Showing papers on "Dynamic bandwidth allocation published in 2022"

Elastic and Reliable Bandwidth Reservation Based on Distributed Traffic Monitoring and Control

Abstract: Bandwidth reservation can effectively improve the service quality for data transfers because of dedicated network resources. However, it is difficult to achieve a desired tradeoff between resource utilization and reliable bandwidth guarantees for data transfers with time-varying traffic. In this article, we study a novel bandwidth reservation solution based on distributed traffic monitoring and control for applications that require reliable bandwidth guarantees. In the proposed solution, designated bandwidth is allocated for an application in advance according to its maximum traffic peak, and idle reserved bandwidth resources are dynamically shared according to regular traffic. Dynamic resource sharing evidently improves resource utilization and effectively eliminates the potential congestion caused by sudden traffic bursts. To ensure that the congestion that occurs occasionally can dissipate rapidly, our solution monitors and manages traffic by a distributed monitoring and control strategy. Hence, we study a delay-constrained and proxy-assisted traffic monitoring structure construction problem and propose an algorithm to solve it. The proposed algorithm can also be used to build a delay-constrained traffic control structure. In addition to the above algorithm, we propose a dynamic traffic control algorithm that can achieve a desirable tradeoff between resource utilization and congestion avoidance capability.

Dynamic Beam Pattern and Bandwidth Allocation Based on Multi-Agent Deep Reinforcement Learning for Beam Hopping Satellite Systems

Abstract: Due to the non-uniform geographic distribution and time-varying characteristics of the ground traffic request, how to make full use of the limited beam resources to serve users flexibly and efficiently is a brand-new challenge for beam hopping satellite systems. The conventional greedy-based beam hopping methods do not consider the long-term reward, which is difficult to deal with the time-varying traffic demand. Meanwhile, the heuristic algorithms such as genetic algorithm have a slow convergence time, which can not achieve real-time scheduling. Furthermore, existing methods based on deep reinforcement learning (DRL) only make decisions on beam patterns, lack of the freedom of bandwidth. This paper proposes a dynamic beam pattern and bandwidth allocation scheme based on DRL, which flexibly uses three degrees of freedom of time, space and frequency. Considering that the joint allocation of bandwidth and beam pattern will lead to an explosion of action space, a cooperative multi-agents deep reinforcement learning (MADRL) framework is presented in this paper, where each agent is only responsible for the illumination allocation or bandwidth allocation of one beam. The agents can learn to collaborate by sharing the same reward to achieve the common goal, which refers to maximize the throughput and minimize the delay fairness between cells. Simulation results demonstrate that the offline trained MADRL model can achieve real-time beam pattern and bandwidth allocation to match the non-uniform and time-varying traffic request. Furthermore, when the traffic demand increases, our model has a good generalization ability.

Realtime mobile bandwidth and handoff predictions in 4G/5G networks

Abstract: Mobile apps are increasingly relying on high-throughput and low-latency content delivery, while the available bandwidth on wireless access links is inherently time-varying. The handoffs between base stations and access modes due to user mobility present additional challenges to deliver a high level of user Quality-of-Experience (QoE). The ability to predict the available bandwidth and the upcoming handoffs will give applications valuable leeway to make proactive adjustments to avoid significant QoE degradation. In this paper, we explore the possibility and accuracy of realtime mobile bandwidth and handoff predictions in 4G/LTE and 5G networks. Towards this goal, we collect long consecutive traces with rich bandwidth, channel, and context information from public transportation systems. We develop Recurrent Neural Network models to mine the temporal patterns of bandwidth evolution in fixed-route mobility scenarios. Our models consistently outperform the conventional univariate and multivariate bandwidth prediction models. For the next second bandwidth prediction, in terms of Mean Absolute Error (MAE), our model is on average 15.28% better than the other methods in 4G traces and 15.37% better than the other methods in 5G traces. For 4G & 5G co-existing networks, we propose a new problem of handoff prediction between 4G and 5G, which is important to achieve good application performance in realistic 5G scenarios. We develop classification and regression based prediction models, which achieve more than 80% accuracy in predicting handoffs between 4G and 5G in a recent 5G dataset.

