Journal articles: 'Bandwidth Allocation Model'

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Torres, Eliseu, Rafael F. Reale, Leobino L. Sampaio, and Joberto S. B. Martins. "A SDN/OpenFlow Framework for Dynamic Resource Allocation based on Bandwidth Allocation Model." IEEE Latin America Transactions 18, no. 5 (2020): 853–60. https://doi.org/10.5281/zenodo.3766178.

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The communication network context in actual systems like 5G, cloud and IoT (Internet of Things), presents an ever-increasing number of users, applications and services that are highly distributed with distinct and heterogeneous communications requirements. Resource allocation in this context requires dynamic, efficient and customized solutions and Bandwidth Allocation Models (BAMs) are an alternative to support this new trend. This paper proposes the BAMSDN (Bandwidth Allocation Model through Software-Defined Networking) framework that dynamically allocates resources (bandwidth) for a MPLS (MultiProtocol Label Switching) network using a SDN (Software-Defined Networking)/OpenFlow strategy with BAM. The framework adopts an innovative implementation approach for BAM systems by controlling the MPLS network using SDN with OpenFlow. Experimental results suggest that using SDN/OpenFlow with BAM for bandwidth allocation does have effective advantages for MPLS networks requiring flexible resource sharing among applications and facilitates the migration path to a SDN/OpenFlow network.

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Balogh, Tomáš, and Martin Medvecký. "Average Bandwidth Allocation Model of WFQ." Modelling and Simulation in Engineering 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/301012.

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We present a new iterative method for the calculation of average bandwidth assignment to traffic flows using a WFQ scheduler in IP based NGN networks. The bandwidth assignment calculation is based on the link speed, assigned weights, arrival rate, and average packet length or input rate of the traffic flows. We prove the model outcome with examples and simulation results using NS2 simulator.

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Ituma, Chinagolum, Mercy Ebere Ikem, and Azemobor Daniel. "Development of Bandwidth Utilization in a Dynamic Network Environment for Network Resource Allocation Using Neural Network." advances in multidisciplinary & scientific research journal publication 16, no. 1 (2025): 1–8. https://doi.org/10.22624/aims/cisdi/v16n1p1.

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Bandwidth is a measure of how much information a network can transfer and receive. It is purchased from internet provider as a periodic monthly expense based on the amount of bandwidth selected by the establishment. Over the years’ business owners, organizations, schools etc. that uses internet for their day to day activities have been allocated bandwidth by internet service providers (ISP) using historical data but most times allocation of this bandwidth could be in excess or too small a bandwidth resulting to slowness of internet access and wastage of bandwidth due to lack of a model or platform that assist the ISP in predicting and allocating the exact bandwidth needed by the users, excess of allocated bandwidth leads to wastage of bandwidth. Not knowing those parameters associated to bandwidth allocation and their consumption, limited amount of bandwidth causes slow network performance and slow download and upload speeds, inability to calculate the amount of bandwidth needed by an individual on a network. This paper uses inputted parameters like number of users, service usage either video or audio etc. this input determine the prediction and allocation, Carry out performance evaluation of the proposed system by comparing it with other existing systems. The methodology that was adopted is Object Oriented Analysis and Design Methodology (OOADM). Hypertext preprocessor (PHP) was used for the development while My Structured Query Language (MYSQL) for the database management. After the development the model was able to allocate accurate bandwidth to users. Keywords: Bandwidth, Neural Network, Dynamic environment, Allocation, Prediction CISDI Journal Reference Format Ituma Chinagolum, Mercy Ebere Ikem & Azemobor Daniel (2025): Development of Bandwidth Utilization in a Dynamic Network Environment for Network Resource Allocation Using Neural Network. Computing, Information Systems, Development Informatics & Allied Research Journal. Vol 16 No 1, Pp 1-8. Available online at www.isteams.net/cisdijournal. dx.doi.org/10.22624/AIMS/CISDI/V16N1P1

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Elmaghraby, Adel S., Anup Kumar, Mehmed M. Kantardzic, and Mostafa Gamal Mostafa. "A Scalable Pricing Model for Bandwidth Allocation." Electronic Commerce Research 5, no. 2 (2005): 203–27. http://dx.doi.org/10.1007/s10660-005-6157-0.

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Lahiya, Indah Wardati, and Fatchul Arifin. "Implementation of FDSS (Fuzzy Decision Support System) Sugeno Model in Optimizing Bandwidth Requirement Management of Web-Based Networks." Elinvo (Electronics, Informatics, and Vocational Education) 8, no. 2 (2024): 171–81. http://dx.doi.org/10.21831/elinvo.v8i2.57557.

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To increase the efficacy of bandwidth allocation at PT. Digdaya Monokrom Group, this study describes the development of a Fuzzy Decision Support System (FDSS) utilizing the Sugeno methodology. The Waterfall development process is employed for the purposes of system planning, construction, and maintenance. The study consists of three primary stages: the creation of fuzzy sets, the development of fuzzy rules, and the process of defuzzification. The study findings demonstrate that the utilization of FDSS has effectively improved the distribution of bandwidth. The distribution has shifted from a uniform one to a more optimized allocation, focusing on the Execution, Content Creator, Administration, and Research Team departments. During a four-week monitoring period, modifications were implemented to distribute bandwidth based on the preferences and needs of various departments, while adhering to the limitations of the current broadband subscription. This has enhanced the efficient exploitation of network resources. The research findings highlight the efficacy of FDSS in prioritizing resource allocations according to specific departmental requirements, consequently improving service quality and maximizing bandwidth subscription capacity. This demonstrates the implementation of strategic management methodologies to optimize the allocation of network resources, resulting in enhanced organizational efficiency and production.

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Rafael, Freitas Reale, Martins da S. Bezerra Romildo, and S. B. Martins Joberto. "Applying Autonomy with Bandwidth Allocation Models." International Journal of Communication Systems 29, no. 13 (2016): 2028–40. https://doi.org/10.5281/zenodo.1287914.

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Bandwidth Allocation Models (BAMs) are resource allocation methods used for networks in general. BAMs are currently applied for handling resources such as bandwidth allocation in MPLS DS-TE networks (LSP setup). In general, BAMs defines resource restrictions by “class” and allocate the available resources on demand. This is frequently necessary to manage large and complex systems like routing networks. GBAM is a new generalized BAM that, by configuration, incorporates the “behavior” of existing BAMs (MAM, RDM, G-RDM and AllocTC-Sharing). In effect, any current available BAM “behavior” is reproduced by G-BAM by simply adjusting its configuration parameters. This paper focuses on investigating the applicability of using autonomy together with Bandwidth Allocation Models (BAMs) for improve performance and facilitating the management of MPLS DS-TE networks. It is investigated the applicability of “BAM switching” using a framework with autonomic characteristics. In brief, it is investigated the switching among “BAM behaviors” and BAM´s reconfiguration with distinct network traffic scenarios by using GBAM. Simulation results suggest that the autonomic switching of “BAM behaviors” based on high-level management rules (SLAs, QoS or other police) may result in improving overall network management and operational parameters such as link utilization and preemption.

