Improve Bandwidth Utilization Research Articles

Receiver Design for Faster-Than-Nyquist Signaling: Deep-Learning-Based Architectures

Faster-than-Nyquist (FTN) is a promising paradigm to improve bandwidth utilization at the expense of additional intersymbol interference (ISI). In this paper, we apply state-of-the-art deep learning (DL) technology into receiver design for FTN signaling and propose two DL-based new architectures. Firstly, we propose an FTN signal detection based on DL and connect it with the successive interference cancellation (SIC) to replace traditional detection algorithms. Simulation results show that this architecture can achieve near-optimal performance in both uncoded and coded scenarios. Additionally, we propose a DL-based joint signal detection and decoding for FTN signaling to replace the complete baseband part in traditional FTN receivers. The performance of this new architecture has also been illustrated by simulation results. Finally, both the proposed DL-based receiver architecture has the robustness to signal to noise ratio (SNR). In a nutshell, DL has been proved to be a powerful tool for the FTN receiver design.

Experiment Study of Downstream Traffic Balancing Strategy on 40G Long Reach Coherent PON

Abstract Distributed high-bandwidth consumption services such as cloud computing require large-capacity, long-distance, and wide-coverage development requirements for Next-Generation Passive Optical Networks (NG-PON2). With the development of NG-PON2 technology, the optical line terminal (OLT) device structure of passive optical network (PON) system is also increasingly complex and heterogeneous. This leads to the problem of network congestion and low bandwidth utilization caused by the unbalanced use of link and port resources in the traditional core network in the PON network. Based on the 40G coherent PON experimental system, this paper studies the traffic balancing problem of OLT equipment, and proposes a dynamic traffic balancing strategy based on real-time monitoring of load sharing and reporting of police and periodic adjustment. The experimental results show that the designed dynamic traffic balancing strategy can effectively reduce the PON network blocking rate and improve bandwidth utilization.

Performance Analysis of SCTP for Multiple Parallel Streams

SCTP is a connection oriented general purpose transport protocol and applications presented in the transport layer for concept of streams. Different streams provide multiple end to end connections that enables independent send and receiver buffer at two end points. In this paper we performed performance measurement for simultaneous parallel streams. Performance of SCTP is closely examined for two parallel streams and considerable improvement of bandwidth utilization observed as compared to single stream

Path‐flow matching: Two‐sided matching and multiobjective evolutionary algorithm for traffic scheduling in cloud data* center network

AbstractImproving the operational efficiency of data center has always been an important direction for the development of ICT. In this paper, we apply two‐sided matching decision‐making process in game theory to traffic scheduling problem in data center network. From the perspective of matching between flow and path, the traffic scheduling is properly arranged. We first propose and model the path‐flow matching problem, considering the preference ordering, then formulate the problem as a multiobjective optimization problem with the target to ensure the stability and satisfaction from the matching scheme, and design a preference‐based path‐flow ordering method Extended PIAS, and finally propose a lightweight scheduling algorithm LinkGame based on multiobjective evolutionary algorithm. Compared with the previous scheduling methods (ECMP, Hedera, and Fincher), experiment results demonstrate that LinkGame can simultaneously consider the stability and satisfaction of the matching results, with improved bandwidth utilization and flow completion time.

An efficient and social-aware distributed in-network caching scheme in named data networks using matching theory

One of the main characteristics of Named Data Networks (NDN) which makes it a promising architecture for the future of the Internet is its universal in-network caching. Due to the limited caching capacity of the network and the infinite amount of data objects, the cache management scheme becomes a challenging task in NDN. While existing cache management schemes utilize network’s caching capacity inefficiently by redundantly keeping popular objects across the network and concentrate on improving bandwidth utilization, we focus on a novel criterion to elevate the cache utilization efficiency. In this paper, a distributed solution that associates the objects to the cache-enabled nodes and maximizes the total network’s social welfare is proposed which models the problem of network’s social welfare maximization as a many-to-one matching game. Further, it is proved that the proposed solution has a number of desired properties. The resulting matching is stable and the outcome of the proposed algorithm is in Competitive Equilibrium, the social-welfare of the proposed algorithm converges to the social-welfare of the centralized optimal approach as the price step number is sufficiently small, the proposed algorithm converges after a finite number of iterations with relatively low overhead and the cost of retrieving the required objects is the minimum for the Internet Service Providers (ISP). Finally, simulation results show the convergence of our proposed scheme to the centralized optimal solution and its outperformance against the default applied caching scheme in NDN in terms of both network’s social welfare and hit ratio.

