High Bandwidth Utilization Research Articles

Adaptive Predictive Proportional Controller for IEEE 802.17

The Resilient Packet Ring (IEEE 802.17) fairness algorithm is simple, but exhibits some weaknesses. The bandwidth allocation severely oscillates when the traffic is unbalanced. Several algorithms have been proposed in recent years to overcome this issue. For example, the proportional controller is used for solving the fairness problem. The proportional controller is able to converge to the fair rates with no oscillations at the steady state. Unfortunately, the controller shows bandwidth oscillations and becomes unstable if the network delay is significant. In this paper, the impact of the delay is studied analytically and through simulation. Also, the Smith’s principle is used to compensate the ring delay. Moreover, the controller gain is tuned using a fuzzy logic system. The performance is evaluated through simulation and the results show that the proposed adaptive predictive proportional controller assures fairness, stability and high bandwidth utilization even in ring network with large delay.

Comparative Study of EIGRP and OSPF Protocols based on Network Convergence

Dynamic routing protocols are one of the fastest growing routing protocols in networking technologies because of their characteristics such as high throughput, flexibility, low overhead, scalability, easy configuration, bandwidth, and CPU utilization. Albeit convergence time is a critical problem in any of these routing protocols. Convergence time describes summary of the updated, complete, and accurate information of the network. Several studies have investigated EIGRP and OSPF on the internet; however, only a few of these studies have considered link failure and addition of new links using different network scenarios. This research contributes to this area. This comparative study uses a network simulator GNS3 to simulate different network topologies. The results are validated using Cisco hardware equipment in the laboratory. The network topology implemented in this research are star and mesh topology. The results are validated using Cisco hardware equipment in the laboratory. Wireshark is effectively used in capturing and analyzing the packets in the networks. This helps in monitoring accurate time response for the various packets. The results obtained from Wireshark suggest the EIGRP has a higher performance in terms of convergence duration with a link failure or new link added to the network than the OSPF routing protocol. Following this study EIGRP is recommended for most heterogeneous network implementations over OSPF routing protocol.

Flexible Multi-Thread Dynamic Bandwidth Allocation Algorithm in VPONs Based on LR WDM/TDM PON

With the smooth upgrade of the access network, multiple tuning-time devices will coexist in the long-reach access network, and the subsequent problems of high round-trip time (RTT) and optical network unit (ONU) tuning delay need to be solved urgently. In this paper, a multi-thread multiple tuning-time devices coexistence (MT-MTDC) bandwidth allocation algorithm is proposed. This algorithm can solve the problems of high RTT and ONU tuning delay in virtual passive optical network (VPON) based on long-reach wavelength division multiplexing/time division multiplexing passive optical network (LR WDM/TDM PON). Firstly, Multi-threaded polling mechanism is introduced into multi-mode coexistence VPON. Next, the number of wavelengths and threads is selected adaptively to ensure high bandwidth utilization. Then, the mechanism of dynamically adjusting the thread window is proposed. The mechanism strengthens the collaboration ability between threads and solves the degradation problem of the multi-thread algorithm. Furthermore, the construction of tuning buffer and the setting of time flag effectively solve the problem of more frequent ONU tuning pressure and ONU transmission conflict caused by multi-threaded polling algorithm. Finally, by comparing with the multi-thread longest-first first-available (MT-LFFA) algorithm and the multi-tuning-time ONU scheduling (MOS) algorithm, the proposed algorithm demonstrates its effectiveness in terms of polling cycle time, average tuning delay, bandwidth utilization and average packet delay.

A Joint Demodulation and Estimation Algorithm for Plasma Sheath Channel: Extract Principal Curves With Deep Learning

For reentry communication, owing to the influence of the time-varying plasma sheath, the received IQ baseband signals are severely rotated on constellation. Researches have shown that the frequency of electron density varies from 20kHz to 100 kHz which is on the same order as the symbol rate of most TT&C communication systems and traditional estimation algorithms cannot track the variation of channel. In this letter, motivated by principal curve analysis, we propose a deep learning (DL) algorithm which is called symmetric manifold network (SMN) to extract the curves on the constellation and classify the signals based on the curves. The key advantage is that SMN can achieve joint optimization of demodulation and estimation. From our simulation results, the new algorithm significantly reduces the symbol error rate (SER) compared to existing algorithms and enables accurate estimation of fading with extremely high bandwidth utilization rate.