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Kołtyś, Kamil, Piotr Pałka, Eugeniusz Toczyłowski, and Izabela Żółtowska. "Multicommodity Auction Model for Indivisible Network Resource Allocation." Journal of Telecommunications and Information Technology, no. 4 (June 26, 2023): 60–66. http://dx.doi.org/10.26636/jtit.2008.4.900.

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In this paper we present the multicommodity auction model BCBT-I that allocates indivisible network resources among bidders. The approach can be considered as a generalization of the basic multicommodity model for balancing communication bandwidth trade (BCBT). The BCBT model assumes that offers concerning inter-node links and point-to-point bandwidth demands can be realized partially. However, in the real-world trade there might be a need to include ca- pacity modularity in the market balancing process. Thus we state the model for balancing communication bandwidth trade that takes into account the indivisibility of traded bandwidth modules. This requires to solve a mixed integer problem and increases computational complexity. Furthermore, the pricing issue appears nontrivial, as the dual prices cannot be longer used to set fair, competitive market prices. For clearing the market, we examine the multicommodity pricing mechanism based on differentiation of buy and sell market prices

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Rafael, Freitas Reale, Martins da S. Bezerra Romildo, and S. B. Martins Joberto. "G–BAM: A Generalized Bandwidth Allocation Model for IP/MPLS/DS-TE Networks." International Journal of Computer Information Systems and Industrial Management Applications 6 (December 1, 2014): 635–43. https://doi.org/10.5281/zenodo.1292772.

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Bandwidth Allocation Models (BAMs) configure and handle resource allocation (bandwidth, LSPs, fiber) in networks in general (IP/MPLS/DS-TE, optical domain, other). BAMs currently available for IP/MPLS/DS-TE networks (MAM, RDM, G-RDM and AllocTC-Sharing) basically define resource restrictions (bandwidth) by “class” (traffic class, application´s class, user´s class or other grouping criteria) and allocate on demand this resource. There is a BAM allocation policy inherent for each existing model which behaves differently under distinct network state, such as heavy traffic loads and dynamic traffic and/or application scenarios. A generalized Bandwidth Allocation Model (G-BAM) is proposed in this paper. G-BAM, firstly, incorporates the inherent behavior of currently used BAMs such as MAM, RDM, G-RDM and AllocTC-Sharing in IP/MPLS/DS-TE context. G-BAM, secondly, proposes a new policy/ behavior allocation in addition to existing ones in which additional private resources are incorporated. G-BAM, thirdly, allows a smoother BAM policy transition among existing policy alternatives resulting from MAM, RDM and AllocTC-Sharing adoption independently.  The paper focuses on the first characteristics of G-BAM which is to reproduce MAM, RDM and AllocTC-Sharing behaviors. As such, the required configuration to achieve MAM, RDM and AllocTC-Sharing behaviors is presented followed by a proof of concept. Authors argue that the G-BAM reproducibility characteristics may improve overall network resource utilization under distinct traffic profiles.

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Vanitha, G., and P. Amudha. "Quality of Service Aware Dynamic Bandwidth Allocation for Rate Control in WSN." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 11s (2023): 166–76. http://dx.doi.org/10.17762/ijritcc.v11i11s.8083.

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Different types of data can be generated by Wireless Sensor Networks (WSNs) in both Real-Time (RT) and Non-RT (NRT) scenarios. The combination of these factors, along with the limited bandwidth available, necessitates careful management of these categories in order to reduce congestion. Due to this, a Proficient Rate Control and Fair Bandwidth Allocation (PRC-FBA) method has been created that prioritizes certain types of traffic and creates a virtual queue for them.In PRC-FBA, the Signal-to-Noise and Interference Ratio (SINR) model is applied to the problem of bandwidth allocation in WSN in an effort to find a compromise between equity and performance. Then, a brand-new bandwidth utility factor is defined with regard to equity and effectivenes. The FBA method in PRC-FBA is devoped for only improving throughput, but not considering delay. However, delay is the main factors for trasnmiitng NRT packets. This paper offers a PRC with Quality of Service (QoS) aware Dynamic Bandwidth Allocation (PRC-QDBA) approach for allocating bandwidth while prioritizing packets based on their traffic classes. This model employs a QoS associated dynamic bandwidth allocation strategy which efficiently distributes the unused time slots among the required nodes. The distribution technique is performed based on hierarchical manner utilizing a parent-child association of tree topology. The parent node receives traffic indication maps (TIMs) from the children nodes and adopts them to allocate time slots based on their demamds. If the parent node is unable to allocate the required slots, it creates a TIM that indicating the demands and transfer it to its immediate parent node. This increases the entire performance rate of RT traffic. Furthermore, this model assures the packet forwarding for previously accepted flows by allowing node transmission based on ancestral connection capabilities. Finally, simulation results demonstartes that the suggested model significantly increases the throughput and delay for bandwidth allocation while also enabling QoS support for RT traffic in WSNs.

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Lalitha, Aswani, and Gangireddy Harinatha Reddy. "An Integrated Signal Allocation Model with Effective Collision Resolution Model for Performance Enhancement of Wireless Sensor Networks." Traitement du Signal 38, no. 5 (2021): 1369–75. http://dx.doi.org/10.18280/ts.380512.

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A Wireless Sensor Network (WSN) differs from conventional wireless or wired networks in that it interacts with the environment. Orthogonal Frequency Division Multiplexing (OFDM) was investigated as a possible interface technology for making effective use of bandwidth. Such networks have been proposed for a variety of purposes such as search and rescue, disaster assistance, and smart positioning systems. These applications often require a large number of wireless sensors that are powered by batteries and are designed for long-term, human-free deployment. Collisions between network nodes can significantly degrade performance in WSNs. Although increased bandwidth facilitates wireless access to high data frequencies, it is prohibitively expensive to increase due to spectrum limits. This necessitates making good use of the available bandwidth. OFDM has been considered as a possible interface mechanism for efficiently utilising bandwidth. While many signals available in WSN technology can be employed to mitigate collisions, multi-signal allocations may have a significant impact on the efficiency of multistage communications. Real-time multimedia flow raises the chance of sensor network failures and congestion, which reduces the efficiency of Quality of Service (QoS). The main goal of the Signal Allocation Scheme is to allocate an appropriate number of signals to any node in order to use professional bandwidth and assure QoS. Load balancing is intended to measure and prevent collisions caused by the number of available slots in the frame. Preparation is another important component in preventing collisions because it decreases delay and optimises energy utilisation. In this paper, an Integrated Signal Allocation Model with Effective Collision Resolution Model (ICAM-ECR) is used to deploy non-overlapping signals dynamically for varying application loads based on expected bandwidth estimation. The suggested model is compared to standard methods, and the findings reveal that the proposed model outperforms existing models.

