Dynamic Bandwidth Allocation Research Articles

A hybrid dynamic bandwidth allocation scheme operating with IACG and cooperative DBA for converged fronthaul networks

The time-division multiplexed passive optical network is seen as a candidate for converged fronthaul networks in 5G, which requires low latency and high capacity. In this paper, a hybrid dynamic bandwidth allocation (DBA) scheme for converged fronthaul that combines a status reporting DBA and a cooperative DBA is proposed. Different deployment scenarios and operating conditions in a 10-Gigabit-capable PON (XGS-PON) system are investigated using the OMNeT++ network simulator. The performance of the proposed hybrid DBA is evaluated in terms of average upstream delay and percentage of frame loss meeting a 140 µs queuing delay requirement for fronthaul traffic. Simulation results show a zero-frame loss for fronthaul traffic in all scenarios using the proposed hybrid DBA which is not achievable using only the status reporting DBA, confirming the advantages of the proposed hybrid DBA.

Dynamic power and bandwidth allocation for DVB‐based LEO satellite systems

A low Earth orbit (LEO) satellite constellation could be used to provide network coverage for the entire globe. This study considers multi-beam frequency reuse in LEO satellite systems. In such a system, the channel is time-varying due to the fast movement of the satellite. This study proposes an efficient power and bandwidth allocation method that employs two linear machine learning algorithms and take channel conditions and traffic demand (TD) as input. With the aid of a simple linear system, the proposed scheme allows for the optimum allocation of resources under dynamic channel and TD conditions. Additionally, efficient projection schemes are added to the proposed method so that the provided capacity is best approximated to TD when TD exceeds the maximum allowable system capacity. The simulation results show that the proposed method outperforms existing methods.

CONVERGENCE OF HETEROGENEOUS WIRELESS NETWORKS FOR FUTURE COMMUNICATIONS: ARCHITECTURE, QOS AND RESOURCE MANAGEMENT

Scientific and theoretical approaches to the implementation of a heterogeneous mobile communication network based on SDN/NFV and SDR technologies are described. The architecture of the future heterogeneous network is proposed, taking into account the evolution of emerging standards and key technologies. An algorithm for dynamic bandwidth allocation and reservation between several logical channels at a certain moment of time to provide QoS for information flows in future networks is created. A simulation model of network traffic service with parameters corresponding to real networks has been made. The study of femtocell SDR load, as the main convergent device at the level of heterogeneous network access by users of different generation mobile communication technologies has been conducted.

Clustering Based Dynamic Bandwidth Allocation in HC-RAN

A wireless network is composed of several independent nodes or gadgets that communicate mutually through a wireless link. The most destructive challenge encountered in a wireless network is bandwidth allocation because it defines the amount the network will cost and how effectively it will function. The most cutting-edge network architecture in the present wireless communication system, cluster-based heterogeneous cloud radio access networks (HC-RANs), is what powers cloud computing in heterogeneous networks. In this research, we proposed an HC-RANs that may optimize energy consumption for wireless data transfer in the multi-hop device to device scenario. The proposed scheme offers bandwidth allocation in wireless environments where there are concerns about significant user mobility over the course of a given time. The above design, we used clustering with joint beam formation for the down link of heterogeneous cloud radio access network (HC-RAN), developed design to improved amount of FBS. Result outcomes helped in calculating Critical bandwidth usage (CBU).

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

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.

Demonstration of real-time motion control on a 10G-EPON edge computing platform with SDN enabled broadband access

Edge computing is more useful for real-time remote motion control of Internet of Things devices than cloud computing because of its superior low latency performance. The access system is attracting attention as a place to perform edge computing. By using the network devices of the access system as an edge computing resource, it becomes possible to realize more precise control. This paper is the first, to our knowledge, to demonstrate real-time motion control by implementing edge computing on a 10-gigabit Ethernet passive optical network based on software-defined network enabled broadband access (SEBA), which is a virtualization platform for access systems. The proposed method analyzes the effectiveness of motion control and sets the optimal network settings automatically by using SEBA to take full advantage of edge computing benefits. The proposed method can provide an optimal network for motion control without making the user aware of the network settings. We construct a general motor-based experimental system and verify the effectiveness of the proposed system. The experiment shows that it properly reflects the optimum network settings to SEBA. Also, we verify that the proposed method changed the network settings to satisfy the reference settling time of 3 s. The optimal dynamic bandwidth allocation (DBA) cycle for motion control is determined after five trials, and the settling time was reduced by 53% compared with the case where the DBA cycle was set to 20 ms and no optimization was performed.

