Bandwidth Allocation Algorithm Research Articles

Node Classification-Based Bandwidth Allocation: A New Scheduling Algorithm for TDMA-Based LANs

Local area networks often comprise nodes that run applications that belong to different traffic classes, with each class having different bandwidth requirements. Traditional Medium Access Control (MAC) protocols treat all nodes in the same manner. This may lead to a disproportionate allocation of bandwidth to the nodes and, consequently, to significant performance degradation. In this paper, a new MAC algorithm, is presented, that allocates different amounts of bandwidth to the nodes according to their traffic class. The bandwidth allocated to the nodes of each traffic class is proportional to the bandwidth requirements of the nodes of that class. The performance of the proposed Node Classification-based Bandwidth Allocation (NCBA) algorithm is studied via extensive simulation results, which indicate that it achieves a significant performance improvement compared to the well-known TDMA scheme. Overall, the new protocol achieves higher throughput, lower delay and exhibits a higher delay Fairness compared to TDMA for various network configurations, under asymmetric bursty traffic.

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

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.

Backhaul-Aware Drone Base Station Placement and Resource Management for Fso Based Drone Assisted Mobile Networks

In drone assisted mobile networks, drones mounted small cell base stations (DBSs) are responsively and flexibly deployed over any Places of Interest (PoI), such as sporadic hotspots and disaster-struck areas, where the existing mobile network infrastructure is unable to provide wireless coverage. Here, a DBS is a relay node to relay traffic between a nearby macro base station (MBS) and the users. In addition, Free-space optics (FSO) is applied as the backhauling solution to significantly increase the capacity of the backhaul link between an MBS and a DBS in a drone assisted mobile network. Most of the existing DBS placement solutions assume the FSO based backhaul link provides sufficient link capacity, which may not be true, especially when a DBS is placed far away from an MBS (e.g., > 10 km in disaster-struck areas) or in a bad weather condition. In this paper, we formulate a problem to jointly optimize bandwidth allocation and DBS placement by considering the FSO based backhaul link capacity constraint. A Backhaul awaRe bandwidth allOcAtion and DBS placement (BROAD) algorithm is designed to efficiently solve the problem, and the performance of the algorithm is demonstrated via extensive simulations.

Research on Dynamic Bandwidth Allocation Algorithm for Software Defined Network of Virtual Power Plant

An adaptive dynamic bandwidth allocation algorithm based on Software Defined Network is proposed to solve the problems of poor flexibility and low resource utilization in Virtual Power Plant communication. The algorithm first proposes the algorithm system structure of the Virtual Power Plant based on the Software Defined Network, and then collects and analyzes the node state information, then modularizes the control and calculates the optimal bandwidth through the Software Defined Network Controller, and finally saves energy according to the resource allocation. The algorithm is developed with different authorization adjustment strategies, and compared with the traditional hybrid TDM/WDM-EPON dynamic algorithm, the experimental results show that the algorithm reduces the packet delay and average queue depth under medium and low load, and the percentage of energy saving under small load can reach 93.2%, which can effectively improve the utilization of bandwidth resources and achieve the energy-saving effect of Virtual Power Plant communication system itself.

Path Load Adaptive Migration for Routing and Bandwidth Allocation in Mobile-Aware Service Function Chain

With network function virtualization (NFV) expanding from network center to edge, the service function chain (SFC) will gradually approach users to provide lower delay and higher-quality services. User mobility seriously affects the quality of service (QoS) provided by the mobile-aware SFC. Therefore, we must migrate the SFC to provide continuous services. In the user estimable movement scenario with a known mobile path and estimable arrival time, we establish the estimation model of user arrival time to obtain the estimated arrival time. Then, to reduce the time that the user is waiting for the migration completion, we propose a softer migration strategy migrating mobile-aware SFC before the user arrives at the corresponding access node. Moreover, for the problem of routing and bandwidth allocation (RBA), to reduce the migration failure rate, the paper proposes a path load adaptive routing and bandwidth allocation (PLARBA) algorithm adjusting the migration bandwidth according to the path load. The experimental results show that the proposed algorithm has significant advantages in reducing the user’s waiting time by more than 90%, decreasing migration failure rate by up to 75%, and improving QoS compared to the soft migration strategy and two RBA algorithms.