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Li, Shiyong, Yue Zhang, Yan Wang, and Wei Sun. "Utility optimization–based bandwidth allocation for elastic and inelastic services in peer–to–peer networks." International Journal of Applied Mathematics and Computer Science 29, no. 1 (2019): 111–23. http://dx.doi.org/10.2478/amcs-2019-0009.

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Abstract This paper considers reasonable bandwidth allocation for multiclass services in peer-to-peer (P2P) networks, measures the satisfaction of each peer as a customer by a utility function when acquiring one service, and develops an optimization model for bandwidth allocation with the objective of utility maximization. Elastic services with concave utilities are first considered and the exact expression of optimal bandwidth allocation for each peer is deduced. In order to obtain an optimum in distributed P2P networks, we develop a gradient-based bandwidth allocation scheme and illustrate the performance with numerical examples. Then we investigate bandwidth allocation for inelastic services with sigmoidal utilities, which is a nonconvex optimization problem. In order to solve it, we analyze provider capacity provisioning for bandwidth allocation of inelastic services and modify the update rule for prices that service customers should pay. Numerical examples are finally given to illustrate that the improved scheme can also efficiently converge to the global optimum.

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Wayer, Shahaf I., and Arie Reichman. "Resource Management in Satellite Communication Systems: Heuristic Schemes and Algorithms." Journal of Electrical and Computer Engineering 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/169026.

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The high cost of frequency bandwidth in satellite communication emphasizes the need for good algorithms to cope with the resource allocation problem. In systems using DVB-S2 links, the optimization of resource allocation may be related to the classical multi-knapsack problem. Resource management should be carried out according to the requests of subscribers, their priority levels, and assured bandwidths. A satisfaction measure is defined to estimate the allocation processes. Heuristic algorithms together with some innovative scaling schemes are presented and compared using Monte Carlo simulation based on a traffic model introduced here.

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. Reale, Rafael F., Romildo M. da S. Bezerra, and Joberto S. B. Martins. "A Bandwidth Allocation Model Provisioning Framework with Autonomic Characteristics." International journal of Computer Networks & Communications 5, no. 6 (2013): 103–19. http://dx.doi.org/10.5121/ijcnc.2013.5606.

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Reale, Rafael F., Romildo Martins S. Bezerra, and Joberto Sergio B. Martins. "A Preliminary Evaluation of Bandwidth Allocation Model Dynamic Switching." International journal of Computer Networks & Communications 6, no. 3 (2014): 131–43. http://dx.doi.org/10.5121/ijcnc.2014.6311.

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Salkin Lutfi, Syarifuddin Kapita, Hairil Kurniadi Sirajuddin, and Yasir Muin. "Development of Adaptive Bandwidth Allocation Model Using PCQ for Network Performance Optimization." Technium: Romanian Journal of Applied Sciences and Technology 17 (November 1, 2023): 234–37. http://dx.doi.org/10.47577/technium.v17i.10081.

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The number of clients has an impact on network performance, and while more bandwidth capacity can sometimes result in better network services, it is not always a given. Clients acquire the appropriate bandwidth, which is managed at the network layer by software, to control the flow and number of packets in the network. The practice of managing bandwidth includes measuring and controlling communications (traffic and packets) through network channels. This is done to prevent overburdening or overloading networks, which will lead to network congestion and poor performance. The goal of this study is to improve the internet network through bad-width allocation using the PCQ approach. When it comes to sharing bandwidth with active users and large users, the results of the suggested strategy are excellent.

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Wang, Shuo, Zhiqiang Zhou, Hongjie Zhang, and Jing Li. "Nxt-Freedom: Considering VDC-Based Fairness in Enforcing Bandwidth Guarantees in Cloud Datacenter." Applied Sciences 10, no. 21 (2020): 7874. http://dx.doi.org/10.3390/app10217874.

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In the cloud datacenter, for the multi-tenant model, network resources should be fairly allocated among VDCs (virtual datacenters). Conventionally, the allocation of cloud network resources is on a best-effort basis, so the specific information of network resource allocation is unclear. Previous research has either aimed to provide minimum bandwidth guarantee, or focused on realizing work conservation according to the VM-to-VM (virtual machine to virtual machine) flow policy or per-source policy, or both policies. However, they failed to consider allocating redundant bandwidth among VDCs in a fair way. This paper presents a bandwidth that guarantees enforcement framework NXT-Freedom, and this framework allocates the network resources on the basis of per-VDC fairness, which can achieve work conservation. In order to guarantee per-VDC fair allocation, a hierarchical max–min fairness algorithm is put forward in this paper. In order to ensure that the framework can be applied to non-congestion-free network core and achieve scalability, NXT-Freedom decouples the computation of per-VDC allocation from the execution of allocation, but it brings some CPU overheads resulting from bandwidth enforcement. We observe that there is no need to enforce the non-blocking virtual network. Leveraging this observation, we distinguish the virtual network type of VDC to eliminate part of the CPU overheads. The evaluation results of a prototype prove that NXT-Freedom can achieve the isolation of per-VDC performance, which also shows fast adaption to flow variation in cloud datacenter.

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Torres, Eliseu, Rafael Reale, Leobino Sampaio, and Joberto Martins. "A SDN/OpenFlow Framework for Dynamic Resource Allocation based on Bandwidth Allocation Model." IEEE Latin America Transactions 18, no. 05 (2020): 853–60. http://dx.doi.org/10.1109/tla.2020.9082913.

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CELIK, ASLIHAN, STEVE NAHMIAS, and RHONDA RIGHTER. "BANDWIDTH ALLOCATION IN A WIRELESS BROADCAST SYSTEM." International Journal of Information Technology & Decision Making 02, no. 04 (2003): 629–40. http://dx.doi.org/10.1142/s0219622003000847.

