Hierarchical Quality Of Service Research Articles

DeepQoS: Core-Stateless Hierarchical QoS in Programmable Switches

Novel applications and network scenarios challenge existing traffic management strategies. Hierarchical Quality of Service (HQoS) provides a fine control of resource sharing and delay, but traditional HQoS solutions have challenging complexity that prevents their deployment in the traffic management engine of high-speed switches. Programmable switches have emerged to make the packet processing pipelines flexible and reconfigurable, but their traffic management capabilities still rely on fixed functions that cannot handle the complexity of traditional HQoS approaches. In this paper, we show how the extended programmability can help in addressing this challenge by the application of a fundamentally different algorithm. To emulate HQoS behavior we extend our core-stateless resource sharing framework called Per Packet Value (PPV) with a HQoS-packet marker architecture called DeepQoS. DeepQoS can be used to mark resource sharing policies of different layers simultaneously and effectively at a single point, e.g., ensuring the fair share of a household’s traffic within an access aggregation network, while also controlling the shares of its subflows. In the PPV framework, bottleneck scheduling is very simple and is unaware of flows and policies, which are encoded to Packet Values. DeepQoS can use these existing simple PPV schedulers without any change. To demonstrate the deployability of the proposed method, we have created the DeepQoS marker implementation in DPDK while redesigned and implemented our packet scheduler called Virtual Dual Queue Core Stateless Active Queue Management (VDQ-CSAQM) on a P4-programmable switch. Using extensive measurements we demonstrate the unique capabilities of DeepQoS to realize rich and deep HQoS.

Dual Dynamic Scheduling for Hierarchical QoS in Uplink-NOMA: A Reinforcement Learning Approach.

The demand for bandwidth-intensive and delay-sensitive services is surging daily with the development of 5G technology, resulting in fierce competition for scarce radio resources. Power domain Nonorthogonal Multiple Access (NOMA) technologies can dramatically improve system capacity and spectrum efficiency. Unlike existing NOMA scheduling that mainly focuses on fairness, this paper proposes a power control solution for uplink hybrid OMA and PD-NOMA in dual dynamic environments: dynamic and imperfect channel information together with the random user-specific hierarchical quality of service (QoS). This paper models the power control problem as a nonconvex stochastic, which aims to maximize system energy efficiency while guaranteeing hierarchical user QoS requirements. Then, the problem is formulated as a partially observable Markov decision process (POMDP). Owing to the difficulty of modeling time-varying scenes, the urgency of fast convergency, the adaptability in a dynamic environment, and the continuity of the variables, a Deep Reinforcement Learning (DRL)-based method is proposed. This paper also transforms the hierarchical QoS constraint under the NOMA serial interference cancellation (SIC) scene to fit DRL. The simulation results verify the effectiveness and robustness of the proposed algorithm under a dual uncertain environment. As compared with the baseline Particle Swarm Optimization algorithm (PSO), the proposed DRL-based method has demonstrated satisfying performance.

OpenBNG: Central office network functions on programmable data plane hardware

SummaryTelecommunication providers continuously evolve their network infrastructure by increasing performance, lowering time to market, providing new services, and reducing the cost of the infrastructure and its operation. Network function virtualization (NFV) on commodity hardware offers an attractive, low‐cost platform to establish innovations much faster than with purpose‐built hardware products. Unfortunately, implementing NFV on commodity processors does not match the performance requirements of the high‐throughput data plane components in large carrier access networks. Therefore, programmable hardware architectures like field programmable gate arrays (FPGAs), network processors, and switch silicon supporting the flexibility of the P4 language offer a promising way to account for both performance requirements and the demand to quickly introduce innovations into networks. In this article, we propose a way to offer residential network access with programmable packet processing architectures. On the basis of the highly flexible P4 programming language, we present a design and open source implementation of a broadband network gateway (BNG) data plane that meets the challenging demands of BNGs in carrier‐grade environments. In addition, we introduce a concept of hybrid openBNG design, realizing the required hierarchical quality of service (HQoS) functionality in a subsequent FPGA. The proposed evaluation results show the desired performance characteristics, and our proposed design together with upcoming P4 hardware can offer a giant leap towards highest performance NFV network access.