Improving bandwidth utilization by compressing small-payload traffic for vehicular networks

The low bandwidth utilization is a serious problem for mobile services over vehicular networks. This is mainly resulted from the high-rate transmission of packets carrying small payloads. Some solu...

Compressed Robust Transmission for Remote Sensing Services in Space Information Networks

With rapid development of space platforms such as small satellites and UAVs for public services, remote sensing services have been considered as one of the most promising services in space information networks. Small satellites and UAVs equipped with sensors such as cameras capture on-demand images and videos. Various remote sensing services using these images and videos can be enabled for public users, including geographical photography, navigation, live broadcast, surveillance and monitoring, road traffic analysis, and so on. In these remote sensing services, images and videos must be transmitted to individual users in a real-time manner. Therefore, the transmission techniques adopted will have direct impact on the received quality of users. As a newly emerged robust wireless transmission scheme, Soft- Cast is able to accommodate multiple receivers of different channel conditions by directly transmitting power scaled samples. In this article, CS and robust transmission-based SoftCast are investigated for downlink image/video-based remote sensing services under resource-limited, time-varying, and heterogeneous space environments, which are developed in order to improve bandwidth utilization efficiency and to achieve graceful performance, respectively. The proposed ComCast scheme is implemented by integrating CS and robust transmission into one framework to exploit benefits from both techniques. Furthermore, resource allocation in ComCast is also addressed to minimize system distortion caused by both CS and transmission. Simulation results demonstrate that ComCast outperforms the existing CS-based scheme as well as the robust transmission scheme in terms of peak signal-to-noise ratio and visual quality.

Size-based queuing

Ethernet has become one of the most researched network technologies for modern, safety-critical, distributed systems due to its maturity and low cost. Standard Ethernet, however, is unsuitable for safety-critical applications due to its lack of delivery guarantees and lack of delay bounds. The Time-Sensitive Networking (TSN) task group proposes several extensions to Standard Ethernet to address these shortcomings. One of the proposed extensions is the Time-Aware Shaper (TAS, IEEE 802.1Qbv-2015) which introduces a gate mechanism that enables scheduled transmissions and minimal jitter for high-priority messages. In order to achieve low jitter for these messages, guard bands are inserted into the schedule of the other traffic classes to ensure that the outgoing link is idle when the transmission of the high-priority message is scheduled to occur. This can result in wasted bandwidth. In this work, we propose Size-Based Queuing (SBQ) - an approach to improve bandwidth utilization in TSN networks that utilize TAS and guard bands. After a detailed description of SBQ, we provide a method to schedule an SBQ-enabled TSN network and conduct a qualitative analysis of the impact of SBQ on the transmission time of messages and the improvements on bandwidth utilization. We show that SBQ can reduce the amount of wasted bandwidth in a network, without impacting the transmission of high-priority messages or requiring extensive changes of the TSN network.

High-priority first dynamic wavelength and bandwidth allocation algorithm in TWDM-PON

Abstract Time and wavelength division multiplexing passive optical network (TWDM-PON) is the mainstream scheme of the next generation access network, and it possesses a number of unique characteristics such as high-bandwidth, long-distance data transmission, and connecting lots of users. As the difference among user traffic demands increases, in order to effectively decrease the network delay and improve resource utilization, a high-priority first dynamic wavelength and bandwidth allocation (HF-DWBA) algorithm in TWDM-PON system is proposed in this study. According to the service-level agreement (SLA), in order to determine the priority of an optical network unit (ONU), the proposed algorithm ensures the high-level ONU traffic distribution in terms of wavelength assignment and bandwidth allocation, and it can execute five types of transmission containers (T-CONTs) as well as four kinds of bandwidth allocation strategies. The results of simulation show that in comparison with traditional algorithms, the proposed HF-DWBA algorithm can effectively reduce end-to-end time delay and improve bandwidth utilization ratio, while making fairness among different types of bandwidth allocation strategies.