Bandwidth Allocation-Based Distributed Event-Triggered LFC for Smart Grids Under Hybrid Attacks

Abstract: In this study, a bandwidth allocation-based distributed event-triggering load frequency control (LFC) has been developed for smart grids to deal with hybrid cyber-attacks, for example, denial-of-service (DoS) attacks and false data injection (FDI) attacks. Firstly, to prevent hybrid cyber-attacks from causing open-loop unstable operation of the LFC systems, we propose a distributed event-triggering communication (ETC) strategy. To attain the maximum usage of bandwidth, a dynamic bandwidth allocation mechanism is integrated with the ETC approach on the basis of resource availability and error between the current state and equilibrium state. This bandwidth reservation and allocation approach aim at detecting attacks and assigning bandwidth to the different channels of distribution networks. Then, by virtue of the Lyapunov approach, the exponential stability criteria are established. Further, the exclusion of Zeno behavior of the designed systems is proved during the control process. Finally, comprehensive case studies show that the proposed method can improve the utilization rate of the network resource.

Achieving the Performance Bounds for Sensing and Communications in Perceptive Networks: Optimal Bandwidth Allocation

Abstract: This letter investigates the performance bounds of sensing and communications (S&C) in perceptive networks, where multiple user equipments (UEs) are deployed with both S&C capabilities whose performances are both closely related to the allocated bandwidth. To this end, we develop a novel bandwidth allocation strategy which optimizes the weighted average range resolution for sensing, while guaranteeing the sum-rate among UEs for wireless communications. We first formulate the bandwidth allocation problem into a convex optimization programming, and then develop a highly efficient algorithm to obtain the optimal solution. Through a deeper analysis of the problem structure, we build an initial understanding and provide insights into the performance tradeoff between S&C, which can be achieved by three specifically tailored bandwidth allocation schemes. Numerical results are given to verify the performance of the proposed method, showing that our bandwidth allocation scheme achieves the pareto boundary of S&C performance, with significantly reduced computational complexity.

Bayesian auction game theory-based DBA for XG symmetrical PON

Abstract: The next-generation passive optical networks (NG-PONs) (i.e., 50G-PON and Time-division-multiplexing/Wavelength-division-multiplexing, TWDM-PON) offer very high bandwidth with improved quality of service. In these PONs, the role of efficient Dynamic bandwidth allocation (DBA) becomes even more important in reducing the upstream delays, bandwidth waste and reducing the upstream delays and delay variance. These qualities of service metrics lead to improved Quality of Experience (QoE) for the end-users in addition to increased revenue for the service providers. This study introduces the game theory concept in the bandwidth distribution process in PON. Specifically, the Bayesian auction game theory (BAGT) process is used in the DBA process to address the unfair and inefficient distribution of upstream bandwidth to the optical network units (ONUs) in XG symmetrical PON(XGs-PON). The proposed BAGT scheme allocates the excess bandwidth to the entire ONUs in proportion to their demands reported via the bidding process. To validate the performance of the BAGT scheme, we also compare it with other existing DBA schemes namely; proportional allocation schemes (PAS), improved bandwidth utilization (IBU), and optimized round-robin (ORR) methods. The simulation results show that the proposed scheme results in higher system throughput and lower upstream delays than the other schemes. BAGT DBA also improves the bandwidth utilization by up to 38% to 50% compared to IBU, ORR, and PAS schemes and exhibits the minimum frame loss ratio.

Distributed Pricing and Bandwidth Allocation in Crowdsourced Wireless Community Networks

Abstract: With the rapid growth of global mobile data traffic, Wi-Fi plays an increasingly important role in expanding network capacity. To overcome the geographical coverage limit of Wi-Fi APs, especially for mobile users, the crowdsourced wireless community network has emerged as a cost-effcient way for providing Internet access services. For instance, it is plausible to share their private residential Wi-Fi APs with each other by designing some tailored incentive/pricing mechanisms. Thus motivated, we propose a distributed pricing and bandwidth allocation scheme to maximize the profit of Wi-Fi providers and provide better Internet services to mobile users. Firstly, we study the stationary networks with incomplete information of users and propose distributed pricing and bandwidth allocation algorithms for single-AP regions and AP group regions, respectively. Then, we generalize the study to dynamic networks and explore distributed pricing based on the statistics of users mobility. Further, we design an online bandwidth allocation algorithm according to the real-time user information. Simulation results demonstrate that the proposed distributed pricing and bandwidth allocation scheme, comparing with the operators pricing scheme, has a better performance on both Wi-Fi APs profit and user experience.