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We develop a model for broadcasting data to wireless appliances. Any data item may either be "pushed", or broadcast without waiting for requests for the item, or it may be "pulled", or broadcast in response to a request. Pushing items is cheaper than handling the individual requests, but if pushed items are not wanted, the bandwidth for broadcasting them is wasted. We determine the optimal allocation of bandwidth between pushed and pulled items.

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Gökhan, Çetin, and Sami Fadali M. "Optimal resource allocation in networked control systems using viterbi algorithm." Bulletin of Electrical Engineering and Informatics 10, no. 3 (2021): pp. 1524~1535. https://doi.org/10.11591/eei.v10i3.3022.

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This paper presents an optimal bandwidth allocation method for a networked control system (NCS) which includes time-driven sensor, event-driven controller and random channels. A hidden markov model (HMM) with a discretized state space is formulated for the random traffic to predict the network states using a suitable data window. Network bandwidth is allocated based on the predicted traffic state subject to bounds on the deterministic traffic that guarantee acceptable NCS performance and do not exceed hardware limitations. Bandwidth allocation uses 𝑙1 minimization of unmet bandwidth demand. A stability condition is derived for a variable but bounded sampling period interval. Computer simulation results show the effect of varying the number of discrete states for the HMM and the window width on bandwidth allocation. The results compare favorably with a published approach based on fuzzy logic.

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Li, Shiyong, Yue Zhang, and Wei Sun. "Optimal Resource Allocation Model and Algorithm for Elastic Enterprise Applications Migration to the Cloud." Mathematics 7, no. 10 (2019): 909. http://dx.doi.org/10.3390/math7100909.

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Cloud computing has been widely used in various industries in recent years. However, when migrating enterprise applications into the cloud, enterprise users face a problem with minimizing migration time and cloud resource providers face a dilemma of resource allocation problem, with the objective of maximizing the migration utility of enterprise users while minimizing the cost of cloud resource providers. In order to achieve them, this paper considered cloud migration objectives including cloud migration time, cloud migration utility, and cloud data center cost, and proposed a resource allocation model for enterprise applications migration into the cloud. The model is divided into two stages: the bandwidth allocation for enterprise applications migration to the cloud and the physical resource allocation of cloud resource providers for enterprise applications deployment into the cloud. In the first stage, we aim to minimize the cloud migration time for enterprise applications, and propose a scheme of bandwidth allocation for each component of applications. In the second stage, we present the resource allocation of cloud resource providers and propose a gradient-based algorithm which can achieve optimal resource allocation. Finally, we give some numerical simulation results to illustrate the performance of the proposed algorithm.

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R.Kennady, Et al. "Increased Task Execution with a Bandwidth-Aware Hadoop Scheduling Approach." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 2 (2023): 189–93. http://dx.doi.org/10.17762/ijritcc.v11i2.9830.

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This research presents a novel bandwidth-aware Hadoop scheduling method that addresses the challenge of task scheduling in Hadoop clusters while considering the real-time network conditions. The proposed method involves the establishment of a job time completion model and a mathematical model for a Hadoop scheduling system. Furthermore, it transforms the Hadoop task scheduling problem into an optimization problem to find the task scheduling method that minimizes job completion time. By leveraging Software-Defined Networking (SDN) capabilities, a time slot-based network bandwidth allocation mechanism is introduced to allocate bandwidth fairly across network links. The proposed method also takes into account task locality and network bandwidth availability when allocating computational nodes for individual tasks. Through this approach, the limitations of existing methods, which fail to simultaneously consider global task scheduling and actual network bandwidth availability, are overcome. Experimental evaluations demonstrate the effectiveness of the proposed method in enhancing the performance of Hadoop task scheduling.

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Huang, Wuwei, Yang Yang, Mingzhe Chen, Chuanhong Liu, Chunyan Feng, and H. Vincent Poor. "Wireless Network Optimization for Federated Learning with Model Compression in Hybrid VLC/RF Systems." Entropy 23, no. 11 (2021): 1413. http://dx.doi.org/10.3390/e23111413.

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In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and then transmits its ML parameters to a base station (BS) which aggregates the ML parameters to obtain a global ML model and transmits it to each user. Due to limited radio frequency (RF) resources, the number of users that participate in FL is restricted. Meanwhile, each user uploading and downloading the FL parameters may increase communication costs thus reducing the number of participating users. To this end, we propose to introduce visible light communication (VLC) as a supplement to RF and use compression methods to reduce the resources needed to transmit FL parameters over wireless links so as to further improve the communication efficiency and simultaneously optimize wireless network through user selection and resource allocation. This user selection and bandwidth allocation problem is formulated as an optimization problem whose goal is to minimize the training loss of FL. We first use a model compression method to reduce the size of FL model parameters that are transmitted over wireless links. Then, the optimization problem is separated into two subproblems. The first subproblem is a user selection problem with a given bandwidth allocation, which is solved by a traversal algorithm. The second subproblem is a bandwidth allocation problem with a given user selection, which is solved by a numerical method. The ultimate user selection and bandwidth allocation are obtained by iteratively compressing the model and solving these two subproblems. Simulation results show that the proposed FL algorithm can improve the accuracy of object recognition by up to 16.7% and improve the number of selected users by up to 68.7%, compared to a conventional FL algorithm using only RF.

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KIM, Sungwook. "An Online Bandwidth Allocation Scheme Based on Mechanism Design Model." IEICE Transactions on Communications E96.B, no. 1 (2013): 321–24. http://dx.doi.org/10.1587/transcom.e96.b.321.

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Lim, Wansu, Pandelis Kourtessis, John M. Senior, et al. "Dynamic Bandwidth Allocation for OFDMA-PONs Using Hidden Markov Model." IEEE Access 5 (2017): 21016–19. http://dx.doi.org/10.1109/access.2017.2657549.

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Luss, Hanan. "An Equitable Bandwidth Allocation Model for Video-on-Demand Networks." Networks and Spatial Economics 8, no. 1 (2007): 23–41. http://dx.doi.org/10.1007/s11067-007-9041-8.

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Sadon, S. K., N. M. Din, M. H. Al-Mansoori, et al. "Dynamic hierarchical bandwidth allocation using Russian Doll Model in EPON." Computers & Electrical Engineering 38, no. 6 (2012): 1480–89. http://dx.doi.org/10.1016/j.compeleceng.2012.05.002.

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Yan, Yonghe, Adel El-Atawy, and Ehab Al-Shaer. "A game-theoretic model for capacity-constrained fair bandwidth allocation." International Journal of Network Management 18, no. 6 (2008): 485–504. http://dx.doi.org/10.1002/nem.709.

