Dynamic Bandwidth Allocation Research Articles

Dynamic bandwidth allocation algorithms for improved throughput and latency performance in CDMA-based next-generation ethernet passive optical networks

In this paper, we propose new scheduling algorithms to improve the performance of the code division multiple access (CDMA) enabled next generation ethernet passive optical networks (NG-EPON). The original dynamic bandwidth allocation (DBA) scheme based on a round robin scheduling algorithm was originally proposed for the first generation CDMA based EPON where the network throughput and delay requirements per optical network unit (ONU) are relatively moderate. On the other hand, in the NG-EPON standard, the network capacity is increased up to 100 Gb/s and stringent requirements are applied to the packet delay. For this reason, in this work, we propose new scheduling algorithms for NG-EPON to assign a grant size on each upstream CDMA code in order to guarantee the newly required network throughput and delay performance. The first DBA algorithm is the first in first out (FIFO) algorithm in which the ONU requests are ordered in terms of their request arrival time. The second scheme is the reservation pattern (RP) algorithm in which each ONU starts transmitting its queue content in its reserved pattern of subcycles following a pre-defined pattern. The performances of the newly proposed algorithms are evaluated and compared. Results show that both newly proposed scheduling schemes can significantly improve the network performance in terms of the packet delay, jitter, and throughput. In addition, the results are compared to many dynamic wavelength and bandwidth allocation (DWBA) algorithms. The results show that the performances are comparable and that CDMA can be a good alternative for WDM for multi-channels based NG-EPON.

Impact of security breach on the upstream delay performance of next generation gigabit passive optical networks

The next generation passive optical networks (NG-GPON) such as long reach GPON is the future-proof solution to answer the continuous demands for access user bandwidth and network expansion. However, security which is yet to be addressed in NG-GPON needs urgent attention as it will become more critical due to much longer distance, denser user population and more network elements. In addition, the longer propagation delay in NG-GPON can also lead to a more complex bandwidth allocation mechanism that is expected to operate in a dynamic manner. Among the highlights of recommendations for future implementation are improvements in the security aspect and the use of dynamic bandwidth allocation (DBA) algorithm that suit the characteristics of long reach GPON. Current PON is exposed to degradation attack, a security breach that can harm how bandwidth fairness mechanism among ONUs work. Thus, this project proposes a secured DBA mechanism for NG-PON that could overcome this particular threat. In specific, a detection phase will be included in the DBA mechanism to sense and subsequently mitigate abnormal behaviours among ONUs that are harmful to the goal of DBA i.e. to ensure QoS among ONUs and traffics. At the same time, careful attention is given on the delay parameter as it is a critical parameter that can affect DBA performance in long reach GPON. In this paper, preliminary analysis is shown that reveal how possibility of threats increase with increasing of distance and network elements.

Efficiency Tests of DBA Algorithms in XG-PON

Sophisticated dynamic bandwidth allocation (DBA) algorithms can dramatically improve or worsen throughput and delay in whole networks. It is very important to choose the right DBA algorithm. Our work tests static assignment and three DBA algorithms, namely GigaPON Access Network DBA, Hybrid Reporting Allocation, and modified Max–Min Fair. All tests were made on our simulator of ten-gigabit passive optical network DBA specially developed for testing DBA algorithms. The tests verify delay of each optical network unit and amount of waste with bandwidth. This paper describes how the used DBA algorithms work and the processes involved in DBA algorithms.

