E2E Quality Of Service Research Articles

NeSt: A QoS differentiating end-to-end networked storage simulator

The emerging high-speed storage technologies increasingly use Nonvolatile Memory Express (NVMe) protocol to meet their high throughput and low latency needs. In a datacenter environment, applications accessing multiple such devices over the fabric (i.e. the network) tend to have Quality of Service (QoS) requirements pertaining to offered throughput and experienced latency. In this paper we describe a networked storage system simulator called NeSt that supports end-to-end (E2E) QoS differentiation across multiple classes of service. This is done by conveying the class designation end to end and using it to consistently but independently apply the differentiation in each segment of the path. We demonstrate the ability of NeSt to provide end-to-end QoS differentiation under a variety of situations. To the best of our knowledge, NeSt is the first simulator of networked storage (consisting of multiple NVMe SSDs) that supports E2E QoS differentiation.

An effective deep-Q learning scheme for QoS improvement in physical layer of software-defined networks

The demands of diverse applications necessitate specific communication requirements, such as jitter, packet loss ratio (PLR), and latency, at the end-to-end (E2E) level within the physical layer of software-defined networking (SDN). In heterogeneous network environments, E2E routes traverse multiple domains with varying quality-of-service (QoS) classes of traffic, posing challenges in meeting unique E2E QoS criteria. Hence the performance on the E2E path is significant to meet the needs of applications. Hence, the issue of providing services on the E2E route is challenging due to several QoS classes in a domain on the source-to-destination route. This paper presents an SDN architecture leveraging Deep Q-learning (DQL) to ascertain the appropriate QoS class for E2E routes in software-defined heterogeneous networks, thereby reducing overall E2E delay. The proposed model with DQL is compared with benchmark reinforcement learning. The proposed framework is validated using various real Internet topologies such as Abilene, USNet, and OS3E, assessing not only E2E delay but also jitter, PLR, and throughput, showcasing its efficacy in optimizing network performance regarding these performance metrics.

End-to-End Service Auction: A General Double Auction Mechanism for Edge Computing Services

Ubiquitous powerful personal computing facilities, such as desktop computers and parked autonomous cars, can function as micro edge computing servers by leveraging their spare resources. However, to harvest their resources for service provisioning, two significant challenges will arise: how to incentivize the server owners to contribute their computing resources, and how to guarantee the end-to-end (E2E) Quality-of-Service (QoS) for service buyers? In this paper, we address these two problems in a holistic way by advocating COMSA. Unlike the existing double auction schemes for edge computing which mostly focus on computing resource trading, COMSA addresses the joint problem of double auction mechanism design and network resource allocation by explicitly taking spectrum allocation and data routing into account, thereby providing E2E QoS guarantees for edge computing services. To handle the design complexity, COMSA employs a two-step procedure to decouple network optimization and mechanism design, which hence can be applied to general network optimization problems for edge computing. COMSA holds some critical economic properties, i.e., truthfulness, budget balance, and individual rationality. Our extensive simulation studies demonstrate the effectiveness of COMSA.

From Resource Auction to Service Auction: An Auction Paradigm Shift in Wireless Networks

In 5G and beyond, the newly emerging services, such as edge computing/intelligence services, may demand the provision of heterogeneous communications, computing, and storage (CCS) resources on and across network entities multihop apart. In such cases, traditional resource-oriented auction schemes, where buyers place bids on resources, may not be effective in providing end-to-end (E2E) quality-of-service (QoS) guarantees. To overcome these limitations, in this article, we coin the concept of E2E service auction where the auction commodities are E2E services rather than certain resource. Under this framework, buyers simply bid for services with E2E QoS requirements without having to know the inner working (which resources are behind). To guarantee E2E QoS for winning bids while ensuring essential economic properties, E2E service auction requires addressing the joint problem of network optimization and auction design with both economical and QoS constraints. To substantiate the mechanism design, we illustrate how to devise E2E service auctions for edge computing systems under various scenarios. We also identify the research opportunities on E2E service auction mechanism design for other critical use cases, including edge intelligence.