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Jian Ming, Zhang, Wang YI, Xie Ze Ming, Tang Shi Yi, and Ou Hao Yuan. "Rate Allocation for Wireless Multimedia Sensor Networks Using Pricing Mechanism." Journal of Sensors 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/738565.

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A bandwidth allocation algorithm for wireless multimedia sensor networks is proposed in this paper. On the premise ofInitialallocation algorithm based on distortion and congestion model to provide an efficient system performance, the allocation algorithm based on pricing mechanism we proposed balances the real-time requirement of different users by adjusting the bandwidth price in each network and each slot. Simulation results show that the proposed algorithm balances the bandwidth ratio of different users according to the video complexity, and it can provide a good system performance guaranteeing the fairness among the users.

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Oluwatobi, Akinmerese, Awodele Oludele, Makinwa Kofi, Kuyoro Shade, and Adedeji Folasade. "A Study of Network Optimization Models for High-Performance Networks." International Journal of Innovative Science and Research Technology 8, no. 5 (2023): 2664–70. https://doi.org/10.5281/zenodo.8021560.

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An important feature of a bandwidth optimization system is the adequate provision of internet services with high data rates and wide coverage. Low bandwidth causes poor internet speed, network downtime, constant network traffic congestion and network unavailability during peak and off-peak periods, to mention a few. Existing research on bandwidth optimization focused on bandwidth allocation in creating different channels and traffic isolation to Guarantee good Quality of Service (QoS). Despite several optimization techniques and bandwidth allocation algorithms of existing researchers, there is still reduced connectivity by which internet users are grossly affected in spite of increased energy cost of network devices and other infrastructure. One of the serious issues of optimization techniques is that of the problem of mixed-integer linear programming. Therefore, this article gives a brief overview of a list of bandwidth optimization models deployed through previous researchers, stating the optimal algorithms that work with each of the models while formulating a new bandwidth optimization model that solves the problem of mixed-integer linear programming technique that was the approach adopted from existing works necessary for wireless networks.

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Le, Van Hoa, and Viet Minh Nhat Vo. "A Combined Delay-Throughput Fairness Model for Optical Burst Switched Networks." Journal of Information and Communication Technology 22, no. 2 (2023): 183–205. http://dx.doi.org/10.32890/jict2023.22.2.2.

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Fairness is an important feature of communication networks. It is the distribution, allocation, and provision of approximately equal orequal performance parameters, such as throughput, bandwidth, loss rate, and delay. In an optical burst switched (OBS) network, fairness is considered in three aspects: distance, throughput, and delay. Studies on these three types of fairness have been conducted; however, they have usually been considered in isolation. These fairness types should be considered together to improve the communication performance of the entire OBS network. This paper proposes a combined delay-throughput fairness model, where burst assembly and bandwidth allocation are improved to achieve both delay fairness and throughput fairness at ingress OBS nodes. The delay fairness and throughput fairness indices are recommended as metrics for adjusting the assembly queue length and allocated bandwidth for priority flows. The simulation results showed that delay and throughput fairness could be achieved simultaneously, improving the overall communication performance of the entire OBS network.

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Pałka, Piotr, and Eugeniusz Toczyłowski. "Pricing Rules Comparison in the Context of Bandwidth Trade." Journal of Telecommunications and Information Technology, no. 2 (June 27, 2023): 61–66. http://dx.doi.org/10.26636/jtit.2010.2.1073.

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In this paper we compare two pricing rules in the context of bandwidth trade. Allocation and pricing rules, together with a set of signals received from independent agents, constitute a market mechanism. In the paper we analyze two pricing rules: well known Vickrey-Clarke-Groves rule (VCG) and the parametric pricing rule (PPR).We apply these pricing rules to the allocation rule specified by the balancing communication bandwidth trade model (BCBT).

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Chao, Wang, Zhang Dalong, and Ran Xiaomin. "Regional Load Balancing Circuitous Bandwidth Allocation Method Based on Dynamic Auction Mechanism." MATEC Web of Conferences 176 (2018): 01020. http://dx.doi.org/10.1051/matecconf/201817601020.

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Aiming at the problem of link congestion caused by the shortage of network bandwidth resources at the user end, this paper first proposes a regional load balancing idea. Then, for the problem of bandwidth resource allocation in regional load balancing, a bandwidth allocation model is established and a dynamic auction algorithm is proposed. The algorithm calculates the link quality and stability by constructing a link model, and introduces the auction bandwidth to the auctioneer's incentive degree to obtain the auction bidding function. The simulation results show that the algorithm can effectively improve the user's network status, reduce the service response delay, increase the throughput, and at the same time can effectively prevent the auction user's false bidding behavior, so that the auction quote quickly converges to the maximum quote, reduces the number of auctions, and reduces Communication overhead.

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Kołtyś, Kamil, Piotr Pałka, Eugeniusz Toczyłowski, and Izabela Żółtowska. "Bandwidth Trading: A Comparison of the Combinatorial and Multicommodity Approach." Journal of Telecommunications and Information Technology, no. 2 (June 27, 2023): 67–72. http://dx.doi.org/10.26636/jtit.2010.2.1074.

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Since the telecommunication market becomes more complex and dynamic, a strong need for a new, efficient and flexible bandwidth trading mechanisms appears. We believe that good mechanisms, that allow effective and fair allocation of bandwidth between market participants will help to develop the real competitive bandwidth market. In this paper we compare two different double-sided bandwidth auction mechanisms, that seem to be well suited approaches for trading indivisible units of bandwidth: combinatorial auction c-SeBiDA and multicommodity mechanism BACBR-I. The c-SeBiDA mechanism considers two types of commodities: inter-node links and paths consisting of particular links. Market participants may bid a single link, or a bundle of links, constituting a specific path. The BACBR-I mechanism is a multicommodity exchange model, that allows bidders to place buy offers not only for individual or bundled links, but rather for end-to-end connections. Therefore, it is the decision model that allocates the most efficient links to connections. We run a large set of experiments to test the allocation and computational efficiency obtained under both approaches.

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Horng, Gwo-Jiun, Chi-Hsuan Wang, and Chih-Lun Chou. "Adaptive Broadcasting Mechanism for Bandwidth Allocation in Mobile Services." Scientific World Journal 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/735457.

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This paper proposes a tree-based adaptive broadcasting (TAB) algorithm for data dissemination to improve data access efficiency. The proposed TAB algorithm first constructs a broadcast tree to determine the broadcast frequency of each data and splits the broadcast tree into some broadcast wood to generate the broadcast program. In addition, this paper develops an analytical model to derive the mean access latency of the generated broadcast program. In light of the derived results, both the index channel’s bandwidth and the data channel’s bandwidth can be optimally allocated to maximize bandwidth utilization. This paper presents experiments to help evaluate the effectiveness of the proposed strategy. From the experimental results, it can be seen that the proposed mechanism is feasible in practice.