A Reinforcement Learning Approach to Energy Efficiency and QoS in 5G Wireless Networks

Satisfying the huge demand for high bandwidth in 5G networks is in part achieved by vertical densification of the network infrastructure with so-called small-cell base stations. As a direct consequence, the performance of 5G networks intrinsically suffers from: 1) a huge inter-cell interference due to the network density and 2) a large energy waste that results from the high redundancy of lightly loaded, always-on, and small-cell base stations. In this paper, we use a game theoretic approach to design a distributed energy efficient bandwidth sharing mechanism for small-cell networks. To circumvent the combinatorial nature of searching in the huge strategy space, we invoke a reinforcement learning approach to intelligently guide the search toward good solutions. More precisely, our solution relies on dynamically learning good strategies for the user-equipment association and orthogonal frequency division multiple access (OFDMA) scheduling to strike a balance between energy efficiency and high bandwidth utilization. Our model takes into account inter-cell interference and the diversity of user quality of service requirements.

A Framework for Adaptive Residual Streaming for Single-Player Cloud Gaming

Applying cloud technology to 3D interactive multimedia applications is a promising way to provide flexible and cost-efficient online high-bandwidth immersive services to a large population of end users. One main reason cloud systems are popular among users is the fact that it relaxes the hardware requirements for high-end interactive visual applications. As most of the computational tasks are done on cloud servers, users no longer need to upgrade their hardware as frequently to keep up with the ever-increasing high-end computing requirements of the latest applications. Moreover, cloud systems make it easier for a user to enjoy applications on different platforms, including mobile devices that are usually not powerful enough to run high-end, memory-intensive services. In short, applying cloud technology to high-end immersive applications has advantages in cost-efficiency and flexibility both for the end users and the service providers. However, there are two main drawbacks to applying cloud technology to 3D interactive multimedia services: (1) high-bandwidth utilization and (2) latency. In this article, we propose a framework that addresses the two problems for single-player cloud gaming by using a combination of collaborative rendering, progressive meshes, and 3D image warping techniques. The experimental results show that the proposed system can reduce the bandwidth usage and improve the visual quality by utilizing local computing power on the client. The results also show that the interaction latency can be reduced somewhat by sacrificing some degree of visual quality in the end system.

Producer Mobility Support Schemes for Named Data Networking: A Survey

Mobile devices connectivity and data traffic growth requires scalable and efficient means of data distribution over the Internet. Thus, influenced the needs for upgrading or replacing the current Internet architecture to cater the situation as Named Data Networking (NDN) was proposed. NDN is clean-slate Internet architecture, proposed to replace IP with hierarchical named content that utilizes route aggregation to improve scalability and support mobility. Although, NDN provides supports for content consumer mobility with the help of catching capabilities, however, content producer faces many problems similar to mobility in IP architecture, such as, long handoff delay, unnecessary Interest packet losses and high bandwidth utilization. Hence, many concepts and schemes were proposed to address these problems. This paper reviewed and conceptually analyzed the schemes based on their fundamental design that broadly categorized into indirection-based approach, mapping-based approach, locator-based approach and control/data plane-based approach. In the review analysis, mapping-based approach schemes provide optimal path for packets delivery, high handoff delay Indirection-based and locator-based approach schemes provide normal handoff delay, but introduces tiangular routing path. The control/data plane-based approach schemes provide sub-optimal routing path and high handoff delay. The paper provided both strength and weakness of each scheme for further research.

Improvement of bit error rate performance of MC-CDMA system by using adaptive digital modulation schemes

In Wireless Communication, the transmission channel suffers due to multipath propagation and channel dispersion due to Inter Symbol Interference (ISI), thereby degrades the system performance greatly. Future communication requires high data rate and effective utilization of bandwidth. Hence, there is a need to improve the Bit Error Rate (BER). The proposed work is Adaptive Modulation (AM), combined with Multi Carrier Code Division Multiple Access (MC-CDMA) based transmission system. It is a promising way to increase the data rate and it uses bandwidth in a efficient manner. The Adaptive Modulation based MC-CDMA systems applied to a wide-area environment, can achieve high data rate up to 100Mbps. In this paper M-ary PSK, M-ary QAM and M-ary CPM modulation techniques are used. The Adap-tive modulation based MC-CDMA systems perform well for around 10 number of users. As a whole, the adaptive MC-CDMA system is found to give the optimum BER performance of given digital modulation schemes for fourth generation environment.