Multi-server federated edge learning for low power consumption wireless resource allocation based on user QoE

Federated edge learning (FEL) deploys a machine learning algorithm by using devices distributed on the edge of a network, trains massive local data, uploads the local model to update the parameters after training, and performs alternate updating with global model parameters to reduce the pressure for uplink data transmission, prevent systematic time delay and ensure data security. This paper proposes that an optimal balance between time delay and energy consumption be achieved by optimizing the transmission power and bandwidth allocation based on user quality of experience (QoE) in a multi-server intelligent edge network. Given the limited computing capability of devices involved in FEL local training, the transmission power is modeled as a quasi-convex uplink power allocation (UPA) problem, and a lower energy consumption bandwidth allocation algorithm is proposed for solution-seeking. The proposed algorithm allocates appropriate power to the device by adapting the computing power and channel state of the device, thereby reducing energy consumption. As the theoretical deduction result suggests that additional bandwidth should be allocated to those devices with weak computing capabilities and poor channel conditions to realize minimal energy consumption within the restraint time. The simulation result indicates that, the maximum gain of the proposed algorithm can be optimized by 31% compared with the baseline.

A novel dynamic bandwidth allocation algorithm in optical access systems

A novel dynamic bandwidth allocation algorithm in optical access systems

Ensuring the QoE-Related Fairness to Reduce the User Abandonment Ratio.

Nowadays, it is quite a challenge for app owners to keep users engaged with an app. Currently, the level of user abandonment is one of the key parameters that application owners are interested in. To meet these challenges, we conduct an extended study of a previously proposed solution that significantly reduces the abandonment rate of a given application. The investigated solution is based on the methods of fairness using the QoE and QoS approach. This paper shows that application abandonment ratios can be reduced by using an appropriate approach to fair bandwidth allocation. Adjusting the bandwidth allocation to users, taking into account the quality of the user experience, has a more effective effect on reducing app abandonment ratios than if quality of service is taken into account. This is because the users make the decision to abandon the application based on their feelings rather than technical parameters. In order to effectively reduce application abandonment ratios, a suitable bandwidth allocation algorithm must be used. This paper presents the impact of using different algorithms on the abandonment ratio and compares the popularly used algorithms and the previously proposed bandwidth allocation algorithm.

Traffic localization-based dynamic bandwidth allocation algorithm for improvement of QoS in peer-to-peer architecture of passive optical networks

Passive optical network (PON) is a popular technology, in recent days, which can be merged with peer-to-peer (P2P) network architecture. In P2P architecture, there is no need for a dedicated server and each peer can provide the data and receive the required data from other peers. With increasing traffic, there occurs aproblem in resource sharing and therefore, the users experience higher latency and lower overall quality of services (QoSs). There are several recent studies regarding the use of PON in P2P network architecture, and some of them are studied for localization of traffic. But in the case of localizing traffic, the use of multiple upstream wavelengths was not studied previously. In this paper, we have proposed a new PON architecture and a new dynamic bandwidth allocation (DBA) algorithm called localizing traffic-based DBA (LT-DBA) to improve the overall QoSs of the PON-based P2P network. By localizing the intra-PON traffic, this architecture separates the inter-PON and intra-PON traffic. Here, in addition to the conventional passive optical splitter, a wavelength reflector is used which can reflect the upstream wavelength used for intra-PON traffic. We also propose an efficient management scheme of the intra-PON traffic, where no report is needed to send to the optical line terminal (OLT). The OLT needs not to allocate time-slot for local packets, and there is a huge optimization of resources. The LT-DBA scheme was evaluated by formulating mathematical models and numerical simulations. The simulations were performed by varying the percentage of local data and by changing the number of optical network units in PON. The simulation results show that our proposed architecture and LT-DBA scheme outperform the existing REDIRECT DBA scheme in terms of end-to-end delay, jitter, and throughput.

Security enhanced dynamic bandwidth allocation algorithm against degradation attacks in next generation passive optical networks

The dynamic bandwidth allocation (DBA) algorithm is highly impactful in improving the network performance of gigabit passive optical networks (GPON). However, reports delineating its vulnerability to certain attacks can be found in the literature, thus raising concerns. A degradation attack manipulates the transmission control protocol (TCP) congestion control algorithm, which may impact the received bandwidth of targeted network users. Here, the absence of electronics within the passive splitter renders attack identification in GPONs a significant challenge. Therefore, the current study aimed to propose a secured DBA mechanism known as security enhanced DBA capable of overcoming this particular threat. A detection phase served as a critical component for sensing and subsequently mitigating any abnormal behaviors observed among optical network units (ONUs). Upon identification of the attacker, penalties were imposed to deter the next attack attempt and reestablish the fairness to previously attacked ONUs. The simulation findings revealed throughput improvement of up to 63% due to the security feature offered by the mechanism. Besides, significant improvements for the upstream delay performance recorded at 52%, 60%, and 65% for traffic containers (TCONT) TCONT2, TCONT3, and TCONT4, respectively, were observed in comparison to the non-secure DBA mechanism. Hence, the integration of the security mechanisms in DBA renders it possible to avoid any exploitation of GPON vulnerability in hacking other users’ bandwidth.

