Bandwidth Reservation Research Articles

Optimizing Bandwidth Reservation Decision Time in Vehicular Networks using Batched LSTM

Optimizing Bandwidth Reservation Decision Time in Vehicular Networks using Batched LSTM

Blockchain-Empowered Resource Trading for Optimizing Bandwidth Reservation in Vehicular Networks

Blockchain-Empowered Resource Trading for Optimizing Bandwidth Reservation in Vehicular Networks

Diktyo: Network-Aware Scheduling in Container-Based Clouds

Containers have revolutionized application deployment and life-cycle management in current cloud platforms. Applications have evolved from single monoliths to complex graphs of loosely-coupled microservices. However, the efficient allocation of microservice-based applications is challenging due to their complex inter-dependencies. Further, recent applications are becoming even more delay-sensitive, demanding lower latency between dependent microservices. Scheduling policies in popular container orchestration platforms mainly aim to increase the resource efficiency of the infrastructure, insufficient for latency-sensitive applications. Application domains such as the Internet of Things and multi-tier web services would benefit from network-aware policies that consider network latency and bandwidth in the scheduling process. Previous works have studied network-aware scheduling via theoretical formulations or heuristic-based methods evaluated via simulations or small testbeds, making their full applicability in popular platforms difficult. This paper proposes a novel network-aware framework for the popular Kubernetes (K8s) platform named Diktyo that determines the placement of dependent microservices in long-running applications focused on reducing the application’s end-to-end latency and guaranteeing bandwidth reservations. Simulations show that Diktyo can significantly reduce the network latency for various applications across different infrastructure topologies compared to default K8s scheduling plugins. Also, experiments in a K8s cluster with microservice benchmark applications show that Diktyo can increase database throughput by 22% and reduce application response time by 45%.

On multi-path bandwidth scheduling for multiple fixed-slot reservations in high-performance networks

Large-scale applications in various fields generate big data at a high speed, which needs to be transferred through High-Performance Networks (HPNs). Bandwidth scheduling in HPNs plays a pivotal role in providing Quality of Service (QoS) to such applications. In this paper, we formulate two bandwidth scheduling problems: (i) maximize the amount of bandwidths to be allocated for multiple fixed-slot bandwidth reservation requests (FBRRs), referred to as maxAB-MultF, and (ii) maximize the number of requests to be satisfied as well as the degree of user’s satisfaction for multiple prioritized fixed-slot bandwidth reservation requests (PFBRRs), referred to as maxNR-MultPF. We prove both of these problems to be NP-complete, and design two heuristic algorithms, namely, Maximal Reserved Bandwidth Resources (MaxRBR) and Dynamic Resource Occupation (DynRO), for them, respectively. For each problem, we also design two algorithms based on greedy strategy for performance comparison. Extensive simulation results illustrate that MaxRBR for maxAB-MultF improves Reserved Bandwidth Resource Ratio over two other algorithms in comparison by 18% and 15%, respectively, and DynRO for maxNR-MultPF improves over another two algorithms in comparison scheduling success ratio by 10% and 5%, respectively, and user satisfaction by 6.5% and 5.5%, respectively. Considering the rapid expansion of HPNs in both speed and scale, the proposed scheduling algorithms have great potentials to improve the network performance of big data applications that require these two types of services.

Optimizing multimedia communication in internet of thing network for improving quality of service

The internet of things (IoT) has revolutionized the way we interact with technology, with the proliferation of interconnected devices leading to an increase in the volume of data transmitted over the network. One of the key applications of IoT is in multimedia communication, where real-time audio and video data is transmitted over the network. However, the diverse nature of applications and the sheer volume of data in IoT networks can lead to network congestion, latency, and variable quality of service (QoS) at the internet side, resulting in a degradation of the overall QoS for multimedia traffic. In this paper, we propose a cross-layer multimedia optimization solution for multi-point to point IoT networks that incorporates service differentiation and bandwidth reservation techniques to improve the QoS of multimedia traffic. We evaluate the performance of our proposed solution using simulations and compare it with existing solutions. Our results show that our proposed solution can significantly improve the QoS of multimedia traffic in IoT networks, even during periods of high network congestion or variable QoS at the internet side.

Performance evaluation of a mobile hotspot supporting quasi‐random traffic

AbstractThe authors study and evaluate a mobility‐aware call admission control algorithm in a mobile hotspot. More specifically, a vehicle which has an access point of a fixed capacity and may alternate between stop and moving phases is considered. In the stop phase, the vehicle services new and handover calls. To prioritise handover calls a probabilistic bandwidth reservation policy is considered where a fraction of the capacity is reserved for handover calls. Based on this policy, new calls may enter the reservation space with a predefined probability. In addition, handover calls have the option to wait in a queue of finite size if there are no available resources at the time of their arrival. In the moving phase, the vehicle services only new calls under the classical complete sharing policy. In both phases, calls arrive in the system according to a quasi‐random process, require a single bandwidth unit for their acceptance in the system and have an exponentially distributed service time. To analytically determine the various performance measures, such as time congestion probabilities, call blocking probabilities and link utilisation, an accurate analytical method is presented based on three‐dimensional Markov chains.