Segment Scheduling Scheme for Efficient Bandwidth Utilization of HTTP Adaptive Streaming in Multipath Environments

HyperText Transfer Protocol (HTTP) adaptive streaming has been receiving attention to provide efficient video streaming services by adaptively adjusting the transmission rate. With increased demand for high-quality video streaming, since mobile devices are now equipped with multiple wireless interfaces connected to different networks (3G/4G or Wi-Fi), one possible solution to provide a better quality of experience (QoE) is to use multipath-based transmission schemes. In conventional HTTP adaptive streaming systems, the segment request policy initially operates in a buffering state and switches to a steady state once the playout buffer reaches a threshold. In the steady state, the client generates an ON/OFF traffic pattern that degrades bandwidth utilization and user QoE in multipath environments. In this paper, we propose a segment scheduling scheme for efficient bandwidth utilization in multipath environments. In our scheme, we first propose a collective segment request policy to improve bandwidth utilization and reducing the frequency of OFF periods. To improve network responsiveness, we present a method for adaptively adjusting the request interval. Subsequently, we propose a segment scheduler to prevent the out-of-order problem in multipath environments. Finally, a rate adaptation algorithm for the proposed request policy is proposed. Through simulation, we prove that our scheme significantly improves bandwidth utilization and increases the average bitrate.

Research of Message Scheduling for In-Vehicle FlexRay Network Static Segment Based on Next Fit Decreasing (NFD) Algorithm

FlexRay is becoming the in-vehicle communication network of the next generation. In this study, the main contents are the FlexRay network static segment scheduling algorithm and optimization strategy, improve the scheduling efficiency of vehicle network and optimize the performance of communication network. The FlexRay static segment characteristic was first analyzed, then selected bandwidth utilization as the performance metrics to scheduling problem. A signal packing method is proposed based on Next Fit Decreasing (NFD) algorithm. Then Frame ID (FID) multiplexing method was used to minimize the number of FIDs. Finally, experimental simulation by CANoe. FlexRay software, that shows the model can quickly obtain the message schedule of each node, effectively control the message payload size and reduced bus payload by 16.3%, the number of FID drops 53.8% while improving bandwidth utilization by 32.8%.

FUZA: An Algorithm for Definition of Reliable Virtual Networks to the Edge as a Service Paradigm

Edge as a Service (EaaS) is a promising approach to increase the management capacity of Internet Service Providers (ISPs) and to support QoS/QoE for their clients. EaaS uses Virtual Networks (VNs) to ease the management of ISPs. Thus, EaaS needs an algorithm to define virtual topologies for the VNs considering the resource utilization, the energy consumption and the service delivery reliability. Within this context, this paper presents Fuzzy for Allocation (FUZA) algorithm to define reliable virtual topologies for EaaS. FUZA is based on a fuzzy system and uses energy consumption and bandwidth availability to define the most suitable virtual topology for the VN requested. The results suggest that the proposed algorithm can deploy reliable VNs, while improving bandwidth utilization and energy consumption of the network infrastructure.

Efficient Performance-Centric Bandwidth Allocation with Fairness Tradeoff

Fair bandwidth allocation in datacenter networks has received a substantial amount of research attention, as multiple tenants are hosted by virtual machines in a public cloud. In the context of private datacenters, link bandwidth is shared among applications running data parallel frameworks, such as MapReduce, instead. In this paper, we introduce the rigorous definition of performance-centric fairness , with the guiding principle that the performance that data parallel applications will enjoy should be proportional to their weights. We first investigate the problem of maximizing application performance while maintaining strict performance-centric fairness. We then present an inherent tradeoff between fairness and efficiency, which is interpreted from the perspectives of bandwidth utilization and social welfare, respectively. From the first perspective, we propose an algorithm to improve bandwidth utilization by introducing an extended version of fairness. From the second perspective, we formulate an optimization problem of bandwidth allocation that maximizes the social welfare across all the applications, allowing a tunable degree of relaxation on performance-centric fairness. A distributed algorithm is then presented to solve the problem, based on dual based decomposition. With extensive simulations, we demonstrate the effectiveness of our algorithms in improving efficiency and application performance (by up to $1.4X$ ), with flexible degree of relaxation on the performance-centric fairness.