A Study of All-fiber Different Bandwidth Interleaver Based on Linear Chirped Fiber Grating

To improve the utilization efficiency of interleaver bandwidth in 10Gbit/s plus 40Gbit/s mixed system, an all-fiber MZI different bandwidth optical interleaver based on linear chirped fiber grating is proposed and discussed in this paper. The same two linear chirped fiber gratings are written at the output of conventional Mach-Zehnder interferometer (MZI), which constitute a reflective cascaded MZI filter. Based on its structure, the output spectrum expression is established and described by using the principle of fiber transmission, reflex theory of fiber grating and the matrix transfer function. Influences on its transmission characteristics by such factors as the coupling coefficients of the couplers, structure parameters of fiber grating and the length differences of the interferometer arms are numerically analyzed and optimized. The results of numerical simulation indicate that when the above parameters are some certain values, 50GHz input single of device is separated into channel spacing of 100GHz odd-even two output signals. Their spectrum bandwidth are 64.67GHz and 36.98GHz at 3dB, they satisfy the requirement of different transmission rates on bandwidth in 10Gbit/s plus 40Gbit/s mixed system and implements different bandwidth transmission. The device has a certain ability to resist the deviation. Compared with the ordinary cascaded MZI interleaver, the advantage of the new interleaver is that reduced numbers of coupler. It has higher bandwidth utilization that compared with the equal bandwidth interleaver, and achieves different bandwidth transmission within 100GHz.

Making pull-based graph processing performant

Graph processing engines following either the push-based or pull-based pattern conceptually consist of a two-level nested loop structure. Parallelizing and vectorizing these loops is critical for high overall performance and memory bandwidth utilization. Outer loop parallelization is simple for both engine types but suffers from high load imbalance. This work focuses on inner loop parallelization for pull engines, which when performed naively leads to a significant increase in conflicting memory writes that must be synchronized. Our first contribution is a scheduler-aware interface for parallel loops that allows us to optimize for the common case in which each thread executes several consecutive iterations. This eliminates most write traffic and avoids all synchronization, leading to speedups of up to 50X. Our second contribution is the Vector-Sparse format, which addresses the obstacles to vectorization that stem from the commonly-used Compressed-Sparse data structure. Our new format eliminates unaligned memory accesses and bounds checks within vector operations, two common problems when processing low-degree vertices. Vectorization with Vector-Sparse leads to speedups of up to 2.5X. Our contributions are embodied in Grazelle , a hybrid graph processing framework. On a server equipped with four Intel Xeon E7-4850 v3 processors, Grazelle respectively outperforms Ligra, Polymer, GraphMat, and X-Stream by up to 15.2X, 4.6X, 4.7X, and 66.8X.

Responsive high throughput congestion control for interactive applications over SDN-enabled networks

New interactive video applications are increasingly emerging over the Internet; these interactive applications are characterized by high bandwidth requirements that fluctuates depending on end-user actions (e.g. less bandwidth is usually needed for stationary scenes). More importantly, this interactive class of services also involves a requirement for high responsiveness (i.e. low latency) from the network, in order to respond in real-time to end-user actions. One emerging service of this nature is 360° video streaming; another example is cloud-based gaming services. In this paper, we focus specifically on JPIP (JPEG 2000 Interactive Protocol) applications that support remote interactive video browsing with dynamic pan and zoom capabilities, as a highly representative example of the interactive service class. Existing network communication services are mostly agnostic to latency implications, and hence are not well adapted to such interactive applications. Meanwhile, explicit resource reservation protocols have not been widely deployed, and do not consider the time-varying dependencies that naturally arise in interactive applications. In this work, we leverage software defined networking (SDN) principles to support a proposed “interactive service” class. The main contributions of this work are a network-exposed application programming interface (API) that provides visibility into the state of the network, an SDN-assisted congestion control algorithm that utilizes network state information to achieve the desired low latency and high bandwidth utilization requirements, and a fair resource assignment algorithm that shares available bandwidth among interactive and non-interactive traffic dynamically – all without a reservation protocol.

Advanced QoS Provisioning and Mobile Fog Computing for 5G

This paper presents a novel QoS and mobile cloud and fog computing framework for future fifth generation (5G) of mobile and fixed nodes with radio network aggregation capability. The proposed 5G framework is leading to high QoS provisioning for any given multimedia service, higher bandwidth utilization, traffic load sharing, mobile cloud plus fog computing features, and multi‐radio interface capabilities. The framework is user‐centric, targeted at always‐on connectivity with using radio network aggregation for available mobile broadband connections, and empowered with mobile cloud and fog computing advantages. Moreover, our proposed framework is using Lyapunov drift‐plus‐penalty theorem that provides a methodology for designing algorithm to maximize the average throughput and stabilize the queuing. Also, we are showing the upper bound of the consumed power and the lower bound of the battery lifetime for the proposed 5G terminal. The advanced performance of our 5G QoS plus MCC framework is evaluated using simulations and analysis with multimedia traffic in heterogeneous mobile and wireless environment. The simulation results are showing that the maximal network utilization, maximal throughput, minimal end‐to‐end delay, efficient energy consumption, and other performance improvements are achieved.