Efficient T-CONT-Agnostic Bandwidth and Wavelength Allocation for NG-PON2

Dynamic bandwidth and wavelength allocation are used to demonstrate high quality of service (QoS) in time wavelength-division multiplexed–passive optical networks (TWDM-PONs). Both bandwidth and wavelength assignment are performed on the basis of transmission containers (T-CONTs) and therefore by means of upstream service priority traffic flows. Our medium access control (MAC) protocol therefore ensures consistency in processing alike classes of service across all optical network units (ONUs) in agreement with their QoS figures. For evaluation of the MAC protocol performance, a simulator has been implemented in OPNET featuring a 40 km, 40 Gbps TWDM-PON with four stacked wavelengths at 10 Gbps each and 256 ONUs. Simulation results have confirmed the efficiency of allocating bandwidth to each wavelength and the significant increase of network traffic flow due to adaptive polling from 9.04 to 9.74 Gbps. The benefit of T-CONT-centric allocation has also been measured with respect to packet delay and queue occupancy, achieving low packet delay across all T-CONTs. Therefore, improved NG-PON2 performance and greater efficiency are obtained in this first demonstration of T-CONTs allocated to both wavelength and time.

Machine Learning-Based Bandwidth Prediction for Low-Latency H2M Applications

Human-to-machine (H2M) communications in emerging tactile-haptic applications are characterized by stringent low-latency transmission. To achieve low-latency transmissions over existing optical and wireless access networks, this paper proposes a machine learning-based predictive dynamic bandwidth allocation (DBA) algorithm, termed MLP-DBA, to address the uplink bandwidth contention and latency bottleneck of such networks. The proposed algorithm utilizes an artificial neural network (ANN) at the central office (CO) to predict H2M packet bursts arriving at each optical network unit wireless access point (ONU-AP), thereby enabling the uplink bandwidth demand of each ONU-AP to be estimated. As such, arriving packet bursts at the ONU-APs can be allocated bandwidth for tranmission by the CO without having to wait to transmit in the following transmission cycles. Extensive simulations show that the ANN-based prediction of H2M packet bursts achieves >90% accuracy, significantly improving bandwidth demand estimation over existing prediction algorithms. MLP-DBA also makes adaptive bandwidth allocation decisions by classifying each ONU-AP according to its estimated bandwidth, with results showing reduced uplink latency and packet drop ratio as compared to conventional predictive DBA algorithms.

Towards Immersive Tactile Internet Experiences: Low-Latency FiWi Enhanced Mobile Networks With Edge Intelligence [Invited

Historically, research efforts in optical networks have focused on the goal of continuously increasing capacity rather than on lowering end-to-end latency. This slowly started to change in the access environment with post-Next-Generation Passive Optical Network 2 research. The emphasis on latency grew in importance with the introduction of 5G ultra-reliable and low-latency communication requirements. In this paper, we focus on the emerging Tactile Internet as one of the most interesting 5G low-latency applications enabling novel immersive experiences. After describing the Tactile Internet's human-in-the-loop-centric design principles and haptic communications models, we elaborate on the development of decentralized cooperative dynamic bandwidth allocation algorithms for end-to-end resource coordination in fiber-wireless (FiWi) access networks. We then use machine learning in the context of FiWi enhanced heterogeneous networks to decouple haptic feedback from the impact of extensive propagation delays. This enables humans to perceive remote task environments in time at a 1-ms granularity.

Dynamic bandwidth allocation algorithm with demand forecasting mechanism for bandwidth allocations in 10-gigabit-capable passive optical network

10G-passive optical network (XG-PON) provides an emerging potential technology to carry multiple services for the first - mile access network. However, it offers 0.3 ms propagation delay between the optical network Unit (ONU) and optical line terminal (OLT) resulting in inevitable increased queuing delay for the bandwidth grants to the ONUs. We present a reasonable and effective uplink dynamic bandwidth allocation method - demand forecasting DBA (DF-DBA) that predicts ONU’s future demands by statistical modelling of the demand patterns and tends to fulfil the predicted demands just in time, which results in reduced delay. Results show that use of simple normal distribution in the DBA engine offers more appropriate bandwidth allocation with 14% decreased packet drop ratio (PDR) values than standard GigaPON access network (GIANT) DBA following request-grant cycle procedure. Proposed DBA when tested for all the T-CONTs, reduced 50% delay and offered 45% throughput improvement at higher traffic load. The unassigned bandwidth margin (UBM) is nearly ideal along with better QoS parameters results which validates that DF-DBA can practically improve the OLT performance. Further, this predictive DBA opens up a new horizon of research for researcher to use it for longer distances in PON (LR-PON) network with different statistical distributions for getting the possible best results in the future.

