Network-level Quality Of Service Research Articles

Dynamic and Effect-Driven Output Service Selection for IoT Environments Using Deep Reinforcement Learning

In the context of the recent emergence of the Internet of Things (IoT), human users and IoT-based services are interacting via physical effects, such as light and sound. Therefore, it is necessary to consider the quality of the delivery of physical effects to users by IoT devices for selecting services in IoT environments. However, traditional service-selection algorithms focus primarily on the network-level Quality of Service (QoS), such as latency and throughput. In this study, we improve on the visual-service effectiveness metric developed in our previous work to measure the effectiveness of the personalized delivery of physical effects of visual services to users by considering user- and application-specific factors. We evaluate the metric by conducting a user study, and the results show that the metric reflects users’ perceived effectiveness with high accuracy. We also investigate the use of virtual reality (VR) to imitate physical environments for efficient evaluation of the metric. Based on this metric, we develop a dynamic effect-driven output-service selection agent (DEOSA) that selects output services dynamically by considering the effectiveness of service-effect delivery. By adopting a state-of-the-art reinforcement-learning algorithm, DEOSA can learn the optimal policy for selecting output services that can be generalized to various environments. We evaluate DEOSA in simulated IoT environments and show that it can learn the optimal policy successfully; it generally performs better than traditional greedy algorithms in terms of the visual service effectiveness metric and the replacement overhead in randomly generated test environments.

A Radio Link Reliability Prediction Model for Wireless Sensor Networks

The wireless sensor network (WSN) has great prospects in monitoring and control of industrial plants and devices. One of the main challenges of developing WSNs for industrial applications is to satisfy their requirements for reliability with strict bounds. Accurate prediction of a radio link's reliability is helpful for upper layer protocols to optimise network level quality of service (QoS) performance. In this paper, to predict the bounds of the confidence interval of the packet reception ratio (PRR), a radio link reliability prediction (RLRP) model is proposed for describing the relation between the reliability metric's bounds and factors that affect it. Based on the RLRP model, the adaptive extended Kalman filter algorithm is adopted to predict the reliability metric. Real-world experiments were performed to demonstrate the proposed model. The results indicate that our RLRP model is accurate in predicting the bounds of link reliability, can better reflect the random characteristic of the radio link, and is more sensitive to dynamic changes of the radio link.

OSM

Different 3D tele-immersive (3DTI) activities pose different prioritized requirements for application and network-level quality of service (QoS) to ensure a strong quality of experience (QoE) for participants. Some applications put heavy weight on audio quality, some consider higher quality for upper body video streams, and some seek very low end-to-end interactivity delay. In addition, a variation in streaming content may arise in the 3DTI space due to the participants' change in interests (e.g., view change). Therefore, there is a need for an adaptive multistream, multisite 3DTI session management strategy that is not only unobtrusive, but also optimizes prioritized QoS parameters in 3DTI content distribution based on user activity and content variation. To address this next generation session management problem, we revisit the design space of multistream and multisite 3DTI session layer. We present an evolutionary 3DTI session optimization approach using Open Session Management (OSM) architecture that uses a global view of participants and overlays network conditions to optimize QoS parameters. Experimental results with PlanetLab traces show that our optimization process is unobtrusive, and the optimized TI sessions provide higher satisfaction to the participants (in some cases up to 50% higher) compared to the current solutions in the 3DTI space.