Time-Constrained Big Data Transfer for SDN-Enabled Smart City

With advanced ICT, the ever-rapid development of informatization has become an integral part of smart city services in healthcare, transportation, energy, education, business, community life, and so on. A huge amount of data, called big data, is generated from various sources, and effective analysis and utilization of big data has become a key factor in the success of smart city services. However, in order to achieve precise big data analytics and make real-time decisions, one of the challenging issues is how to efficiently deliver the huge amounts of collected data to the processing servers. In this article, we first propose a novel architecture to support smart city services based on SDN technology. Then we study the time-constrained big data transfer scheduling (TBTS) problem under the proposed architecture, and present an intelligent strategy to address the TBTS issue by utilizing the SDN controller to conduct dynamic flow control and multi-path transfer scheduling. Simulation results demonstrate that the proposed strategy can efficiently support big data transfer in terms of low transfer delay and high bandwidth utilization.

Joint Optimization of Bandwidth for Provider and Delay for User in Software Defined Data Centers

In large-scale Internet applications running on geographically distributed datacenters, such as video streaming, it is important to efficiently allocate requests among datacenters. To the best of our knowledge, existing approaches, however, either solely focus on minimizing total cost for provider, or guaranteeing QoS for end-users. In this paper, we apply the software defined network (SDN) controller to enable the central control of the entire network, and propose a joint optimization model to consider high bandwidth utilization for provider and low delay for users. We present the Nash bargaining solution (NBS) based method to model both requirements of provider’s high bandwidth utilization and end-users’ low delay. Specifically, we formulate the design of request allocation under those requirements as an optimization problem, which is NP-hard. To solve such hard optimization problem, we develop an efficient algorithm blending the advantages of Logarithmic Smoothing technique and the auxiliary variable method. According to the theoretical analysis, we verify the existence and uniqueness of our solution and the convergence of our algorithm. We conduct a large amount of experiments based on real-world workload traces and demonstrate the efficiency of our algorithm compared to both greedy and locality algorithms.

Function Split Between Delay-Constrained Routing and Resource Allocation for Centrally Managed QoS in Industrial Networks

Industrial networks demand centrally controlled quality of service (QoS), often in the form of hard real-time guarantees. Software-defined networking (SDN) provides a convenient paradigm for central QoS control. However, existing SDN-based solutions cannot guarantee hard real-time QoS as they rely on a control loop over the forwarding (data) and control planes. We propose a novel SDN-based QoS control framework that maintains an accurate network model through network calculus to avoid a control loop over forwarding and control planes, allocates resources to and routes flows over a network of “queue links,” whereby each physical network link houses multiple queue links (with different QoS levels), and manages QoS through a function split between delay-constrained least-cost routing on the network of queue links and the resource allocation to the queue links. This function split greatly reduces the computational complexity while achieving hard real-time QoS with high bandwidth utilization. Our evaluation results indicate that our function split approach allows for online runtime admission control and can achieve bandwidth utilization above 80% while meeting deterministic real-time QoS requirements.

OFPT: OpenFlow based Parallel Transport in Datacenters

Although the dense interconnection datacenter networks (DCNs) (e.g. FatTree) provide multiple paths and high bisection bandwidth for each server pair, the single-path TCP (SPT) and ECMP which are widely used currently neither achieve high bandwidth utilization nor have good load balancing. Due to only one available transmission path, SPT cannot make full use of all available bandwidth, while ECMP`s random hashing results in many collisions. In this paper, we present OFPT, an OpenFlow based Parallel Transport framework, which integrates precise routing and scheduling for better load balancing and higher network throughput. By adopting OpenFlow based centralized control mechanism, OFPT computes the optimal path and bandwidth provision for each flow according to the global network view. To guarantee high throughput, OFPT dynamically schedules flows with Seamless Flow Migration Mechanism (SFMM), which can avoid packet loss in flow rerouting. Finally, we test OFPT on Mininet and implement it in a real testbed. The experimental results show that the average network throughput in OFPT is up to 97.5% of bisection bandwidth, which is higher than ECMP by 36%. Besides, OFPT decreases the average flow completion time (AFCT) and achieves better scalability.