Green Traffic Off-Loading Over Uncertain Shared Spectrums With End-to-End QoS Guarantee

The fast proliferation of Internet of Things (IoT) exacerbates the current spectrum shortage. As a promising solution, licensed spectrum sharing has received great attentions recently. However, due to the unpredictable activities of incumbent users, the availability of the shared spectrum is uncertain, making the quality of service (QoS) provisioning based on it a difficult task, especially under multi-hop scenarios. In this paper, considering the energy-efficiency issue, we propose an end-to-end (E2E) QoS guaranteed green traffic off-loading scheme over the uncertain shared spectrums in multi-hop networks. Specifically, we formulate it into a two-step problem, an off-loaded traffic maximization (OTM) problem and an energy-efficiency improvement (EEI) problem. The former one is to determine the admitted sessions. To achieve the E2E QoS guarantee under the uncertain spectrum supply, we develop a concept of equivalent link capacity, and construct a risk-averse joint chance constraint. Since the formulated problem is intractable, we first develop a data-driven conservative transformation to make the joint chance constraint a set of deterministic individual ones. Then, we design a convex-hull-based and a substitution-based linearization approach to make all the constraints tractable. For the second step, the EEI problem with the same constraints as the OTM problem is designed to refine the resource scheduling for the admitted sessions to optimize the energy-efficiency. To deal with the fractional-form energy-efficiency objective, a Dinkelbach method based iterative algorithm is further developed. Numerical results have shown the effectiveness of the proposed scheme.

An Effective Hierarchical Control Plane for Software-Defined Networks Leveraging TOPSIS for End-to-End QoS Class-Mapping

If an end-to-end (E2E) path includes multiple domains, we need inter-domain collaboration to ensure the E2E quality-of-service (QoS) for the applications. In heterogeneous networks, an E2E path may go through domains with several QoS classes in each domain. However, the prevalent legacy network architecture and the standard software-defined networking (SDN) model lack effective mechanisms for inter-domain collaboration and QoS class mapping. In this study, we propose a hierarchical SDN control plane approach to guarantee the E2E QoS among multiple domains with various QoS classes on the E2E path. We propose a controller module for selecting the most suitable QoS class for each domain in the E2E path based on multi-criteria decision-making by using the technique for order of preference by similarity to ideal solution (TOPSIS). We map the suitable service classes in the global controller (GC) for provisioning the E2E QoS according to the application service requests. First, we propose an SDN-based inter-domain communication scheme and the message processing algorithm for E2E service delivery when multiple QoS classes exist in each domain. Next, we formulate the problem of service class selection with TOPSIS, provide an E2E mapping scheme, and demonstrate it with an example. Finally, we compare the proposed approach with the existing schemes for E2E QoS class mapping in terms of E2E delay, jitter, packet loss rate (PLR), and cost (per bandwidth unit). According to our simulation results, the proposed approach ensures the E2E QoS and guarantees the E2E delay, jitter, PLR, and cost according to the application service requests.

SDN-enabled distributed open exchange: Dynamic QoS-path optimization in multi-operator services

We propose an SDN-enabled distributed open exchange framework for dynamic optimization of end-to-end (E2E) quality of service (QoS) paths over multi-operator networks, which enables individual network service providers (NSP) to offer inter-operator services with E2E QoS guarantees while allowing each NSP to manage their own network resources. Different from the state of the art, there are no physical Internet exchange points in the proposed framework and NSPs are assumed to have direct inter-connections. In the proposed SDN-enabled “virtual” open exchange, the SDN controllers of all NSPs directly communicate with each other to advertise a set of QoS-enabled paths across their own network with ask prices, and each NSPs dynamically selects the best E2E price-performance path for its customers by bidding on a subset of these advertised paths, and form E2E paths by concatenating them. The main contributions of this paper are a distributed open exchange framework and a distributed procedure for E2E path computation by collaboration between SDN controllers of multiple NSPs, which is coordinated by the SDN controller of the NSP in which the managed service request originates. The proposed procedure has been verified over a multi-operator SDN environment, emulated by using the Mininet, which includes a controller-to-controller messaging protocol for provisioning multi-operator video services with E2E QoS.

On the Feasibility of Inter-Domain Routing via a Small Broker Set

The Internet is a gigantic distributed system where the end-to-end (E2E) quality-of-service (QoS) plays an important role. Yet the current inter-domain routing protocol, namely, the Border Gateway Protocol (BGP), cannot provide E2E QoS guarantees. The main reason is that an autonomous system (AS) can only receive guarantees from its first-hop ASes via service level agreements (SLAs). But beyond the first-hop, QoS along the path from a source AS to a destination AS is not within the source AS's control regime. This makes it difficult to provide high quality-of-experience services to many Internet users even when many content providers are willing to pay for such high quality E2E guarantees. In this paper, we investigate the feasibility of providing high QoS-guaranteed E2E transit services by utilizing a (small) set of ASes/IXPs to serve as “ brokers ” to provide supervision, control and resource negotiation. Finding an optimal set of ASes as brokers can be formulated as a Maximum Coverage with $B-$ dominating path Guarantee (MCBG) problem, and we show that it is in fact NP-hard. To address this problem, we design a $(\frac{1{-}e^{-\!1}}{2}){-}$ approximation algorithm and also an efficient heuristic algorithm when additional constraints (e.g., the path length) are considered. We further analyze the APX-hardness of the MCBG problem to reveal the existence of the best approximation ratio. Based on the current Internet topology, we demonstrate that it is indeed feasible to provide high QoS guarantees for most E2E connections with only a small broker set: with only 0.19, 1.9 or 6.8 percent ASes/IXPs serving as brokers, 53.13, 85.41 or 99.29 percent of all global E2E connections can receive high QoS-guaranteed services. Finally, we provide an economic model to study the behaviours of ASes when cooperating our brokerage scheme with the BGP protocol, and show that there are incentives to form and maintain such a brokerage coalition.