Developing machine learning based framework for the network traffic prediction

Network traffic analysis is a crucial step in developing efficient congestion control systems and identifying valid and malicious packets. Because network resources are apportioned based on predicted usage, these solutions reduce network congestion. For a variety of reasons, including dynamic bandwidth allocation, network security, and network planning, the ability to forecast network traffic is critical. Machine learning (ML) techniques to network traffic analysis have received a lot of interest. This article outlines an approach for analyzing network traffic. Three machine learning-based methodologies make up the methodology. The experimental investigation employed the NSL KDD data set. On the basis of accuracy and other criteria, KNN, Support vector machine, and nave bayes are compared.

Research on prediction weighted interpolated polling dynamic bandwidth allocation for optical fiber bus based on gigabit passive optical network

Optical fiber bus technology is an important research direction in communication systems of electronic devices in special vehicle platforms. According to the requirements for communication quality between devices in special vehicle platforms, an optical fiber bus based on gigabit passive optical network topology is proposed. A data cache-based predictive weighted interpolated polling dynamic bandwidth allocation method is presented and investigated for the optical fiber bus’s upstream bandwidth allocation. The network controller establishes a weighted buffer area for the communication requirements in the polling period according to the type and data volume of the network terminal (NT) data stream and dynamically allocates the bandwidth of each optical NT to better meet the communication requirements for different data within the special device platform. Verification is done by means of OPNET software simulation and the establishment of a NT simulation test system in the laboratory. This proves that the proposed dynamic bandwidth allocation algorithm can reduce the end-to-end delay of RS422 port data by more than 50% and meet the Ethernet and controller area network port data delay requirements.

A novel dynamic bandwidth allocation scheme towards improving the performance of XG-PON system

Time division multiplexed passive optical networks (TDM-PONs) such as EPON, XG-PON, XGS-PON, etc. have become widely accepted network architectures for meeting the bandwidth requirement of high-end consumer applications. The available bandwidth is still limited and needs to be utilized efficiently. There are scenarios when one ONU may completely dominate the network bandwidth leading to starvation of another ONUs. This may happen for an ONU in every allocation cycle. This enforces the OLT to provide such a fair allocation scheme that would provide a chance to different ONUs during polling and scheduling mechanism. This paper presents two novel DBA schemes namely the analytic hierarchy process proportional allocation scheme (AHP-PAS) and weighted sum model proportional allocation scheme (WSM-PAS) to determine the order of a transmission container (T-CONT) of an ONU for polling and scheduling. The proposed schemes are implemented in the network simulator (NS-3) and compared with the existing proportional allocation scheme (PAS) for inter-ONU and intra-ONU. The obtained results confirm that the proposed DBA schemes significantly improve the network performance in terms of delay fairness index, upstream mean delay, packet loss ratio, and packet jitter for T-CONT 2, 3, and 4.

Load adaptive merging algorithm for multi-tenant PON environments

Wavelength division multiplexing\ ime division multiplexing passive optical network (WDM/TDM-PON) is the attractive candidate for PON bandwidth sharing among multiple service providers, featuring massive bandwidth and longer reach. This infrastructure reduces the overall cost of the Fiber-to-the-premises (FTTP) services and offers relatively lower tariffs for the end customers. The dynamic bandwidth and wavelength allocation (DBWA) process in such PON networks ensure the fair sharing of the available bandwidth resources among the virtual network operators (vNOs). The earlier reported DBWA schemes with multiple vNOs have not efficiently utilized the unused and residual upstream bandwidth. This study presents a novel load adaptive merging algorithm (LAMA) for converting various individual virtual bandwidth maps(vBWmaps) into a single physical bandwidth map (phyBWMap). The LAMA scheme modifies the existing strict priority scheme called the Priority-Based Merging Algorithm (PBMA) scheme and improves the performance of the merging engine by allocating the phyBWMap in a load adaptive manner to the vNOs in the multi-tenant PON architecture. The proposed algorithm is compared with PBMA in terms of throughput efficiency, upstream delay, and capacity utilization under self-similar and Poison traffic scenarios. The results show that the proposed scheme offers higher bandwidth utilization resulting in increased throughput with lower upstream delays in the multi-tenant PON environment.