PBB-TE 기반의 패킷전송시스템에서 멀티캐스트 서비스와 계층적 QoS 구현

We have proposed a solution to multicast services and an advanced quality of service (QoS) mechanism on a packet transport system (PTS) based on PBB-TE. The point-to-multipoint (PtMP) connection in the PBB-TE system have been realized by grouping point-to-point (PtP) PTL trunks and mapping a BSI onto the PtP PTL trunks using a multicast backbone destination address. To provide end-to-end QoS of the PtMP services, the hierarchical QoS scheme for backbone service instances and connection-oriented paths has been implemented in the PTS. For providing different capabilities for service selection and priority selection, the PTS offers to customers three basic types of the port-based, C-tagged, and S-tagged service interface defined by the IEEE 802.1ah. To offer to customers different capabilities of the layer 3 applications and services, moreover, an IP-flow service interface have been added. In order to evaluate traffic performance for PtMP services in the PTS, the PtMP throughputs for the link capacity of 1 Gbps at the four service interfaces were measured in the leaves of the ingress edge node, the transit node, and the egress edge node. The throughputs were about 96 % because the B-MAC overhead of 22 bytes occupies 4% of the 512-byte packet. The QoS performance is ability to guarantee an application or a user a required bandwidth, and could be evaluated by the accuracy of policing or shaping. The accuracy of the policing scheme and the accuracy of the shaping scheme were 99% and 99.3% respectively.

Topology Aggregation for Hierarchical Wireless Tactical Networks

Wireless tactical network (WTN) is the most important present-day technology enabling modern network centric warfare. It inherits many features from WMNs, since the WTN is based on existing wireless mesh networks (WMNs). However, it also has distinctive characteristics, such as hierarchical structures and tight QoS (Quality-of-Service) requirements. Little research has been conducted on hierarchical protocols to support various QoS in WMN. We require new protocols specifically optimized for WTNs. Control packets are generally required to find paths and reserve resources for QoS requirements, so data throughput is not degraded due to overhead. The fundamental solution is to adopt topology aggregation, in which a low tier node aggregates and simplifies the topology information and delivers it to a high tier node. The overhead from control packet exchange can be reduced greatly due to decreased information size. Although topology aggregation is effective for low overhead, it also causes the inaccuracy of topology information; thus, incurring low QoS support capability. Therefore, we need a new topology aggregation algorithm to achieve high accuracy. In this paper, we propose a new aggregation algorithm based on star topology. Noting the hierarchical characteristics in military and hierarchical networks, star topology aggregation can be used effectively. Our algorithm uses a limited number of bypasses to increase the exactness of the star topology aggregation. It adjusts topology parameters whenever it adds a bypass. Consequently, the result is highly accurate and has low computational complexity.

An XML-based Quality of Service Enabling Language for the Web

In this paper, we introduce an XML-based hierarchical QoS markup language, called HQML, to enhance distributed multimedia applications on the World Wide Web (WWW) with quality of service (QoS) capability. The design ofHQML is based on two observations: (1) the absence of a systematic QoS specification language, that can be used by distributed multimedia applications on the WWW to utilize the state-of-the-art QoS management technology and (2) the power and popularity of XML to deliver richly structured contents over the Web. HQML allows distributed multimedia applications to specify all kinds of application-specific QoS policies and requirements. During runtime, the HQML Executor translates the HQML file into desired data structures and cooperates with the QoS proxies that assist applications in end-to-end QoS negotiation, setup and enforcement. In order to make QoS services tailored toward user preferences and meet the challenges of uncertainty in the distributed heterogeneous environments, the design of HQML is featured as interactive andflexible . In order to allow application developers to create HQML specifications correctly and easily, we have designed and developed a unified visual QoS programming environment, called QoSTalk. In QoSTalk, we adopt a grammatical approach to perform consistency check on the visual QoS specifications and generate HQML files automatically. Finally, we introduce the distributed QoS compiler, which performs the automatic mappings between application- and resource-level QoS parameters to relieve the application developer of the burden of dealing with low-level QoS specifications.