Towards Agile and Smooth Video Adaptation in HTTP Adaptive Streaming

HTTP Adaptive Streaming (HAS) is widely deployed on the Internet for live and on-demand video streaming services. Video adaptation algorithms in the existing HAS systems are either too sluggish to respond to congestion level shifts or too sensitive to short-term network bandwidth variations. Both degrade user video experience. In this paper, we formally study the tradeoff between responsiveness and smoothness in HAS through analysis and experiments. We show that client-side buffered video time is a good feedback signal to guide video adaptation. We then propose novel video rate control algorithms that balance the needs for video rate smoothness and high bandwidth utilization. We show that a small video rate margin can lead to much improved smoothness in video rate and buffer size. We also propose HAS designs that can work with multiple servers and wireless connections. We develop a fully functional HAS system and evaluate its performance through extensive experiments on a network testbed and the Internet. We demonstrate that our HAS designs are highly efficient and robust in realistic network environment.

ENGLISH

Internet represents a shared resource wherein users contend for the finite network bandwidth. Contention among independent user demands can result in congestion, which in turn leads to long queuing delays, packet losses or both. Congestion control regulates the rate at which traffic sources inject packets into a network to ensure high bandwidth utilization while avoiding network congestion. This paper presents a new Active Queue Management algorithm in internet routers using a hybridization of multiresolution wavelet with the classical PID control (MR. Wavelet PID). The aim is to control the router queue length within a desired threshold queue level for a linearized TCP congestion model. The analytical results for a linearized TCP/AQM model are simulated using MATLAB. The performance of the proposed control scheme is evaluated for various network scenarios and the obtained results show the capability of the proposed controller to compensate for a wide range of TCP flows and link capacity variations.

Full-Duplex Airborne Ultrasonic Data Communication Using a Pilot-Aided QAM-OFDM Modulation Scheme.

Orthogonal frequency division multiplexing (OFDM) has been extensively used in a variety of broadband digital wireless communications applications because of its high bandwidth utilization efficiency and effective immunity to multipath distortion. This paper has investigated quadrature amplitude modulation and OFDM methods in air-coupled ultrasonic communication, using broadband capacitive ultrasonic transducers with high- k dielectric layers. OFDM phase noise was discussed and corrected using a pilot-aided estimation algorithm. The overall system data rate achieved was up to 400 kb/s with a spectral efficiency of 2 b/s/Hz. An ultrasonic propagation model for signal prediction considered atmospheric absorption of sound in air, beam divergence, and transducer frequency response. The simulations were compared with the experimental results, and good agreement was found between the two. Two-way communication through air was also implemented successfully by applying three-way handshaking initialization and an adaptive modulation scheme with variable data rates depending on the transmission distance, estimated using received signal strength indication measurement. It was shown that the error-free transmission range could be extended up to 2.5 m using different system transfer rates from 400 kb/s down to 100 kb/s. In full-duplex transmission mode, the overall error-free system data rate achieved was 0.8 Mb/s up to 1.5 m.

UFalloc: Towards Utility Max-min Fairness of Bandwidth Allocation for Applications in Datacenter Networks

Providing fair bandwidth allocation for applications is becoming increasingly compelling in cloud datacenters, as different applications compete for the shared datacenter network resources. While existing solutions mainly provide bandwidth guarantees for virtual machines (VMs) or tenants with the aim of achieving the VM-level or tenant-level fairness of bandwidth allocation, scant attention has been paid to providing bandwidth guarantees for applications to achieve the fairness of application performance (utility). In this paper, we introduce a rigorous definition of application-level utility max-min fairness, which guides us to develop a non-linear model to investigate the relationship between the utility fairness and bandwidth allocation for applications. Based on such a model, we further arbitrate the intrinsic tradeoff between the network bandwidth utilization and utility fairness of application bandwidth allocation, using a tunable fairness relaxation factor. To improve the bandwidth utilization while maintaining the strict utility fairness of bandwidth allocation, we design UFalloc, an application-level Utility max-min Fair bandwidth allocation strategy in datacenter networks. With extensive experiments using OpenFlow in Mininet virtual network environment, we demonstrate that UFalloc can achieve high utilization of network bandwidth while maintaining the utility max-min fair share of bandwidth allocation with a certain degree of fairness relaxation, yet with an acceptable computational overhead.