Access Link Capacity Research Articles

Dimensioning access link capacity for time-varying traffic with mixed packet streams and circuit connections

Access links that connect cloud data centers or enterprise networks to public networks are important parts of the network infrastructure and make up considerable portions of overall network expenditures. When a customer network is connected to an overlaid elastic optical network, determining the capacity of the access link is difficult. Furthermore, access links carry mixed packet streams and circuit connections, each with different performance requirements. Additionally, traffic loads are time-varying and often exhibit diurnal patterns. In this study, we formulate the access link capacity dimensioning problem as an optimization problem with a nested dynamic constraint satisfaction subproblem. Instead of using hard performance measures, such as packet delays and blocking probabilities, we use the probability of fulfillment with regard to different traffic arrival rates as the performance measure and the performance–cost ratio as our optimization objective. Numerical results suggest that a 7.5% to 19.47% cost savings can be achieved if resources are shared between packet streams and circuit connections. And if resource preemptions are allowed, the delay performance for packet streams can be improved by 12% with more frequent preemptions. Our study provides useful insights into the planning and operation of access links.

Optimal Capacity Partitioning in Homogeneous P2P Network

In some networks like WiFi, WLAN, LTE, and WiMAX, the access link capacity division between uplink and downlink can be altered by the users/nodes. A node will always strategize its capacity division to an optimal point, where it allocates minimum capacity for upload to maintain just enough contribution level so as to get sufficient download to completely utilize its download capacity. In this letter, we game theoretically analyze partitioning of access link capacity as a capacity partitioning game in the network, where nodes are performing multiple uploads and downloads. In this game, one of the Nash equilibria is also socially optimal and results in most efficient resource distribution across the network. This Nash equilibrium (NE) corresponds to the optimal point of the capacity partitioning. We also establish that aforementioned NE is the only plausible equilibrium in the game. This NE can be used as a benchmark for various capacity partitioning algorithms used in peer-to-peer networks, such that closer is the algorithm's output to the NE, better will be its performance.

User-perceived quality aware adaptive streaming of 3D multi-view video plus depth over the internet

Video streaming is a foremost and growing contributor in the ever increasing Internet traffic. Since last two decades, due to the enhancement in cameras and image processing technology, we have seen a shift towards multi-view plus depth (MVD) technology from traditional 2D and 3D video technology. This growth comes with deep changes in the Internet bandwidth, video coding and network technologies, which smoothed the mode for delivery of MVD content to end-users over the Internet. Since, MVD contains large amounts of data than single view video, it requires more bandwidth. It is a challenging task for network service provider to deliver such views with the best user’s Quality of Experience(QoE) in dynamic network condition. Also, Internet is known to be prone to packet loss, bandwidth variation, delay and network congestion, which may prevent video packets from being delivered on time. Besides that, different capabilities of end user’s devices in terms of computing power, display, and access link capacity are other challenges. As consequences, the viewing experiences of 3D videos may well degrade, if the quality-aware adaptation techniques are not deployed. In this article, our work concentrates to present a comprehensive analysis of a dynamic network environment for streaming of 3D MVD over Internet (HTTP). We analyzed the effect of different adaptation of decision strategies and formulated a new quality-aware adaptation technique. The proposed technique is promoting from layer based video coding in terms of transmitted views scalability. The results of MVD streaming experiment, using the proposed approach have shown that the video quality of perceptual 3D improves significantly, as an effect of proposed quality aware adaptation even in adverse network conditions.

Optimal Beamforming With Limited Feedback for Millimeter-Wave in-Band Full-Duplex Mobile X-Haul Network

To increase the flexibility of network architecture, a mobile X-haul network (MXN) structure has been considered, in which the wireless front-haul, mid-haul, and backhaul links are integrated into a wireless X-haul link. Accordingly, the mobile station can be served by flexible transmission reception point (f-TRP) or remote radio head through the access link and the associated data should be delivered from XDU to the f-TRP through the X-haul link. Accordingly, the system throughput is determined by the minimum value of the access link capacity and the X-haul link capacity. In this paper, when millimeter-wave (mmWave) is exploited in such MXN with in-band full duplex, the optimal beamforming strategy is proposed, in which the receive beamforming for the X-haul link and the transmit beamforming for the access link are jointly designed to maximize the system throughput. Furthermore, we investigate the rate loss due to the quantization error of the channel state information at f-TRP with limited feedback, in which its upper bound is analytically derived and exploited in the determination of the number of feedback bits for a given finite rate loss.

A DASH-based HEVC multi-view video streaming system

Recent advancement in cameras and image processing technology has generated a paradigm shift from traditional 2D and 3D video to multi-view video (MVV) technology, while at the same time improving video quality and compression through standards such as high efficiency video coding (HEVC). In multi-view, cameras are placed in predetermined positions to capture the video from various views. Delivering such views with high quality over the Internet is a challenging prospect, as MVV traffic is several times larger than traditional video, since it consists of multiple video sequences, each captured from a different angle, requiring more bandwidth than single-view video to transmit MVV. In addition, the Internet is known to be prone to packet loss, delay, and bandwidth variation, which adversely affect MVV transmission. Another challenge is that end users' devices have different capabilities in terms of computing power, display, and access link capacity, requiring MVV to be adapted to each user's context. In this paper, we propose an HEVC multi-view system using Dynamic Adaptive Streaming over HTTP to overcome the above-mentioned challenges. Our system uses an adaptive mechanism to adjust the video bit rate to the variations of bandwidth in best effort networks. We also propose a novel scalable way for the multi-view video and depth content for 3D video in terms of the number of transmitted views. Our objective measurements show that our method of transmitting MVV content can maximize the perceptual quality of virtual views after the rendering and hence increase the user's quality of experience.

