO. But it guarantees more data rates to DiffServ flows passing multiple bottleneck links.