Dynamic Bandwidth allocation algorithm for avoiding Frame rearrangement in NG-EPON

Next Generation Ethernet Passive Optical Network (NG-EPON) is considered to be future prospective access technology that could help to achieve 100Gbps data rates. Wavelength bonding is a phenomenon that can help Optical Network Units (ONU) to enhance their transmission capabilities. Using wavelength bonding, an ONU could transmit on multiple wavelength channels in parallel. The ONUs can achieve data transmission rates ranging from 25Gbps to 100Gbps. In upstream direction, ONUs share different available channels in time-sharing manner to effectively utilize the resources in NG-EPON. Dynamic Wavelength & Bandwidth Allocation (DWBA) algorithm is required for efficient allocation of wavelength and bandwidth resources in upstream direction. DWBA plays a vital role to help ONUs for transmission on multiple channels simultaneously. When an ONU transmits on multiple channels, a frame-rearrangement problem would occur at the Optical Line Terminal (OLT). OLT suffers from an extra overhead of frame-rearrangement; as the received frames at OLT are not in proper sequence. DWBA can play a vital role in avoiding frame rearrangement overhead. We proposed a DWBA algorithm to avoid/minimize frame rearrangement problem and efficient bandwidth allocation in NG-EPON. Our proposed DWBA avoids and minimizes frame-rearrangement problem and provides efficient resource allocation. We comparatively analyzed and evaluated our proposed DWBA with the existing DWBA algorithm. The simulation results show that our proposed DWBA minimizes frame-rearrangement problem as compared to existing DWBA algorithms and proves to be more efficient based on average (end-to-end) delay and completion time.

Bin-packing based offline dynamic bandwidth and wavelength allocation algorithms for power efficiency in Super-PON

Enduring the rapidly growing demand for high data rates is the main challenge for the current network providers. Super passive optical network (Super-PON), a prominent next generation Ethernet PON (NG-EPON) candidate, can suffice this exponentially increasing data rate requirements. However, to appease such requirements, it employs many transceivers and increases the power-consumption of the network. In this work, we focus on reducing the carbon footprint of Super-PON and propose power-efficient dynamic bandwidth and wavelength allocation (DBWA) algorithms, namely best fit bin-packing sleep mode aware (BF-SMA) and updated BF-SMA (UBF-SMA). The proposed algorithms use SMA for bandwidth scheduling and different bin-packing techniques for wavelength allocation. In bin-packing, the number of available wavelengths and their efficient allocation is based on the network load. For restricting the number of available wavelengths, we can switch off the non-essential transceivers at the OLT, which also helps in maximizing the wavelength utilization and increasing the power efficiency. The simulation results show that in comparison to the state-of-the-art DBWA algorithms, the proposed algorithms improve the power efficiency and reduce the average delay of a Super-PON system. Furthermore, we use Jain’s fairness index to validate the fairness of the proposed DBWA algorithms.

An Intelligent Dynamic Bandwidth Allocation Method to Support Quality of Service in Internet of Things

Worldwide, Internet of Things (IoT) devices will surpass a range of five billion by 2025 and developed countries will extend to advance by supplying almost two-thirds of such connections. With existing infrastructure, allocating bandwidth to billions of IoT devices is going to be cumbersome. This paper addresses the problem of Dynamic bandwidth allocation in IoT devices. We enhanced the dynamic bandwidth allocation algorithms to support QoS in different bandwidth ranges. Our Proposed innovative Machine learning-based Intelligent Dynamic Bandwidth Allocation (IDBA) algorithm allocates the bandwidth effectively between IoT devices based on utilization patterns observed through machine learning methods. Moreover, we showed that an IDBA algorithm results in supporting quality of service in terms of ensuring uninterrupted bandwidth to critical IoT application where bandwidth tolerance is zero percent, along with that IDBA increasing the network throughput correlated to other dynamic bandwidth allocation algorithms. We demonstrate simulations in different applications. The results show that IDBA achieves better throughput even in low bandwidth range.