Generalized Multi-Access Dynamic Bandwidth Allocation Scheme for Future Generation PONs: A Solution for Beyond 5G Delay/Jitter Sensitive Systems

Abstract: In this paper, we present a novel dynamic bandwidth allocation (DBA) scheme for future generation passive optical networks (PON) in order to meet the beyond 5G (B5G) and sixth generation (6G) stringent requirements. Our proposed algorithm is a generalized multi-access DBA (GMA-DBA) that exploits both orthogonal and non-orthogonal multi-access (MA) resources, resulting in a radical enhancement in the network performance. The proposed GMA-DBA algorithm is modeled as an optimization problem for which a closed form solution is derived. Results show that the GMA-DBA is capable of accommodating a network throughput higher than 1 Tbps while securing a latency and jitter below 100 µs and 10 µs, respectively. It can also maintain reliability, simplicity and energy efficiency. Therefore, using a non-orthogonal MA layer seems to be inevitable to achieve the stringent performance needed for the B5G and 6G next generation systems.

Dynamic Subcarrier Assignment in OFDMA-PONs Based on Deep Reinforcement Learning

Abstract: Orthogonal Frequency Division Multiplexing Access Passive Optical Networks (OFDMA-PONs), a solution for the next-generation optical access network, allows multiple optical network units (ONUs) to dynamically share subcarriers (SCs) to support efficient bandwidth allocation. In uplink transmission, multiple ONUs can share orthogonal low bit rate SCs to transmit data at different time slots (TSs) during the transmission cycle. In this paper, the dynamic subcarrier allocation (DSA) scheme based on deep reinforcement learning (DRL) is proposed for various ONU bandwidth requests. The novel scheme jointly allocates time slots, subcarriers, and modulation formats in a dynamic and flexible manner. The ONU can save transmit power by using a lower order modulation format while meeting the delay requirement. The simulation part demonstrates how the proposed DRL-based DSA scheme can be adapted to various situations, including 1) variation in the size of ONU bandwidth requests, and 2) variation in the weight of different indicators. The extensive simulation results show that, for the first time, the proposed DRL-based DSA algorithm achieves optimal traffic latency with substantial power saving, compared with the traditional two-dimensional DSA algorithms.

Protection Schemes in HPON Networks Based on the PWFBA Algorithm

Abstract: In this paper, possibilities for network traffic protection in future hybrid passive optical networks are presented, and reasons for realizing and utilizing advanced network traffic protection schemes for various network traffic classes in these networks are analyzed. Next, principles of the Prediction-based Fair Wavelength and Bandwidth Allocation (PFWBA) algorithm are introduced in detail, focusing on the Prediction-based Fair Excessive Bandwidth Reallocation (PFEBR) algorithm with the Early Dynamic Bandwidth Allocation (E-DBA) mechanism and subsequent Dynamic Wavelength Allocation (DWA) scheme. For analyzing various wavelength allocation possibilities in Hybrid Passive Optical Networks (HPON) networks, a simulation program with the enhancement of the PFWBA algorithm is realized. Finally, a comparison of different methods of the wavelength allocation in conjunction with specific network traffic classes is executed for future HPON networks with considered protection schemes. Subsequently, three methods are presented from the viewpoint of HPON network traffic protection possibilities, including a new approach for the wavelength allocation based on network traffic protection assumptions.

Bandwidth Allocation of Stream-Reservation Traffic in TSN

Abstract: Time-Sensitive Networking (TSN) evolves from Ethernet AVB in which the Credit-Based Shaping (CBS) is employed to guarantee the deterministic transmission of traffic. In CBS, the real-time performance of traffic associated with the credits can practicably settle the uncertainty of queueing and forwarding for stream-reservation traffic. Hence, the optimization of bandwidth allocation under the CBS becomes a key point to ensure guaranteed performance in the network. In this paper, a bandwidth allocation method is proposed for stream-reservation traffic while the real-time requirements are satisfied. We first illustrate the significance of appropriate bandwidth allocation for traffic under the CBS and construct a general schema for its bandwidth allocation. Also, the influences of the protected window for Control Data Traffic (CDT) on stream-reservation traffic are considered in our method. Further, mathematical models are constructed to analyze the delay bounds and backlogs of traffic to form the feedback for the optimal bandwidth allocation process. Finally, two node-level cases with different bandwidth utilization and a synthetic industrial networking scenario are carried out to demonstrate our method. The results confirm that the excessive reserved bandwidth does not necessarily decrease the delay bound, especially under the high traffic loads scenario. A more desirable bandwidth allocation strategy under the CBS mechanism is that the reserved bandwidth should be just enough according to the traffic loads to ensure the deterministic transmission of traffic.