Next Generation Fiber-Wireless Fronthaul for 5G mmWave Networks

mmWave radio, although instrumental for achieving the required 5G capacity KPIs, necessitates the need for a very large number of access points, which places an immense strain on the current network infrastructure. In this article, we try to identify the major challenges that inhibit the design of the Next Generation Fronthaul Interface in two upcoming distinctively highly dense environments: in Urban 5G deployments in metropolitan areas, and in ultra-dense Hotspot scenarios. Second, we propose a novel centralized and converged analog Fiber-Wireless Fronthaul architecture, specifically designed to facilitate mmWave access in the above scenarios. The proposed architecture leverages optical transceivers, optical add/drop multiplexers and optical beamforming integrated photonics towards a Digital Signal Processing analog fronthaul. The functional administration of the fronthaul infrastructure is achieved by means of a packetized Medium Transparent Dynamic Bandwidth Allocation protocol. Preliminary results show that the protocol can facilitate Gb/s-enabled data transport while abiding to the 5G low-latency KPIs in various network traffic conditions.

Dynamic hybrid slot-size bandwidth allocation algorithm for reducing packet delay and jitter variation of real time traffic in EPON

In the modern data networks, the demand is increasing for interruption free, high speed, and best quality of services to perform successful communications. This paper emphasizes on the high priority (HP) traffic like video conferencing, video streaming, telemedicine, teleconferencing, and interactive gaming for the real time communications. To achieve the best quality data communication for the HP traffic, in this paper, we propose a new dynamic bandwidth allocation (DBA) algorithm called dynamic hybrid slot-size bandwidth allocation (DHSSBA) algorithm, which is the modified version of existing hybrid slot-size/rate (HSSR) algorithm. The performance of the proposed scheme has been analyzed by using numerical simulations in terms of the end-to-end packet delay, absolute delay variation, jitter, and throughput for both the HP and best effort (BE) traffic. We have also compared the simulation results of the proposed scheme with those of the existing modified HSSR (MHSSR), delay variation guaranteed protocol (DVGP), and HSSR schemes. From the comparison of the simulation results, at the highest offered load of 1.0, it can be seen that for the HP traffic the proposed scheme provides 60%, 50%, and 20% less average end-to-end delay than the existing HSSR, DVGP, and MHSSR schemes, respectively. At the highest offered load of 1.0, the proposed scheme also provides about 35% higher throughput than both the HSSR and DVGP schemes with 45% and 35% less jitter variation than the HSSR and DVGP schemes, respectively.

QoS-Based DWBA Algorithm for NG-EPON

The next-generation Ethernet passive optical network (NG-EPON) is basically classified into two architectures on the basis of the wavelength sharing by the optical network units (ONUs). The single scheduling domain (SSD) and multi-scheduling domain (MSD) EPON are the two different design architectures for NG-EPON. A vital task in NG-EPON is to design dynamic wavelength bandwidth allocation (DWBA) algorithms that can meet the future demands of the network subscribers. A number of DWBA algorithms have been designed for time and wavelength division multiplex (TWDM) EPON. The existing DWBA algorithms for TWDM-EPON could be used in MSD-EPON by making necessary parametric changes. The design and implementation of new DWBA algorithms for MSD-EPON are still required specifically. In this paper, we have proposed a quality of service (QoS)-based DWBA algorithm for NG-EPON. We have comparatively analyzed our proposed DWBA with the existing algorithms like earlier finished time (EFT), weighted bipartite matching (WBM), and earlier finished time with void filling (EFT-VF). The results show that our proposed DWBA algorithm performs better as compared to EFT, WBM, and EFT-VF on the basis of average packet delay and average completion time for NG-EPON.