Joint Channel Assignment and Bandwidth Reservation Using Improved FireFly Algorithm (IFA) in Wireless Mesh Networks (WMN)

Joint Channel Assignment and Bandwidth Reservation Using Improved FireFly Algorithm (IFA) in Wireless Mesh Networks (WMN)

Why and how edge cloud computing can address performance and economic sustainability issues for telco domestic networks

This paper analyzes some of the telecommunication companies' (telcos) domestic networks' main objectives and issues related to the application services Quality of Experience (QoE), i.e., "technical QoE," and the economic sustainability of the Very High Capacity (VHC) networks. Telco domestic networks and Over The Top (OTT) networks are the Internet segments connecting the end-user equipment to the servers/clouds that provide application services. With the advent of VHC networks, telcos afford difficulties in managing effectively and efficiently the application services and their business sustainability. This paper affords some issues related to traditional telcos' domestic network architectures and the approach to managing the application services' performance improvement. Some telcos started changing their architectures, although a massive transformation had not yet started in the industry. Traditionally, telcos focus on network services, i.e., the transport of IP packets. Performance improvement is obtained by QoS-based traffic management techniques, such as bandwidth reservation and packet prioritization. To manage application performance improvement, the use of layer 4 techniques and Edge Cloud Computing (ECC) is effective, as demonstrated by the multiyear experience of OTTs which already use these technologies. In telco domestic networks, layer 2 tunnels increase the complexity of deploying ECC. However, some vendors provide non-standard solutions to make the IP layer 3 user plane visible and to deploy ECC. ECC is the key factor for the transformation. It is a mini/micro-data center that distributes some applications and content closer to the end users. The distribution can provide a paradigm shift in a telco's business. In the paper, we first highlight the need for regulators to appreciate the need to encourage this industry transformation fully.

Adaptive Bandwidth Management Model for Wireless Mobile Ad-hoc Network

The quality of service (QoS) component in a mobile ad-hoc network has an active role in the current network scenario. In a dynamic mobile ad hoc network, ensuring optimum QoS with a scarce network resource is a significant challenge. To achieve QoS, it is essential to adopt some effective and efficient mechanisms. We have proposed an adaptive bandwidth manager model (ABMM) which uses a bandwidthsharing concept along with the flexible bandwidth reservation algorithm (FBRA) for an effective, quick and authentic data transfer. During real-time data transfer, to make communication effective, we make use of bandwidth-sharing network design problems and the concept of reserving bandwidth in high-performance networks. In our proposed model we are concentrating on the maximum utilization of resources, and using the scheduling concept to provide the minimum required bandwidth guarantee to QoS flows. Our goal is to reduce the delay in data transfer and enhance the throughput while properly utilizing the system resources. Our simulation result also shows that our model improves the network performance.

Federated Learning over Next-Generation Ethernet Passive Optical Networks

Federated Learning (FL) is a distributed machine learning type of processing that preserves the privacy of user data, sharing only the parameters of ML models with a common server. The processing of FL requires specific latency and bandwidth demands that must be fulfilled by the operation of the communication network. This paper introduces two Dynamic Wavelength and Bandwidth Allocation algorithms for TWDM-PONs: one based on bandwidth reservation and the other on statistical multiplexing for the Quality of Service provisioning for FL traffic over 50 Gb/s Ethernet Passive Optical Networks.

Minimum Bandwidth Reservation for CBS in TSN With Real-Time QoS Guarantees

Minimum Bandwidth Reservation for CBS in TSN With Real-Time QoS Guarantees

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

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

Optimized scheduling method in 6TSCH wireless networks

IEEE802.15.4e-TSCH is a mode exploited by the Internet of Things. Time Slotted Channel Hopping (TSCH) presents an upgrade to the IEEE 802.15.4 to build a Medium Access Control (MAC) for low power and loss network applications in IoT. This norm defines the concept of TSCH based on channel hopping and reservation of bandwidth to achieve energy efficiency, as well as consistent transmissions. Centralized approaches have been proposed for planning TSCH. They have succeeded in increasing network efficiency and reducing latency, but the scheduling length remains not reduced. However, distributed solutions appear to be more stable in the face of change, without creating a priori assumptions about the topology of the network or the amount of traffic to be transmitted. A distributed scheduling allowing neighboring nodes to decide on a coordination system operated by a minimal scheduling feature is currently proposed by the 6TiSCH working group. This scheduling allows sensor nodes to determine when data is to be sent or received. However, the details of scheduling time intervals are not specified by the TSCH-mode IEEE802.15.4e standard. In this work, we propose a distributed Optimized Minimum Scheduling Function (OMSF) that is based on the 802.15.4e standard TSCH mode. For this purpose, a distributed algorithm is being implemented to predict the scheduling requirements over the next slotframe, focused on the Poisson model and using a cluster tree topology. As a consequence, it will reduce the negotiation operations between the pairs of nodes in each cluster to decide on a schedule. This prediction allowed us to deduce the number of cells needed in the next slotframe. Clustering decreases, the overhead processing costs that produce the prediction model. So, an energy-efficient data collection model focused on clustering and prediction has been proposed. As a result, the energy consumption, traffic load, latency, and queue size in the network, have been reduced.