Enabling richer statistical MANET simulations through cluster computing

The wide-scale adoption of modern smart phones and other multi-radio mobile devices, has begun to provide pragmatic deployment environments for non-cellular mobile ad hoc network (MANET) services (i.e., for disaster recovery scenarios, peered mobile games, social networking applications, etc.). User perceptions of the quality of such MANET services will be driven, in part, by standard network-level quality of service (QoS) metrics such as delay, jitter, throughput, etc. Much of the existing MANET literature has explored these issues, as well as MANET routing protocol design, through single computer Monte Carlo simulations (e.g., via ns-2, ns-3, OMNeT++, or OpNet). Results are then reported as the averages of these Monte Carlo runs. As is well known from probability and statistics, such averaging is only meaningful when applied across statistically ergodic data (i.e., data drawn from the same underlying distribution). But, assessing the validity of this underlying ergodic assumption requires transitioning to more rigorous cluster-based MANET simulation frameworks. This work highlights the theoretical rationale for such ergodicity testing, the developments of a cluster-based framework, the STARs framework, to support such testing, and the results and insights obtained by using this framework to evaluate the popular DYMO and OLSR MANET routing protocols. This work also discusses why the insights ergodic testing provides are of interest to potential real-world MANET deployments.

Theoretical framework for quality of service analysis of differentiated traffic in 802.11 wireless local area networks

In this study, the authors provide an analytical framework to assess network-level quality of service (QoS) measures for differentiated, non-saturated traffic in infrastructure-mode 802.11 wireless local area networks using the distributed coordination function access mechanism. The authors build on a general analytical framework that takes into account the medium access control (MAC) access mechanism, the MAC layer packet buffer and the characteristics of the offered load to obtain the probability of a collision with M classes of traffic. The authors then derive analytical expressions for the throughput, the end-to-end packet delay and the packet delay outage probability for differentiated traffic. A case study of voice-over-IP (VoIP) traffic in 802.11b/g networks is used to validate the theoretical framework. The analytical results are in good agreement with the simulation results, showing that although the collision probability for packets transmitted at the access point (AP) is lower than for packets transmitted from the clients, the end-to-end delay in the downlink is much longer than that in the uplink because of the large queuing delay because of the multiplexing of several VoIP connections at the AP. The authors also compare the maximum number of VoIP connections that can be admitted in an 802.11 network while respecting their QoS constraints; these were computed with the proposed theoretical model, an ns-2 simulation model and other schemes previously proposed in the literature. The results indicate that their approach is more accurate over a wide range of parameter values, thus demonstrating the validity, the flexibility and the robustness of the proposed theoretical framework.

Joint assessment of Network- and Perceived-QoS in video delivery networks

Given the increasing number of IP streaming video customers, service providers are seeking an efficient way to monitor in real time the offered quality of service, as perceived by each end user. Since real-time video quality assessment via image processing algorithms is quite bandwidth- and processing-power-demanding, a feasible alternative could be to monitor the Network-level Quality of Service (NQoS) and associate it with the Perceived QoS (PQoS). This article presents a network-agnostic framework for the joint assessment of N- and P-QoS, with the aim of correlating these two parameters for a specific network and service configuration. This framework/architecture is implemented with open source software tools and is being demonstrated in an actual WiMAX streaming video distribution platform.

Network-Level QoS Assurances Through Adaptive Allocation of CDMA Resources

In a Code Division Multiple Access (CDMA) network, multiple Mobile Hosts (MHs) can simultaneously transmit over the wireless channel by using different codes. To assure an acceptable Quality of Service (QoS) for all MHs' flows, the network usually tunes the transmit powers of all MHs to achieve a certain level of signal strength as compared to the noise and the interference (SINR) for each MH. The traditional assumption in power control schemes is that the SINR requirement is statically determined for each MH's flow.In contrast, in this paper, we propose a scheme that dynamically adapts the SINR requirements of MH's flow based on its QoS requirements and the conditions of the wireless channel between the MHs and the base station. As a result of this adaptation, we show that network-level QoS measures such as fraction of packets meeting their delay requirements and energy consumed per packet transmission are significantly better than in a scheme that statically fixes the SINR requirements. We show that the adaptation approach works well for the Matched Filter (MF) and the Minimum Mean Squared Error (MMSE) receivers.Our scheme uses a simple table-driven approach for optimally selecting the target SINR requirement for each MH at run time. The entries, in the table are computed off-line using a dynamic programming algorithm with the objective of maximizing a profit function that balances the need for meeting the network-level QoS requirements and the cost of using a particular target SINR for a given transmission.