Adaptive multiview video streaming: challenges and opportunities

Delivering multiview video content over present packet networks poses multiple challenges. First, the best effort nature of the Internet exposes media packets to variable bandwidth, loss, and delay as they traverse the network. Second, the prediction dependencies employed to maximize compression efficiency make the reconstruction process at the client extremely vulnerable to missing data. Third, the heterogeneity of client devices in terms of computing power, display capabilities, and access link capacity necessitates customizing the streaming process per user. My article reviews existing opportunities for addressing these challenges from within each of the three main stages of the content delivery pipeline (i.e., encoding, transmission, and reconstruction). Concretely, I first describe adaptive source coding techniques that construct a compressed representation of the multiview video source that exhibits resilience to network bandwidth variations and client view selection uncertainty. Then I discuss intelligent methods for error protection, caching, and packet scheduling that organize the transmission of multiview data in a bandwidth-effective way. Here, I also review prospective multipath and cloud-assisted techniques for multiview video streaming. Finally, I identify robust client-side content reconstruction schemes and adaptive media playout methods that can minimize the impact of missing data and enhance the user's interactive experience. Then I proceed to describe community-driven streaming techniques for delivering interactive multiview content over a population of social peers. The article concludes with an outline of approaches for synergistic exploitation of the techniques I will present theretofore, jointly across the different layers of the network protocol stack at which they individually operate. Here, I also highlight the main deployment challenges for some of these techniques, and how their design should be addressed accordingly, to overcome them.

Characterization of the busy-hour traffic of IP networks based on their intrinsic features

Internet traffic measurements collected during the busy hour constitute a key tool to evaluate the operation of networks under the heaviest-load case scenarios, and further provide a means to network dimensioning and capacity planning. In this light, this study provides a throughout analysis of the busy-hour traffic measurements of an extensive set of universities, regional networks, and Internet exchange points collected from the Spanish Research and Education Network, RedIRIS. After showing that the traffic volumes observed in the busy hour over time can be modeled by a white Gaussian process, this work takes one step further and examines the influence of the networks’ intrinsic features, mainly population size and access link capacity, on the busy-hour traffic. Well-known statistical methodologies, such as ANOVA and ANCOVA, show that the network size in terms of number of users justifies most of the busy-hour traffic information. We further provide a linear-regression model that adjusts the amount of traffic that each network user contributes to the busy-hour traffic mean values, with a direct application to the problem of link capacity planning of IP networks.

Load-Balanced and Interference-Aware Spanning Tree Construction Algorithm for TDMA-Based Wireless Mesh Networks

Wireless mesh networks have been attracting many users in recent years. By connecting base stations (mesh nodes) with wireless connections, these network can achieve a wide-area wireless environment with flexible configuration and low cost at the risk of radio interference between wireless links. When we utilize wireless mesh networks as infrastructures for Internet access, all network traffic from mobile nodes goes through a gateway node that is directly connected to the wired network. Therefore, it is necessary to distribute the traffic load by deploying multiple gateway nodes. In this paper, we propose a spanning tree construction algorithm for TDMA-based wireless mesh networks with multiple gateway nodes so as to maximize the traffic volume transferred between the mesh network and the Internet (system throughput) by taking account of the traffic load on the gateway nodes, the access link capacity and radio interference. Through a performance evaluation, we show that the proposed algorithm increases the system throughput regardless of the bottleneck position and achieves up to 3.1 times higher system throughput than a conventional algorithm.

Monitoring access link capacity using TFRC probe

Accurate estimation of network characteristics based on end-to-end measurements is an important and challenging problem. With the increasing variety and sophistication of Internet access methods, the mobility of the users and the need for seamless handoff across them, monitoring access link capacity becomes critical for efficient multimedia delivery. In fact, this allows the multimedia server to properly adjust its sending rate to the rapidly changing access speed of the mobile client. This problem is challenging because most of the existing capacity monitoring schemes are active, like Pathrate (and therefore, introduce extra overhead on the bandwidth limited access link). Moreover, the access link is often asymmetric (e.g. ADSL, 1×RTT, etc.) thus preventing the use of round-trip monitoring schemes such as Pathchar and CapProbe. In this study, we propose and evaluate a passive, one-way link capacity monitoring tool called TFRC Probe. With TFRC Probe the source can monitor the forward direction capacity of both asymmetric and symmetric access links, and can rapidly and accurately adapt its transmissions rate accordingly. We validate TFRC Probe with both simulation and testbed experiments, and show that TFRC Probe is a very flexible tool that can accurately track frequent changes in access capacity.