Dynamic bandwidth allocation algorithm for long reach passive optical network

Next generation broadband access networks are gaining more interests from many key players in this field. The demands for longer reach and higher bandwidth are among the driving factors for such network as it can reach wider area up to 100 km, even beyond; has enhanced bandwidth capacity and transmission speed, but with low cost and energy consumption. One promising candidate is long reach passive optical network, a simplified network with reduced number of network elements, equipment interfaces, and even nodes; which leads to a significant reduction in the network’s capital expenditure and operational expenditure. Outcome of an extended reach often results in increased propagation delay of dynamic bandwidth allocation messages exchange between the optical line terminals and optical network units, leading to the degradations of bandwidth allocation and quality of service support. Therefore, an effective bandwidth allocation algorithm with appropriate service interval setup for a long reach network is proposed to ensure the delay is maintained under ITU-T G.987.1 standard requirement. An existing algorithm is improved in terms of service interval so that it can perform well beyond 100 km. Findings show that the improved algorithm can reduce the mean delay of high priority traffic classes for distance up to 140 km.

Cluster-based PON with dynamic upstream data transmission sequence algorithm for improving QoSs

Passive optical network (PON) with online polling-based dynamic bandwidth allocation (DBA) algorithms effectively reduces the granting and back-off delays as well as the overall end-to-end delay of the PON with offline polling-based DBA schemes. However, in the online polling-based DBA schemes, distribution of excess bandwidths from the lightly loaded optical network units (ONUs) to the highly loaded ONUs is not possible. In both the conventional online and offline polling-based DBA schemes, theoptical line terminal (OLT) assigns the time-slots to the ONUs for upstream data transmissions based on the first-come-first-serve principle. That is why the highly loaded ONUs those remainbehind the lightly loaded ONUs should be waited until the end of the upstream data transmissions of all the preceding ONUs. Due to this longer waiting time before getting the chance to transmit the upstream data increases the possibility of buffer overflow of the highly loaded ONUs. In this paper, a new cluster-based PON architecture with a dynamic upstream data transmission sequence (DUDTS) algorithm is introduced. In the cluster-based PON with DUDTS scheme, all the active ONUs of a PON system are divided into several clusters. Then the data transmission sequence of the ONUs in each cluster is dynamically changed to give higher priority to the highly loaded ONUs for assigning the earlier time-slots than the lightly loaded ONUs. The DUDTS scheme also considers the traffic incoming statuses in the ONUs’ buffer,distributes the excess bandwidth from the lightly loaded ONUs to the highly loaded ONUs within a cluster, and adds the unutilized bandwidth of a cluster to the ONUs of thefollowing cluster. Numerical simulations are performed to evaluate and compare the performances among the proposed cluster-based PON with DUDTS scheme and the existing dynamic hybrid slot-size bandwidth allocation (DHSSBA) algorithm to demonstrate the effectiveness of the proposed scheme. The cluster-based PON with DUDTS scheme provides better results in terms of the grant to request ratio, end-to-end delay, packet loss probability, and fairness compared to the existing DHSSBA scheme.

A QoS-Aware Dynamic Bandwidth Allocation Algorithm for Passive Optical Networks with Non-Zero Laser Tuning Time

The deployment of new 5G services and future demands for 6G make it necessary to increase the performance of access networks. This challenge has prompted the development of new standardization proposals for Passive Optical access Networks (PONs) that offer greater bandwidth, greater reach and a higher rate of aggregation of users per fiber, being Time- and Wavelength-Division Multiplexing (TWDM) a promising technological solution for increasing the capacity by up to 40 Gbps by using several wavelengths. This solution introduces tunable transceivers into the Optical Network Units (ONUs) for switching from one wavelength to the other, thus addressing the ever-increasing bandwidth demands in residential broadband and mobile fronthaul networks based on Fiber to the Home (FTTH) technology. This adds complexity and sources of inefficiency, such as the laser tuning time (LTT) delay, which is often ignored when evaluating the performance of Dynamic Bandwidth Allocation (DBA) mechanisms. We present a novel DBA algorithm that dynamically handles the allocation of bandwidth and switches the ONUs’ lasers from one wavelength to the other while taking LTT into consideration. To optimize the packet delay, we introduce a scheduling mechanism that follows the Longest Processing Time first (LPT) scheduling discipline, which is implemented over the Interleaved Polling with Adaptive Cycle Time (IPACT) DBA. We also provide quality of service (QoS) differentiation by introducing the Max-Min Weighted Fair Share Queuing principle (WFQ) into the algorithm. The performance of our algorithm is evaluated through simulations against the original IPACT algorithm, which we have extended to support multi-wavelengths. With the introduction of LPT, we obtain an improved performance of up to 73% reduction in queue delay over IPACT while achieving QoS differentiation with WFQ.