Streaming video delivery over Internet with adaptive end-to-end QoS

Many multimedia applications rely on video streaming techniques. However, video delivery over a Best Effort network such as today's Internet is a challenge. Traffic load in the network changes dynamically and in an unpredictable way causing the resource availability to vary. Providing an application level end-to-end quality of service in such an environment requires network-awareness and ability to adapt. We address the issue of mapping between application-level quality of service for streaming video and network-level quality of service. We show that continuous playback requires a limit on the delay jitter. We tackle the problem of providing end-to-end video quality given that the network does not guarantee limited delay variability. Our approach is unique in a way we do not model network as a black box but investigate what information about the network status is necessary for an application to make adaptation decisions. We rely on simple multi-level ECN-based mechanism to obtain a feedback from the network as well as on end-point observations to determine available bandwidth. Such an approach allows to obtain better user-perceived video quality by providing additional information to properly interpret the arrival rate observed at the end-point. We propose a 3-rate adaptation mechanism for video streaming to illustrate the philosophy of adaptivity based on network awareness, where the network awareness is not limited to observing network reaction to a set of stimuli.

INTELLIGENT PROTOCOL ADAPTATION IN A MEDICAL E-COLLABORATION ENVIRONMENT

Distributed multimedia e-health applications have a set of specific requirements which must be taken into account if effective use is to be made of the limited resources provided by public telecommunication networks. Moreover, there is an architectural gap between the provision of network-level Quality of Service (QoS) and user requirements of e-health applications. In this paper, we address the problem of bridging this gap from a multi-criteria decision-making perspective in the context of a remote collaborative environment for back pain treatment. We propose adaptable data transport mechanisms, capable of responding to evolving networking, application and user requirements. To this end we present a framework which allows for not only construction of tailored multimedia communication protocols, but also for the inclusion of user requirements in such protocols. This is achieved by equipping our protocol adaptation mechanism with multi-criteria decision making based techniques that can be used to allocate resources according to their ratio-scale priorities in response to detection of system degradation or evolving user preferences. The applicability of our approach is illustrated in three usage scenarios.

Performance evaluation of service differentiating Internet servers

The differentiated service approach has been proposed as a potential solution to provide quality of service (QoS) in the next generation Internet. The ultimate goal of end-to-end service differentiation can be achieved by complementing the network-level QoS with service differentiation at Internet servers. In this paper, we have presented a detailed study of the performance of service differentiating Web servers (SDIS). Various aspects, such as admission control, scheduling, and task assignment schemes for SDIS, have been evaluated through real workload traces. The impact of these aspects has been quantified in a simulation-based study. Under high system utilization, a service differentiating server provides significantly better services to high priority tasks compared to a traditional Internet server. A combination of selective early discard and priority-based task scheduling and assignment is required to provide efficient service differentiation at the servers. The results of these studies could be used as a foundation for further studies on service differentiating Internet servers.

An Holistic View of Quality of Service

The growing presence of digital multimedia in everyday life, as evidenced by the continuing increase in Internet usage, is expected to augment or replace traditional modes of social and economic interaction. Face-to-face meetings, paperwork, and office-space are all expected to diminish in importance as cyberspace provides new facilities and interaction modes. In the higher education sector, distributed learning environments (DLEs) are being cited as solutions to the ambitious political goals of better education, wider access and lower costs. DLEs are still in their infancy however, and if they are to succeed in transforming conventional educational practice, they must become quality of service (QoS) aware. The notion of QoS originated in computer networking, but if it is not addressed appropriately in all a system's components then there may be little or no benefit for that system's users, regardless of the network quality. There is a real danger that policy makers in the educational sphere will simply equate the needs of the end users, namely teachers and students, with network-level QoS. Our experience with the TAGS framework for constructing DLEs has shown that QoS must be taken into account from many perspectives before traditional educational processes can be satisfactorily transformed. This paper contributes towards an holistic view of QoS in DLEs by reviewing the network perspective and augmenting it with other, equally important, concerns.