Premium quality or guaranteed fluidity? Client-transparent DASH-aware bandwidth allocation at the radio access network

Abstract: In this paper we propose a novel client-transparent Dynamic Adaptive Streaming over HTTP (DASH)-aware bandwidth allocation strategy. The approach, while being application layer transparent, guarantees fluidity to all users but it provides priority-based services to premium users, identified by their Willingness-To-Pay (WTP) profiles. Since different service qualities can be accommodated using WTP, the approach can be extended to XR services, immersive videos, live uplink streaming. To achieve this goal, the allocation problem is firstly formulated as a classical Game Theory problem whose closed form solution is clearly understood in the literature. In a nutshell, the WTP-based, Game Theoretically Optimal Bandwidth Allocation (WTP-GTOBA), firstly satisfies the minimum bandwidth needs of each user and then fairly distributes the residual bandwidth. WTP-GTOBA can be approximately implemented by a greedy, application layer transparent algorithm to be implemented at a DASH-aware network element managing different neighbouring radio access stations. Thereby, the proposed method is suitable for integration of WTP and resource management among multiple service providers and heterogeneous client groups. Numerical simulations carried out under a realistic scenario show that the proposed approach outperforms state-of-the-art application-layer transparent competitors, providing premium quality and/or guaranteed fluidity to different users based on their WTP.

Dynamic Bandwidth Allocation for C-Band Shared FBG Sensing and Telecommunications

Abstract: The telecommunications data transfer in single-mode (SM) optical fiber (OF) of a passive optical network (PON) is managed by dynamic bandwidth allocation (DBA). In most Internet of Things (IoT) sensor network applications, both raw sensing signals and telecommunication data are transmitted in SM OFs, too. At the present time, this is not done in a shared SM OF. This article presents a novel concept to share fiber Bragg grating (FBG) sensing and telecommunication services (TS) in the optical C-band of the shared transmission. This concept is based on statistical detection and monitoring of FBGs sensing signals. The key steps of the proposed concept are FBG power spectral peaks statistical detection, monitoring of the FBGs dynamics, and periodical estimation of telecommunication channels (TChs) occupancy and availability. The proposed concept was demonstrated and validated using the sensor network with a deployed group of FBG-based sensors, by implementing various static or dynamic approaches. By doing so, we achieved TChs bandwidth availability approaching 80%, compared to previously wasted bandwidth with availability at most 15.6%. The experimental results showed that a DBA system with implemented dynamic TChs occupancy is a reliable way to share fiber bandwidth between both FBG sensing and TChs.

A Flexible Ethernet Calendar Allocation Based on Client Traffic

Abstract: Aiming at the problem of low link bandwidth utilization in the current FlexE client slot allocation mechanism, a FlexE calendar bandwidth allocation mechanism that is compatible with the client data transmission rate is proposed, and the LSTM algorithm is used to predict network traffic data, and according to the client priority and traffic prediction results, the client is allocated with slots. Experiments show that, compared with the traditional FlexE slot allocation mechanism, the method proposed in this paper can make the bandwidth resource utilization rate reach 82.8%.

(Network value)‐based adaptive dynamic bandwidth allocation algorithm for 5G network slicing

Abstract: In this article, a (network value)‐based inter‐slice and intra‐slice adaptive dynamic bandwidth allocation algorithm is proposed for the coexistence scenario of URLLC slices, eMBB slices, and mMTC slices in 5G fronthaul networks. The network value model applicable to network slicing is constructed to provide a means for the value evaluation of virtual networks. According to the bandwidth requirements of the slices, the adaptive inter‐slice bandwidth allocation is realized to ensure that the fronthaul network can obtain the maximum economic value under different load states. For the service characteristics of three slices, three intra‐slice bandwidth allocation algorithms are proposed, respectively, to realize adaptive ONU bandwidth allocation. It not only meets the differentiated service demands of different slices, but also enables each slice to obtain the maximum QoS value. By simulation and analysis, the effectiveness of the proposed algorithm is demonstrated.

The process mining method approach to analyze users’ behavior of internet in the Local Area Network of Sriwijaya University

Abstract: The Sriwijaya University internet network management unit does not yet have a standard formulation for implementing Bandwidth Management & Bandwidth Allocation. To provide the best service, they apply the Best-Effort Service concept. As a result, it requires a relatively large network capacity and bandwidth provision so that it has an impact on costs. Therefore, it is necessary to know how users use internet bandwidth as the basic principle of Bandwidth Management & Bandwidth Allocation. This study has completed how to determine the behavior of internet users on the campus LAN as a reason to evaluate internet bandwidth usage. With the Process Mining method, process mapping has been carried out for all access to internet usage from all faculties. As a result, the factors that characterize and need to be considered in bandwidth management are obtained. In order of significance are Total Access Length, Average Variance, Number of User Case IDs, Number of Non-Academic Ports, Number of Academic Ports, Number of Access Frequency, Number of Events, and Number of Ports of Service.