Demand Forecasting DBA Algorithm for Reducing Packet Delay with Efficient Bandwidth Allocation in XG-PON

In a typical 10G-Passive Optical Network (XG-PON), the propagation delay between the Optical Network Unit (ONU) and Optical Line Terminal (OLT) is about 0.3 ms. With a frame size of 125 μs, this amounts to three frames of data in the upstream and three frames of data in the downstream. Assuming no processing delays, the grants for any bandwidth requests reach the ONU after six frames in this request-grant cycle. Often, during this six-frame delay, the queue situation is changed drastically, as much, more data would arrive in the queue. As a result, the queued data that is delayed loses its significance due to its real-time nature. Unfortunately, almost all dynamic bandwidth allocation (DBA) algorithms follow this request-grant cycle and hence lacking in their performance. This paper introduces a novel approach for bandwidth allocation, called Demand Forecasting DBA (DF-DBA), which predicts ONU’s future demands by statistical modelling of the demand patterns and tends to fulfil the predicted demands just in time, which results in reduced delay. Simulation results indicate that the proposed technique out-performs previous DBAs, such as GigaPON access network (GIANT) and round robin (RR) employing the request-grant cycle in terms of Throughput and Packet delivery ratio (PDR). Circular buffers are introduced in statistical predictions, which produce the least delay for this novel DF-DBA. This paper, hence, opens up a new horizon of research in which researchers may come up with better statistical models to brew better and better results for Passive optical networks.

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.

(Overlap and non-overlap)-based DBA algorithm with wavelength optimal length for upstream channel in multi-OLT PON

Abstract In this paper, an (overlap and non-overlap)-based dynamic bandwidth allocation (DBA) algorithm with wavelength optimal length (WOL) for upstream channel in multi-OLT passive optical network (PON) is proposed. By introducing optical line terminal (OLT) pool, the problem of OLT services imbalance is solved. Based on the service and its weight factor, proportion algorithm is constructed to allocate OLTs and wavelengths to OLT pool and wavelength group respectively. By proposing a new concept of WOL, the bandwidth wastage is reduced. By presenting overlap and non-overlap algorithms, the bandwidth utilization is improved further. By the simulation and analysis, the effectiveness of the proposed algorithms is demonstrated.

A Distributed Control Framework for TDM-PON Based 5G Mobile Fronthaul

The 5G mobile fronthaul (MFH) is bound to be overwhelmed by the explosive growth and stringent requirements of future wireless traffic. The time division multiplexed (TDM) passive optical network (PON) is a candidate for supporting such an MFH. Typically, such a TDM-PON utilizes upstream dynamic bandwidth allocation (DBA) schemes that are centralized at a distant central office (CO) which results in a performance that is not best suited for the MFH. Therefore, this work proposes a novel control framework by shifting the centralized DBA tasks away from the CO towards the closely clustered Remote Radio Heads (RRHs). By exploiting the interconnectivity of the RRHs, the access nodes exchange signaling and control information among themselves to facilitate a fully distributed upstream DBA without the involvement of the CO. The proposed framework separates the control plane from the data plane which paves the way for an efficient exchange of control messages, increased available upstream bandwidth and improved cyclic bandwidth allocation. This translates into a TDM-PON based MFH with lower latency, higher utilization and reduced packet loss.

Dynamic Bandwidth Allocation in Small-Cell Networks: An Economics Approach

We propose and experimentally demonstrate a bandwidth allocation method based on the comparative advantage of spectral efficiency among users in a multi-tone small-cell radio access system with frequency-selective fading channels. The method allocates frequency resources by ranking the comparative advantage of the spectrum measured at the receivers ends. It improves the overall spectral efficiency of the access system with low implementation complexity and independently of power loading. In a two-user wireless transmission experiment, we observe up to 23.1% average capacity improvement by using the proposed method.