Dynamic Traffic Scheduling and Congestion Control across Data Centers Based on SDN

Software-defined Networking (SDN) and Data Center Network (DCN) are receiving considerable attention and eliciting widespread interest from both academia and industry. When the traditionally shortest path routing protocol among multiple data centers is used, congestion will frequently occur in the shortest path link, which may severely reduce the quality of network services due to long delay and low throughput. The flexibility and agility of SDN can effectively ameliorate the aforementioned problem. However, the utilization of link resources across data centers is still insufficient, and has not yet been well addressed. In this paper, we focused on this issue and proposed an intelligent approach of real-time processing and dynamic scheduling that could make full use of the network resources. The traffic among the data centers could be classified into different types, and different strategies were proposed for these types of real-time traffic. Considering the prolonged occupation of the bandwidth by malicious flows, we employed the multilevel feedback queue mechanism and proposed an effective congestion control algorithm. Simulation experiments showed that our scheme exhibited the favorable feasibility and demonstrated a better traffic scheduling effect and great improvement in bandwidth utilization across data centers.

An Energy Efficient Cell Selection Framework for Femtocell Networks With Limited Backhaul Link Capacity

Dense deployment of femtocells improves the network capacity without significantly burdening the operator with huge capital and operational expenditure. However, extremely dense deployment of femtocells comes with the cost of increased cochannel interference and higher energy consumption. Additionally, femtocells burden the existing ADSL/broadband lines by using them as backhaul to connect to the cellular core network. A cell selection scheme defines the criteria on which mobile users associate themselves with base stations. This criteria may include received signal quality, available bandwidth, and energy consumption. Hence, cell selection plays a crucial role in system capacity, load balancing, and energy consumption. In this paper, we provide a framework for femtocell deployment in the urban scenario where interference, energy consumption, and backhaul capacity are major concerns. We first model the energy consumption of base stations, user equipment, and wired backhaul links. Then, we propose an efficient spectrum and power allocation technique to mitigate interference and improve bandwidth utilization in the uplink and downlink, respectively. Finally, we suggest a novel QoS-aware cell selection scheme that assigns mobile users to femtocells considering the capacity improvement obtained per unit increase in energy consumption. The proposed cell selection scheme incorporates the energy consumption of the wired backhaul links and their limited capacity constraint into the cell selection criteria. Our proposed spectrum and power allocation technique, when combined with the proposed cell selection, leads to a significant reduction in energy consumption without any deterioration in the system capacity. Simulation results confirm that our proposed framework has the potential to significantly improve the energy efficiency of the network.

Intelligent Requests Algorithm Based Scheduling and Efficient Dynamic Bandwidth Allocation to Improve QoS for EPONs

Abstract The proposed traffic grooming methodology for long-reach-passive optical networks will decrease the latency in upstream. The scheduling and wavelength assignment for ethernet passive optical networks has been shown to perform much better in terms of delay. The dynamic traffic grooming algorithm based on intelligent water drop is proposed in which new depositions function has been introduced for efficient handling of bandwidth. Therefore, once equally distanced optical network units were scheduled on constant wavelengths, the void formation impact is reduced. The outcomes conjointly depict the result of the planned methodology on bandwidth utilization improvement and jitter by 1.46 and 408.66 µs improvements respectively, even overall latency is improved by 465.83 µs by value. These results depict the validity of the planned dynamic bandwidth allocation methodology for traffic grooming.