Self-Adaptive Resource-Allocation Scheme Combining Traffic Prediction With User Satisfaction in Multi-Wavelength VPON

Abstract: In this paper, a self-adaptive resource-allocation scheme combining traffic prediction with user satisfaction is firstly established in multi-wavelength VPON. Among VPONs, by proposing a (wavelength utility)-based dynamic wavelength allocation algorithm, the optimal allocation of wavelengths can be achieved. In a VPON: under condition that the total requested bandwidth is larger than the total bandwidth, by introducing a bandwidth constraint factor ϵ , the maximum amount of bandwidth granted for high-priority service can be limited, and the “starvation” problem of low-priority service can be prevented. By solving the user satisfaction model, not only the optimal allocation of low-priority service can be obtained, but also the comprehensive user satisfaction is maximized. Under condition that the total requested bandwidth is smaller than the total bandwidth, by combining an ANN prediction model with a user satisfaction model, a bandwidth allocation model based on traffic prediction and user satisfaction is created. By this model, not only the resource utilization is improved but also the transmission delay is reduced. At the same time, user satisfaction is maximized. By adjudicating on the set judgment condition, the self-adaptive function of control system for the above two conditions is implemented. By simulation, the effectiveness of the proposed scheme is demonstrated.

RNN based EPON dynamic bandwidth allocation algorithm for complex network

Abstract: Abstract In the development of ethernet passive optical networks (EPONs), quality of service (QoS) support and fairness per optical network unit (ONU) are crucial issues. However, making an elaborate analysis of the existing prediction-based bandwidth allocation algorithm, light load penalty, low prediction precision are pointed out. We present an improved dynamic bandwidth pre-allocation algorithm (R-DBA), which employs recurrent neural network (RNN) to predict the high-priority service traffic in EPON. And we introduce mixed integer linear programming (MILP) for optimally building DBA algorithm. This algorithm achieves the prediction of the high-priority service traffic by RNN during the waiting time and supports bandwidth pre-allocation, thus ensuring the fairness of the bandwidth allocation.

Enhancing Energy Efficiency of the Doze Mode Mechanism in Ethernet Passive Optical Networks Using Support Vector Regression

Abstract: An Ethernet passive optical network (EPON) is an optical access network that allows a higher data rate with low power consumption. To improve energy savings for an EPON, the sleep and doze modes for the optical network units (ONUs) play a pivotal role. Many prediction schemes have been proposed to control these modes. To increase the prediction accuracy, this study proposes an energy-efficient approach that uses a support vector regression (SVR) model. A dynamic bandwidth allocation (DBA) scheme called SVR-DBA is designed to allocate bandwidth to ONUs more efficiently and fairly. To determine the effectiveness of the proposed scheme, simulations are performed. The simulation results show that the proposed scheme decreases energy consumption for ONUs by up to 47% and fulfills the quality-of-service (QoS) requirements in terms of delay, jitter, and packet loss.

Bandwidth-Aware Event-Triggered Load Frequency Control for Power Systems Under Time-Varying Delays

Abstract: Networked Load frequency control (LFC) inevitably subjects to constrained bandwidth and time delays. However, the network traffic essentially varies from time to time and then the bandwidth status may be only busy during some specific peak periods but idle during others. This paper proposes a bandwidth-aware event-triggered load frequency control (ETLFC) scheme for multi-area power systems under time-varying delays by incorporating bandwidth-aware adaptive regulation scheme into decentralized ETLFC scheme. Different from existing time-delay ETLFC model, a model of aperiodic sampled-data system with time delay is constructed for the ETLFC scheme to obtain less conservative stability and co-design conditions based on looped Lyapunov functional. The regulation scheme is designed to adaptively adjust the threshold parameter of the ETLFC scheme based on variable bandwidth status and system output change in order to lessen communication burden while ensuring desired control performance. For fixed output change, a better bandwidth status generates a smaller threshold parameter to raise the triggering frequency in order to utilize available communication resources to improve control performance rather than unilaterally reduce data transmissions in the existing research. Case studies are undertaken by an IEEE 39-bus test system to show the effectiveness and advantages of the proposed scheme.