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Liu, Yazhi, Dongyu Wei, Chunyang Zhang, and Wei Li. "Distributed Bandwidth Allocation Strategy for QoE Fairness of Multiple Video Streams in Bottleneck Links." Future Internet 14, no. 5 (2022): 152. http://dx.doi.org/10.3390/fi14050152.

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In QoE fairness optimization of multiple video streams, a distributed video stream fairness scheduling strategy based on federated deep reinforcement learning is designed to address the problem of low bandwidth utilization due to unfair bandwidth allocation and the problematic convergence of distributed algorithms in cooperative control of multiple video streams. The proposed strategy predicts a reasonable bandwidth allocation weight for the current video stream according to its player state and the global characteristics provided by the server. Then the congestion control protocol allocates the proportion of available bandwidth, matching its bandwidth allocation weight to each video stream in the bottleneck link. The strategy trains a local predictive model on each client and periodically performs federated aggregation to generate the optimal global scheme. In addition, the proposed strategy constructs global parameters containing information about the overall state of the video system to improve the performance of the distributed scheduling algorithm. The experimental results show that the introduction of global parameters can improve the algorithm’s QoE fairness and overall QoE efficiency by 10% and 8%, respectively. The QoE fairness and overall QoE efficiency are improved by 8% and 7%, respectively, compared with the latest scheme.

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Lannoo, Bart, Lieven Verslegers, Didier Colle, Mario Pickavet, Maurice Gagnaire, and Piet Demeester. "Analytical model for the IPACT dynamic bandwidth allocation algorithm for EPONs." Journal of Optical Networking 6, no. 6 (2007): 677. http://dx.doi.org/10.1364/jon.6.000677.

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Sheu, Tsang-Ling, and Guan-Ying Pao. "A bandwidth allocation model for a two-pass RSVP setup mechanism." Computer Communications 26, no. 14 (2003): 1662–72. http://dx.doi.org/10.1016/s0140-3664(03)00118-x.

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Cao, Jiashen, Rathijit Sen, Matteo Interlandi, Joy Arulraj, and Hyesoon Kim. "GPU Database Systems Characterization and Optimization." Proceedings of the VLDB Endowment 17, no. 3 (2023): 441–54. http://dx.doi.org/10.14778/3632093.3632107.

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GPUs offer massive parallelism and high-bandwidth memory access, making them an attractive option for accelerating data analytics in database systems. However, while modern GPUs possess more resources than ever before (e.g., higher DRAM bandwidth), efficient system implementations and judicious resource allocations for query processing are still necessary for optimal performance. Database systems can save GPU runtime costs through just-enough resource allocation or improve query throughput with concurrent query processing by leveraging new GPU resource-allocation capabilities, such as Multi-Instance GPU (MIG). In this paper, we do a cross-stack performance and resource-utilization analysis of four GPU database systems, including Crystal (the state-of-the-art GPU database, performance-wise) and TQP (the latest entry in the GPU database space). We evaluate the bottlenecks of each system through an in-depth microarchitectural study and identify resource underutilization by leveraging the classic roofline model. Based on the insights gained from our investigation, we propose optimizations for both system implementation and resource allocation, using which we are able to achieve 1.9x lower latency for single-query execution and up to 6.5x throughput improvement for concurrent query execution.

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Abubakar Ibrahim, Adamu, Sanjir Inam Salsabil, and Ibrahim A. Lawal. "Effective Utilization of An Unused Bandwidth in IEEE 802.16 Network." Journal of Telecommunication, Electronic and Computer Engineering (JTEC) 14, no. 2 (2022): 15–22. http://dx.doi.org/10.54554/jtec.2022.14.02.003.

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A large percentage of available bandwidth in IEEE 802.16 networks can be utilised by using previous unused bandwidth. This is a common problem that occurs inside IEEE 802.16 networks, and it manifests itself when a subscriber station in an IEEE 802.16 network's Quality of Service (QOS) assured services is unable to predict how much data is being held back as unused bandwidth. As a direct consequence of this fact, the ongoing research has proposed simulating the process by which the remainder of the reserved bandwidth that is not being used will be recycled in order to enhance the Quality of Service and preserve the existing bandwidth reservation. Therefore, it was conceived that bandwidth might be reserved in the subscriber station separately from the bandwidth that is used for the downlink and the uplink of data transmission. This would prevent wasting the bandwidth. Through the utilization of an appropriate scheduling strategy associated with Round Robin, a simulation of an allocation of unoccupied bandwidth was carried out. The simulation findings reveal that an optimised bandwidth can ensure that the model can recycle 50–60 percent of the average amount of idle bandwidth. This is achieved through the allocation of unused bandwidth scheduling techniques. The findings of this research have demonstrated that it is possible to estimate the amount of data that is set aside as unused bandwidth and reuse it.

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Hu, Yi Hong, Guo Chu Shou, Zong Jue Qian, and Hao Xing Shen. "Research on Converged Access Network of WDM-PON and WiMAX." Applied Mechanics and Materials 58-60 (June 2011): 1583–89. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1583.

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Fixed Mobile Convergence (FMC) provides a solution of the converged access network for wired and wireless network. PON and WiMAX are the typical representatives in fiber access network and broadband wireless access network, of which the convergence has great research value. The converged network of PON and WiMAX has the advantage of high-bandwidth, which can provide various kinds of broadband access services and has features of low cost and simple and flexible. There are a variety of system forms for PON technology, one of them with unique advantages is WDM-PON system. In WDM-PON systems, each service has exclusive transmission bandwidth, which makes the converged network of WDM-PON and WiMAX has much more advantages than any other PON network. This paper proposes a converged network model of WDM-PON and WiMAX, and focuses on the analysis of dynamic bandwidth allocation algorithm applicable to the converged network model; then does some simulation of this dynamic bandwidth allocation algorithm, proves that the algorithm has a good delay effect in overload conditions, and analyses the bandwidth rate taken by traffic flow of different service levels under different network load situations.

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Mudiar, Priyanko Raj, Kandarpa Kumar Sarma, and Nikos Mastorakis. "Adaptively Equalized Bandwidth Optimization Model using SCADA-DWWAN based Neural Network." WSEAS TRANSACTIONS ON ELECTRONICS 13 (September 19, 2022): 107–14. http://dx.doi.org/10.37394/232017.2022.13.14.