High resolution target range estimation in discontinuous spectra high frequency radar

ABSTRACTThe range resolution is limited by insufficient continuous bandwidth in High Frequency Radar (HFR), due to the working frequency band (3–30 MHz) is heavily congested. In order to minimize the mutual interference from other users and improve bandwidth utilization, the Discontinuous Spectra Synthetic Bandwidth (DSSB) signal is proposed. For collecting all target information from echoes, multiple snapshots are needed to synthesize the range spectrum of multiple targets in the long-range observation window. The Multi-Snapshots Compressed Sensing-Information Extraction (MCS-IE) method is proposed to accurately estimate range and amplitude from multiple snapshots. For MCS-IE method, a new measurement matrix according to random frequencies of compressed sensing is designed for samples in every snapshot, and then information extraction method is used for the same range window with multiple samples and estimations. A series of comparison experiments based on measured data from HFR Frequency Monitoring System (FMS) are tested to verify proposed methods.

CoMan: Managing Bandwidth Across Computing Frameworks in Multiplexed Datacenters

Inefficient bandwidth sharing in a datacenter network, between different application frameworks, e.g., MapReduce and Spark, can lead to inelastic and skewed usage of link bandwidth and increased completion times for the applications. Existing work, however, either solely focuses on managing computation and storage resources or controlling only sending/receiving rate at hosts. In this paper, we present CoMan, a solution that provides global in-network bandwidth management in multiplexed data centers, with two goals: improving bandwidth utilization and reducing application completion time. CoMan first designs a novel abstraction of virtual link groups (VLGs) to establish a shared bandwidth resource pool. Based on this pool, CoMan implements a three-level bandwidth allocation model, which enables elastic bandwidth sharing among computing frameworks as well as guarantees network performance for the applications. CoMan further improves the bandwidth utilization by devising a VLG dependency graph and solves an optimization problem to guide the path selection using a $\frac{3}{2}$ -approximation algorithm. We conduct comprehensive trace-driven simulations as well as small-scale testbed experiments to evaluate the performance of CoMan. Extensive simulation results show that CoMan improves the bandwidth utilization and speeds up the application completion time by up to $2.83\mathcal{\times}$ and $6.68\mathcal{\times}$ , respectively, compared to the ECMP $+$ ElasticSwitch solution. Our implementation also verifies that CoMan can realistically speed up the application completion times by $2.32\mathrm{\times}$ on average.

A Hybrid Routing Protocol for Wireless Distributed Networks

Trends in networking are shifting from distributed to logically centralized networks. Software defined networking (SDN) is the key technology behind this shift. This new paradigm not only proves the ease of network management in wired networks but also results into graceful evolution of networking protocols. Moreover, wireless distributed networks (WDNs) and software defined radios (SDRs) are also shifting towards the centralized approach. However, due to distributed control nature of WDNs, already prevailing routing algorithms cannot cope the design principle of centralized routing algorithms. Hence, a new routing algorithm that incorporates SDN in WDNs is required. In this paper, we propose a logically centralized approach for WDNs called centralized approach to mobile ad hoc network (CATMAN). It is a self-healing and hybrid routing protocol. It combines distributed and logically centralized network control along with the flavors of reactive, proactive, and opportunistic routing protocols. CATMAN is designed to automatically switch between logically centralized routing protocol and distributed routing protocol based on the types of available network nodes. The protocol significantly reduces control overhead and hence improves bandwidth utilization. While route computations, this protocol deliberately avoids the nodes with weaker batteries, optimizing the effective life of whole network. The simulation results showed that the CATMAN protocol outperform better approach to mobile ad hoc network (BATMAN) protocol by signaling overhead reduction up to 570%.

Practical Residual Interference After Cancellation for Constant Envelope Modulation With Data-Aided Synchronization

Interference cancellation (IC) is a well-known technique for improving bandwidth utilization in wireless networks. In this paper, we evaluate the practical residual interference of IC with constant envelope modulation in a flat fading environment for a low-power wide area wireless sensor network application, both analytically and experimentally. We propose a new model for the residual interference power, which is the power of the packet being canceled times a random variable. We derive the mean, variance, and distribution of the random variable considering the arbitrary overlapping scenario between two packets with one-time IC. Then, we show how the method can be applied recursively to model the residual interference power when multiple packets are canceled in ordered successive IC. In contrast to the conventional model, we find that this factor varies for different overlapping scenarios and is a function of the signal-to-interference-and-noise ratio of the preamble of the packet being canceled and of the overlapping degree. The theoretical statistics of the residual interference assume maximum likelihood estimation of synchronization offsets.