Cloud radio access network fronthaul solution using optimized dynamic bandwidth allocation algorithm

In order to address the challenges that have come with the exploding demand for higher speed, traffic growth and mobile wireless devices, Mobile network operators have decided to move to the notion of small cells based on cloud radio access network. The merits of cloud based RAN includes the ease of infrastructure deployment and network management as well as the fact that its performance are optimized and it is cost effective the merits of cloud based RAN includes the ease of infrastructure deployment and network management as well as the fact that its performance are optimized and it is cost effective. Notwithstanding, cloud radio access network comes with so many strict requirements to be fulfilled for its fronthaul network. In this paper, we have presented these requirements for a 5G fronthaul network. Particular interest on the time division multiplex passive optical network’s challenge of latency was treated by proposing an optimized version of the round robin dynamic bandwidth allocation algorithm. Results obtained show an improvement in the latency of the original algorithm which meets the fronthaul requirement. Other test parameters like jitter and BER were also improved by our proposed optimized algorithm.

Modified Dynamic Bandwidth Allocation Algorithm for Upstream Access in WDM/TDM PON to Reduce Energy Consumption

Modified Dynamic Bandwidth Allocation Algorithm for Upstream Access in WDM/TDM PON to Reduce Energy Consumption

Bin-Packing-Based Online Dynamic Bandwidth and Wavelength Allocation Algorithm in Super-PON

Super passive optical network (Super-PON) is a next-generation Ethernet PON (NG-EPON) candidate that is envisaged to provide high data rate and low latency. For NG-EPON, there are two types of algorithms that manages bandwidth and wavelength scheduling, namely offline and online. The latter method is more scalable and efficient than the former method. Several online algorithms exist that propose schemes to manage wavelength and bandwidth scheduling. However, these algorithms lack in efficient wavelength utilization and switching. In this work, we propose a novel online bin-packing based dynamic bandwidth and wavelength allocation (DBWA) algorithm for Super-PON, namely updated best fit bin-packing (UBF-BP). This algorithm limits the wavelength switching per cycle, and uses the modified version of best fit bin-packing (BF-BP) technique for optimal wavelength allocation. Simulation results show that the proposed DBWA algorithm has a low complexity and overcomes the inefficiencies of wavelength utilization and switching. This results in lower network delay and higher channel utilization than the state-of-the-art DBWA. Furthermore, to verify the correctness of the proposed algorithm, we propose an analytical model and validate these simulation results with the analytical results.

A Case for Pricing Bandwidth: Sharing Datacenter Networks With Cost Dominant Fairness

Unlike other resources such as CPU or memory in a virtual machine, inter-virtual-machine (inter-VM) bandwidth has not been explicitly priced in datacenter networks. In this article, we argue that tenants of an IaaS cloud computing platform should be given the flexibility to pay more for explicitly priced datacenter bandwidth beyond traditional virtual machines, in order to achieve better (or more predictable) application performance. We show that a much simpler design principle can be followed to allocate bandwidth fairly, and desirable properties related to fairness can be more easily achieved, compared with state-of-the-art proposals. We call such a design principle cost dominant fairness, which stipulates that bandwidth should be allocated based on the total cost that a tenant incurs for running its applications in the cloud. Guided by the principle of cost dominant fairness, we explore the design space of pricing inter-VM bandwidth, as well as achieving fair bandwidth sharing among multiple tenants. Through our study, we believe that it is best to assign per-VM-pair weights based on individualized prices. We present a distributed bandwidth allocation algorithm that is theoretically supported by a network utility maximization formulation, and practically implemented as a shim layer at each virtual machine. We are also concerned with practical issues of billing, where discounts are needed to ensure that a tenant only pays for the bandwidth share that it is allocated. Finally, we have evaluated our pricing framework and per-VM-pair weighted fair bandwidth allocation in the Mininet emulation testbed and simulations.