Proposed an efficient multilevel dynamic bandwidth allocation (M-DBA) scheme for FiWi networks

Proposed an efficient multilevel dynamic bandwidth allocation (M-DBA) scheme for FiWi networks

Bidirectional TWDM Optical access network with novel dynamic bandwidth allocation and scheduling algorithm

Bidirectional TWDM Optical access network with novel dynamic bandwidth allocation and scheduling algorithm

Dynamic Bandwidth Allocation Using Radio Over Fiber in Passive Optical Network

Dynamic Bandwidth Allocation Using Radio Over Fiber in Passive Optical Network

Implementation of Extra Efficient Bandwidth Utilization Dynamic Bandwidth Allocation Algorithm to Support Differentiated Service Classes in XGPON

The Dynamic Bandwidth Allocation (DBA) algorithm is required for efficient bandwidth utilization in XG-PON. The majority of existing DBA algorithms do not make use of the unused bandwidth of a queue with other service classes queue. In the update operation, the efficient bandwidth utilization (EBU) method employs a Borrow Refund (BR) method to utilize unused bandwidth between traffic class queues. This paper presents an extra efficient bandwidth utilization (EEBU) algorithm, which overcomes the limitations mentioned above with proper polling and scheduling mechanism. The theoretical and simulation results show that EEBU improvements for T-CONT 2 delay are 1% and 10%, and for T-CONT 3 delay are 8% and 22%, and for T-CONT 4 delay by 6% and 4.5% compared to the EBU and Giga PON access network (GIANT) respectively.

Bayesian auction game theory-based DBA for XG symmetrical PON.

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.

Enhanced Dynamic Bandwidth Allocation Algorithm for Intelligent Home Networks

Internet of Things (IoT) has been seen playing a tremendous change in the Information Technology (IT) environments, and thus its importance has also been realized and played a vital role within Intelligent Home Networks (IHNs). This is because IoT establishes a connection between things and the Internet by utilizing different sensing devices to implement the intelligence to deal with the identification and management of the connected things. IHNs use intelligent systems to perform their daily operations. Meanwhile, these networks ensure comfort, safety, healthcare, automation, energy conservation, and remote management to devices and users. Apart from that, these networks provide assistance in self-healing for faults, power outages, reconfigurations, and more. However, we have realized that more and advanced devices and services continue to be introduced and used in these networks. This has led to competitions of the limited available network resources, services, and bandwidth. In this paper, therefore, we present the design and implementation of a Novel Dynamic Bandwidth Allocation (NoDBA) algorithm to solve the performance bottleneck incurred with IHNs. The proposed algorithm deals with the management of bandwidth and its allocation. In the proposed algorithm, this study integrates two algorithms, namely; Offline Cooperative Algorithm (OCA) and Particle Swarm Optimization (PSO) to improve Quality of Service (QoS). PSO defines the priority limits for subnets and nodes in the network. Meanwhile, OCA facilitates dynamic bandwidth allocation in the network. The Network Simulator-2 (NS-2) was used to simulate and evaluate the NoDBA and it showed improved results compared to the traditional bandwidth allocation algorithms. The obtained results show an average throughput of 92%, average delay of 0.8 seconds, and saves energy consumption of 95% compared to Dynamic QoS-aware Bandwidth Allocation (DQBA) and Data-Driven Allocation (DDA). Keywords: IHNs, Dynamic Bandwidth Allocation, PSO, OCA, QoS

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

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.

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

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.

RNN based EPON dynamic bandwidth allocation algorithm for complex network

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.

Dynamic Bandwidth Allocation and Precoding Design for Highly-Loaded Multiuser MISO in Beyond 5G Networks

Dynamic Bandwidth Allocation and Precoding Design for Highly-Loaded Multiuser MISO in Beyond 5G Networks