QoSatAr: a cross-layer architecture for E2E QoS provisioning over DVB-S2 broadband satellite systems

This article presents QoSatAr, a cross-layer architecture developed to provide end-to-end quality of service (QoS) guarantees for Internet protocol (IP) traffic over the Digital Video Broadcasting-Second generation (DVB-S2) satellite systems. The architecture design is based on a cross-layer optimization between the physical layer and the network layer to provide QoS provisioning based on the bandwidth availability present in the DVB-S2 satellite channel. Our design is developed at the satellite-independent layers, being in compliance with the ETSI-BSM-QoS standards. The architecture is set up inside the gateway, it includes a Re-Queuing Mechanism (RQM) to enhance the goodput of the EF and AF traffic classes and an adaptive IP scheduler to guarantee the high-priority traffic classes taking into account the channel conditions affected by rain events. One of the most important aspect of the architecture design is that QoSatAr is able to guarantee the QoS requirements for specific traffic flows considering a single parameter: the bandwidth availability which is set at the physical layer (considering adaptive code and modulation adaptation) and sent to the network layer by means of a cross-layer optimization. The architecture has been evaluated using the NS-2 simulator. In this article, we present evaluation metrics, extensive simulations results and conclusions about the performance of the proposed QoSatAr when it is evaluated over a DVB-S2 satellite scenario. The key results show that the implementation of this architecture enables to keep control of the satellite system load while guaranteeing the QoS levels for the high-priority traffic classes even when bandwidth variations due to rain events are experienced. Moreover, using the RQM mechanism the user’s quality of experience is improved while keeping lower delay and jitter values for the high-priority traffic classes. In particular, the AF goodput is enhanced around 33% over the drop tail scheme (on average).

On QoE monitoring and E2E service assurance in 4G wireless networks

From the users and service providers point of view, the upcoming 4G wireless (WiMAX and LTE) networks are expected to deliver high performance sensitive applications like live mobile TV, video calling, mobile video services, etc. The 4G networks are intended to provide an accurate service view of customer-perceived service quality ? their ?Quality of Experience? or QoE. Delivering high QoE depends on factors that contribute to the user?s perception of the target services as well as the Quality of Service (QoS) of the network. Although a better network QoS in many cases will result in better QoE, fulfilling all traffic QoS parameters alone may not guarantee satisfied users. On the other hand, if the QoS of the network degrades, the QoE of users' applications could be affected significantly. This article presents an integrated view of End-to- End (E2E) QoS and service assurance support in WiMAX and LTE networks. The integrated view also considers the existing cross-layer implementations to achieve the necessary E2E QoS and how the QoS and QoE should and can be monitored over the network in an E2E fashion. The existing cross-layer implementations ensure the E2E QoS performance before establishing the applications. However, even though the network has strong QoS support, the service providers should still monitor the QoS of the network and QoE of users? applications accurately to achieve service quality assurance.

EVALUATION OF QOS IN UMTS BACKBONE NETWORK BY USING DIFFERENTIATED SERVICES

A distinguishing feature of the Universal Mobile Telecommunications System (UMTS) is the support of different levels of quality of service (QoS) as required by subscribers and their applications. To provide QoS, the UMTS backbone network needs an efficient QoS mechanism to provide the demanded level of services on UMTS network. We implement a model to investigate end-to-end quality of service (QoS) provisioning approaches for UMTS networks in a DiffServ IP network environment. The effort was put on QoS classes mapping from DiffServ to UMTS, Access Control, buffering and scheduling optimization. The DiffServ Code Point was utilized in the E2E UMTS QoS provisioning to differentiate different types of traffic. We hybridized our work by applying Resource reservation protocol (RSVP) in routers and hosts. The main advantages and drawbacks are discussed. We found that our proposed model (hybridized model (DiffServ/RSVP)) improves the end-to-end delay and end-to-end variation compared with DiffServ model only, and it is superior to DiffServ regarding to throughput, utilization and packet loss ratio. The overall work guarantees the E2E QoS parameters of each service class, especially for real-time applications and improved the bandwidth utilization. Simulation results show that DiffServ can be an effective candidate for UMTS backbone bearer service.