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Artificial training and learning algorithms, enhanced with semi-supervised or self-supervised feature extraction capacities, employ adaptive decision optimization models. These are often favored over complex deep learning algorithms for achieving better controllability and ease of observation, lower complexity in simulating, building or designing and virtual prototyping of automatic network resource management (ANRM) standards. An Adaptive Linear Neuron type Artificial Neural Network (ADALINE-ANN) which is based on multi-tapered machine learning approach has been simulated in a virtual Supervisory Control and Data Acquisition (SCADA) framework integrated with a Distributed Control System (SCADA/DCS-Net). The system has been virtually simulated considering an adaptively equalized learning and decision approach which utilizes Markov Trained-Steepest Gradient Descent (HMM-SGD) based machine learning model employing Kalman optimization. Affinity clustering is employed for spectrum sensing by extracting the Constellation Nyquist Bands from an M-Quadrature Amplitude Modulation (QAM) orthogonal signal undergoing AWGN and Rayleigh fading as well as co-channel interference (CCI), and ensemble analysis using Channel State-Space plots are used for optimal spectrum allocation in an Adaptive Orthogonal Frequency Division Multiple Access (Adaptive-OFDMA) layout. It has been done by implementing an adaptively equalized Automatic Repeat Request (ARQ) pipelining model which utilizes minimum least square error (MLSE) minimization model. The objective is to improve the bandwidth allocation and usage ensuring most minimum spectrum wastage or loss. Successive Interference Cancellation (SIC) has been implemented to minimize static buffer and interference loss. Thus, spectrum loss due to latency and jitter which occurs from bandwidth congestion is minimized by improving the network resource tracking and allocation. It results in improved and stable bandwidth equalization.

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Stańczuk, Wojciech, Józef Lubacz, and Eugeniusz Toczyłowski. "Trading Links and Paths on a Communication Bandwidth Market." JUCS - Journal of Universal Computer Science 14, no. (5) (2008): 642–52. https://doi.org/10.3217/jucs-014-05-0642.

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This paper presents a novel market model for balancing communication bandwidth trade. The distinguishing characteristic of the model is that it assumes that market players can place buy offers not only for isolated network resources (inter-node links), but also for end-to-end network paths of predefined capacity. It also enables effective balancing of sell and buy offers for network resources in such a way which maximizes the global economic welfare. From a formal point of view, the model produces a linear programming problem for clearing a multi-commodity market. Three simple examples are used to discuss and illustrate the proposed model.

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Bambos, Nicholas, and George Michailidis. "Queueing and scheduling in random environments." Advances in Applied Probability 36, no. 1 (2004): 293–317. http://dx.doi.org/10.1239/aap/1077134474.

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We consider a processing system, composed of several parallel queues and a processor, which operates in a time-varying environment that fluctuates between various states or modes. The service rate at each queue depends on the processor bandwidth allocated to it, as well as the environment mode. Each queue is driven by a job traffic flow, which may also depend on the environment mode. Dynamic processor scheduling policies are investigated for maximizing the system throughput, by adapting to queue backlogs and the environment mode. We show that allocating the processor bandwidth to the queues, so as to maximize the projection of the service rate vector onto a linear function of the workload vector, can keep the system stable under the maximum possible traffic load. The analysis of the system dynamics is first done under very general assumptions, addressing rate stability and flow conservation on individual traffic and environment evolution traces. The connection with stochastic stability is later discussed for stationary and ergodic traffic and environment processes. Various extensions to feed-forward networks of such nodes, the multi-processor case, etc., are also discussed. The approach advances the methodology of trace-based modelling of queueing structures. Applications of the model include bandwidth allocation in wireless channels with fluctuating interference and allocation of switching bandwidth to traffic flows in communication networks with fluctuating congestion levels.

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Bambos, Nicholas, and George Michailidis. "Queueing and scheduling in random environments." Advances in Applied Probability 36, no. 01 (2004): 293–317. http://dx.doi.org/10.1017/s0001867800012970.

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We consider a processing system, composed of several parallel queues and a processor, which operates in a time-varying environment that fluctuates between various states or modes. The service rate at each queue depends on the processor bandwidth allocated to it, as well as the environment mode. Each queue is driven by a job traffic flow, which may also depend on the environment mode. Dynamic processor scheduling policies are investigated for maximizing the system throughput, by adapting to queue backlogs and the environment mode. We show that allocating the processor bandwidth to the queues, so as to maximize the projection of the service rate vector onto a linear function of the workload vector, can keep the system stable under the maximum possible traffic load. The analysis of the system dynamics is first done under very general assumptions, addressing rate stability and flow conservation on individual traffic and environment evolution traces. The connection with stochastic stability is later discussed for stationary and ergodic traffic and environment processes. Various extensions to feed-forward networks of such nodes, the multi-processor case, etc., are also discussed. The approach advances the methodology of trace-based modelling of queueing structures. Applications of the model include bandwidth allocation in wireless channels with fluctuating interference and allocation of switching bandwidth to traffic flows in communication networks with fluctuating congestion levels.

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Yu, Liangkun, Xiang Sun, Rana Albelaihi, Chaeeun Park, and Sihua Shao. "Dynamic Client Clustering, Bandwidth Allocation, and Workload Optimization for Semi-Synchronous Federated Learning." Electronics 13, no. 23 (2024): 4585. http://dx.doi.org/10.3390/electronics13234585.

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Federated Learning (FL) revolutionizes collaborative machine learning among Internet of Things (IoT) devices by enabling them to train models collectively while preserving data privacy. FL algorithms fall into two primary categories: synchronous and asynchronous. While synchronous FL efficiently handles straggler devices, its convergence speed and model accuracy can be compromised. In contrast, asynchronous FL allows all devices to participate but incurs high communication overhead and potential model staleness. To overcome these limitations, the paper introduces a semi-synchronous FL framework that uses client tiering based on computing and communication latencies. Clients in different tiers upload their local models at distinct frequencies, striking a balance between straggler mitigation and communication costs. Building on this, the paper proposes the Dynamic client clustering, bandwidth allocation, and local training for semi-synchronous Federated learning (DecantFed) algorithm to dynamically optimize client clustering, bandwidth allocation, and local training workloads in order to maximize data sample processing rates in FL. DecantFed dynamically optimizes client clustering, bandwidth allocation, and local training workloads for maximizing data processing rates in FL. It also adapts client learning rates according to their tiers, thus addressing the model staleness issue. Extensive simulations using benchmark datasets like MNIST and CIFAR-10, under both IID and non-IID scenarios, demonstrate DecantFed’s superior performance. It outperforms FedAvg and FedProx in convergence speed and delivers at least a 28% improvement in model accuracy, compared to FedProx.