Deep Learning-Based Dynamic Bandwidth Allocation for Future Optical Access Networks

Over the last decade, Passive Optical Networks (PONs) have emerged as an ideal candidate for next-generation broadband access networks. Meanwhile, machine learning and more specifically deep learning has been regarded as a star technology for solving complex classification and prediction problems. Recent advances in hardware and cloud technologies offer all the necessary capabilities for employing deep learning to enhance Next-Generation Ethernet PON’s (NG-EPON) performance. In NG-EPON systems, control messages are exchanged in every cycle between the optical line terminal and optical network units to enable dynamic bandwidth allocation (DBA) in the upstream direction. In this paper, we propose a novel DBA approach that employs deep learning to predict the bandwidth demand of end-users so that the control overhead due to the request-grant mechanism in NG-EPON is reduced, thereby increasing the bandwidth utilization. The extensive simulations highlight the merits of the new DBA approach and offer insights for this new line of research.

Traffic estimation based on long short-term memory neural network for mobile front-haul with XG-PON

A novel predictive dynamic bandwidth allocation (DBA) method based on the long short-term memory (LSTM) neural network is proposed for a 10-gigabit-capable passive optical network in mobile front-haul (MFH) links. By predicting the number of packets that arrive at the optical network unit buffer based on LSTM, the round-trip time delay in traditional DBAs can be eliminated to meet the strict latency requirement for MFH links. Our study shows that the LSTM neural network has better performance than feed-forward neural networks. Based on extensive simulations, the proposed scheme is found to be able to achieve the latency requirement for MFH and outperforms the traditional DBAs in terms of delay, jitter, and packet loss ratio.

Hierarchical evolutionary game based dynamic cloudlet selection and bandwidth allocation for mobile cloud computing environment

To bridge the gap between the resource-constrained mobile devices and the resource-demanding applications, mobile cloud computing (MCC) emerges for offloading complex tasks to a cloud server. Based on this concept, cloudlets, which move available resource to the vicinity of the mobile network, enhance further the system accessibility and performance. Moreover, to strengthen the network capacity in traffic intensive area, dense small cell network (DSCN) is proposed as one of the promising solutions. In this study, the operation of cloudlets and DSCN is collaboratively studied in order to further improve the system performance. On the one hand, users can select a cloudlet and dynamically adapt the connection according to the performance and the cost, which is referred to as a user-essential dynamic cloudlet selection problem. On the other hand, a cloudlet needs to set the optimal selling price and the size of resource for the users, which is considered as a cloudlet resource allocation problem. To jointly address the problems of dynamic cloudlet selection and resource allocation, the authors propose a hierarchical evolutionary game to maximise the utilities. Simulation studies are carried out to demonstrate the effectiveness of the proposed algorithms, which, indeed, improve the entire system performance significantly.

TWDM-PON中支持区分服务的节能动态波长带宽分配算法

TWDM-PON中支持区分服务的节能动态波长带宽分配算法

Adaptive dynamic wavelength and bandwidth allocation algorithm based on error-back-propagation neural network prediction

With the emergence of new services such as high-definition video, cloud computing and virtual reality, Wavelength Division Multiplexing/Time Division Multiplexing-Passive Optical Network (WDM/TDM-PON) has become a key technology for future access network. The development of Software Defined Networking (SDN) and machine learning also brings new opportunities to the flexibility of WDM/TDM-PON. In this paper, an Adaptive Dynamic Bandwidth Allocation algorithm based on error-back-propagation Neural Network Prediction (ADBA-NNP) was proposed to reduce the Round-trip-time (RTT) delay in the bandwidth-scheduling period. A Dynamic Wavelength Allocation (DWA) algorithm and a novel architecture of WDM/TDM-PON was proposed to simple the multi-carrier source. The experimental results validated that the proposed algorithm could dynamically allocate wavelengths under multi-carrier at 12.5G intervals. Compared with the traditional algorithms, the proposed algorithm could reduce the transmission delay by 25%.