Bandwidth Prediction for 5G Cellular Networks

Abstract: Effective bandwidth prediction in the fifth-generation (5G) cellular networks is essential for bandwidth-consuming applications, such as virtual reality and holographic video streaming. However, accurate bandwidth prediction in 5G networks remains a challenging task due to the short-distance coverage and frequent handover properties of 5G base stations. In this paper, we propose HYPER, a HYbrid bandwidth PrEdiction appRoach using commercial smartphones. Hyper uses an AutoRegressive Moving Average (ARMA) time series predictive model for intra-cell bandwidth prediction and a Random Forest (RF) regression model for cross-cell bandwidth prediction. Our ARMA model takes prior bandwidth usage as its input, while the RF model further uses related network and physical features to predict future bandwidth. We conduct a measurement study in commercial 5G networks to analyze the relationship between these features and bandwidth. Moreover, we also propose a handover window adaptation algorithm to automatically adjust the handover window size and determine which model to use during handover. We use commercial 5G smartphones for data collection and conduct extensive experiments in diverse urban environments. Experimental results based on one TB of cellular data show that HYPER can reduce the bandwidth prediction error by more than 13% compared to state-of-the-art bandwidth prediction approaches.

Trusted 6G-Envisioned Dynamic Spectrum Allocation: A Reference Model, Layered Architecture, and Use-Case

Abstract: Abstract Spectrum allocation among multiple telecom providers is challenged with a fair spectrum allocation process and collusion among multiple telecom parties involved in spectrum bids. As spectrum licensing have shifted toward decentralization, blockchain-based spectrum allocation can address the limitations through a fair and trusted bidding process, and spectrum allocation which is transparent to all bidders. Moreover, the spectrum allocation process has shifted to dynamic spectrum allocations, and thus in the coming future, owing to the inherent advantages of sixth-generation (6G) networks, with high network reliability, user bandwidth, high-precision, ultra-high reliability, and extreme flexibility, all presented as networked-in-a-box service, dynamic spectrum allocation in 6G-envisioned networks is a reality in near future. In light of these facts, we present in this paper, a comprehensive examination of the integration of a blockchain-based scheme for dynamic spectrum access in 6G-envisioned communications. We present the layered reference architecture and highlight a case study of future blockchain-based spectrum access for 6G-serviced network access. The paper serves as starting foundation toward the build of effective blockchain-based spectrum allocation schemes with effective networked serviced applications.Keywords6GBlockchainSpectrum sharingDecentralizationTelecommunication industry

Traffic-Aware Dynamic Functional Split for 5G Cloud Radio Access Networks

Abstract: The recent adaption of virtualization technologies in the next generation mobile network enables 5G base station to be segregated into a Radio Unit (RU), a Distributed Unit (DU), and a Central Unit (CU) to support Cloud based Radio Access Networks (C-RAN). RU and DU are connected through a fronthaul link. In contrast, CU and DU are connected through a midhaul link. Although virtualization of CU gives benefits of centralization to the operators, there are other issues to be solved such as optimization of midhaul bandwidth and computing resources at edge cloud and central cloud where the DUs and CUs are deployed, respectively. In this paper, we propose a dynamic functional split selection for the DUs in 5G C-RAN by adopting to traffic heterogeneity where the midhaul bandwidth is limited. We propose an optimization problem that maximizes the centralization of the C-RAN system by operating more number of DUs on split Option-7 by changing the channel bandwidth of the DUs. The dynamic selection of split options among each CU-DU pair gives 90% centralization over the static functional split for a given midhaul bandwidth.

High Bandwidth Utilization DWBA Algorithm for Upstream Channel in NG-EPON

Abstract: In this paper, an (ONU-load and RTTs)-based (OLR) dynamic wavelength and bandwidth allocation (DWBA) algorithm for upstream channel in next-generational Ethernet passive optical network (NG-EPON) is proposed. By proposing adaptive threshold grouping algorithm, the waste of bandwidth resources caused by massive guard timeslots and mismatch between assigned transmission window and frame size is reduced. By adjusting the Optical Network Unit (ONU) scheduling order, the idle time caused by Round-Trip Times (RTTs) is reduced. By proposing joint ONU grouping and RTT scheduling mechanism, load balance among wavelengths is achieved. By proposing a fair allocation scheme, the fairness of bandwidth granting for each ONU is ensured. Finally, by the simulation, the effectiveness of proposed algorithm is demonstrated. The simulation indicates that the rate of bandwidth utilization, the average package delay, the scheduling cycle and the network throughput in the system based on proposed algorithm have better performance.