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Xiong, Gang, and Jincheng Guo. "Contribution-Based Resource Allocation for Effective Federated Learning in UAV-Assisted Edge Networks." Sensors 24, no. 20 (2024): 6711. http://dx.doi.org/10.3390/s24206711.

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This paper considers UAVs as edge computing nodes and investigates a novel network resource allocation method for federated learning within a three-layer wireless network architecture containing cloud, edges (UAVs), and clients. To address the issue of fair bandwidth resource allocation among clients participating in federated learning, a contribution calculation strategy based on the Shapley value (SV) used as the weight for model aggregation is proposed. On this basis, a client selection and wireless resource allocation method based on model contribution is further designed. By reducing the training and aggregation frequency of the low-contribution clients during the asynchronous aggregation phase, the limited bandwidth resources are allocated to high-contribution clients, thus improving the convergence speed and accuracy of the global model. Simulation experiments demonstrate that the proposed method can significantly reduce the system delay and total energy consumption with gains between 15% and 50% while also improving the final accuracy of the global model by 0.3% and 2% on both short-term and long-term perspectives, respectively.

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Mrs., K.S.Saraswathi Devi. "Federated Learning-Based Resource Allocation for Cloud-Edge Computing." IJAPR Journal UGC Indexed & Care Listed 7, no. 1 (2022): 120–25. https://doi.org/10.5281/zenodo.8311909.

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<strong>Cloud-edge computing is a promising paradigm that can address the challenges of latency, bandwidth, and privacy in cloud computing. However, the edge nodes have limited resources, so it is important to allocate resources efficiently. This paper proposes a federated learning-based resource allocation framework for cloud-edge computing. The proposed framework consists of three main components: a federated learning algorithm, a resource allocation algorithm, and a secure communication protocol. The federated learning algorithm is responsible for training a machine learning model without sharing the data with a central server. The resource allocation algorithm is responsible for allocating resources to the edge nodes efficiently. The secure communication protocol is used to protect the privacy of the data during the federated learning process. The proposed framework is evaluated using simulations. The results show that the proposed framework can achieve better performance than traditional resource allocation algorithms.</strong>

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Saravanan, G., and N. Yuvaraj. "Cloud resource optimization based on poisson linear deep gradient learning for mobile cloud computing." Journal of Intelligent & Fuzzy Systems 40, no. 1 (2021): 787–97. http://dx.doi.org/10.3233/jifs-200799.

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Mobile Cloud Computing (MCC) addresses the drawbacks of Mobile Users (MU) where the in-depth evaluation of mobile applications is transferred to a centralized cloud via a wireless medium to reduce load, therefore optimizing resources. In this paper, we consider the resource (i.e., bandwidth and memory) allocation problem to support mobile applications in a MCC environment. In such an environment, Mobile Cloud Service Providers (MCSPs) form a coalition to create a resource pool to share their resources with the Mobile Cloud Users. To enhance the welfare of the MCSPs, a method for optimal resource allocation to the mobile users called, Poisson Linear Deep Resource Allocation (PL-DRA) is designed. For resource allocation between mobile users, we formulate and solve optimization models to acquire an optimal number of application instances while meeting the requirements of mobile users. For optimal application instances, the Poisson Distributed Queuing model is designed. The distributed resource management is designed as a multithreaded model where parallel computation is provided. Next, a Linear Gradient Deep Resource Allocation (LG-DRA) model is designed based on the constraints, bandwidth, and memory to allocate mobile user instances. This model combines the advantage of both decision making (i.e. Linear Programming) and perception ability (i.e. Deep Resource Allocation). Besides, a Stochastic Gradient Learning is utilized to address mobile user scalability. The simulation results show that the Poisson queuing strategy based on the improved Deep Learning algorithm has better performance in response time, response overhead, and energy consumption than other algorithms.

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Akanza Konan Ricky, NDRI, GOORE Bi Tra, GNIMASSOUN Jean Edgard, and TIECOURA Yve. "A DYNAMIC BANDWIDTH ALLOCATION SYSTEM IN XG-PONS BASED ON STATISTICAL ESTIMATION OF BUFFER INPUTS AND OUTPUTS." International Journal of Advanced Research 10, no. 10 (2022): 544–52. http://dx.doi.org/10.21474/ijar01/15522.

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The exchanges in the New Generation Optical Access Network (NG-PON), are mainly based on the bandwidth request by the Optical Network Units (ONU) and its granting by the Optical Line Termination (OLT). This process (request-grant) not being synchronized, will create in the ONU buffer a long delay and the loss of sensitive packets. Many authors, from signaling to prediction, have proposed models to control these parameters, however only those based on prediction reduce the delay in the queues but also waste bandwidth by over- or under-allocating. Our goal is to propose a model that accurately allocates bandwidth to ONU while minimizing their queue delay. As such, we propose a Statistical Queue Estimation model based on ONU Buffer Inputs and Outputs (ESTEST). In its execution ESTEST memorizes the ONU bandwidth requirements and the bandwidth used to transmit their data in the ith upstream frames. With these two parameters (requirements and bandwidth used), our algorithm computes the traffic intensity (ðœŒ) and predicts the queue size of the ONU. On 100 observations we compute the mean and standard deviation of the ðœŒth values and with the reduced centered normal distribution, find the confidence interval of size estimation.

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Kołtyś, Kamil, Krzysztof Pieńkosz, and Eugeniusz Toczyłowski. "Auction Models Supporting End-to-End Connection Trading." Journal of Telecommunications and Information Technology, no. 2 (June 30, 2012): 55–62. http://dx.doi.org/10.26636/jtit.2012.2.1265.

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The paper concerns bandwidth allocation problem on the telecommunication market where there are many sellers and buyers. Sellers offer the bandwidth of telecommunication links. Buyers are interested in the purchase of the bandwidth of several links that makes up an end-to-end connection between two nodes of telecommunication network. We analyze three auction models supporting such a bandwidth exchange: NSP (network second price), BCBT (model for balancing communication bandwidth trading) and BCBT-CG which is a modification of BCBT that applies column generation technique. All of these models concern divisible network resources, treat bandwidth of telecommunication links as an elementary commodity offered for sale, and allow for purchasing bandwidth along multiple paths joining two telecommunication nodes. All of them also aim at maximizing the social welfare. Considered auction models have been compared in the respect of economic and computational efficiency. Experimental studies have been performed on several test instances based on the SNDlib library data sets.

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Journal articles on the topic 'Bandwidth Allocation Model'

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