Performance Evaluation of Call Admission Control Schemes in 3GPP Long Term Evolution Networks

Radio resource management (RRM) techniques are employed for resource utilization in wireless broadband networks. One of the major RRM techniques that are aimed at controlling the admission and rejection of new or handoff calls/connections in a network is known as Call Admission Control (CAC). CAC accepts or rejects a connection request based on a certain pre-determined criterion(s). Performance Evaluation of some existing CAC schemes was presented in this paper. The schemes evaluated are; Adaptive Call Admission Control Scheme with Bandwidth reservation termed as (ACAC), QoS-Aware Call Admission Control Scheme termed as (QA-CAC) and Enhanced Adaptive Call Admission Control Scheme with bandwidth reservation termed (EA-CAC). Vienna LTE system level simulator was used for the simulation experiments conducted. After several experiments, the results show that the QA-CAC and EA-CAC schemes perform better in terms of increasing the throughput of real-time (RT) traffic while all the three schemes almost have the same performance in terms of admitting the non-real-time (NRT) traffic.

Effective Utilization of An Unused Bandwidth in IEEE 802.16 Network

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.

Extending MQTT with Real-Time Communication Services Based on SDN.

MQTT is one of the most popular application-layer protocols used in the scope of the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT), given its suitability for resource-constrained embedded systems. However, MQTT Quality-of-Service policies do not support timeliness requirements, which is common in IIoT. The literature reports several research works that address this limitation, but they are limited in scope (e.g., improvements in the broker’s internal operation, control of the publisher’s data rate, and path optimizations). Conversely, this paper presents a comprehensive architectural approach, proposing a set of extensions to the MQTT protocol that allow applications to explicitly specify real-time requirements and instantiate corresponding network reservations to enforce the desired temporal behavior. Such reservations are enforced via Software Defined Networking, specifically the OpenFlow protocol, but other protocols that allow bandwidth reservations, e.g., TSN, can also be used. This paper presents the proposed system architecture together with extensive emulation and implementation results that validate the feasibility of the approach, showing that time-sensitive MQTT traffic can be effectively segregated and prioritized to meet application-defined real-time requirements. Using several combinations of network topologies and load levels and comparing to the absence of the proposed real-time mechanisms, both average and worst-case latencies of the time-sensitive traffic decreased to approximately half, while for the normal traffic, they increased by approximately 10%.

Resource Allocation for Joint Communication and Localization Systems With MU-MIMO

Joint communication and localization is an attractive technique to simultaneously provide data transmission and localization services, and efficient resource allocation could bring a high data rate and high localization accuracy in limited resources, which is significant for multi-user conditions. In this paper, we concentrate on the joint multiple resource allocation to achieve a trade-off between the performance of the communication and localization process in the millimeter multi-user Multiple Input Multiple Output(MU-MIMO) system. We first develop a robust beam scheduling and user grouping approach using the mutual angle information and channel correlation coefficient to reduce the multi-user interference. Then, we formulate a multi-domain resource allocation problem, where the joint impact of beamforming, bandwidth reservation, and power control is considered. Furthermore, an efficient algorithm is proposed to iteratively perform the sub-carrier and power allocation until satisfying the data rate and localization error-bound constraints after decomposing the large-scale problem into two small-scale sub-problems by the difference of the convex function algorithm. Numerical results show that the proposed algorithm achieves a good trade-off between data rate and localization error and has better performance than other previously proposed algorithms in the literature.

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

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

5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0

Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.

Call Blocking Probabilities under a Probabilistic Bandwidth Reservation Policy in Mobile Hotspots

In this paper we study a mobility-aware call admission control algorithm in a mobile hotspot. To this end, a vehicle is considered which has an access point with a fixed capacity. The vehicle alternates between stop and moving phases. When the vehicle is in the stop phase, it services new and handover calls by prioritizing them via a probabilistic bandwidth reservation (BR) policy. Based on this policy, new handover calls may enter the reservation space with a predefined probability. When the vehicle is in the moving phase, it services new calls only. In that phase, two different policies are considered: (a) the classical complete sharing (CS) policy, where new calls are accepted in the system whenever there exists available bandwidth, and (b) the probabilistic BR policy. Depending on the selected policy in the moving phase, we propose the probabilistic BR loss model (if the CS policy is selected) and the generalized probabilistic BR loss model (if the probabilistic BR policy is selected). In both stop and moving phases, where the call arrival process is Poisson, calls require a single bandwidth unit in order to be accepted in the system, while the service time is exponentially distributed. To analytically determine call blocking probabilities and the system’s utilization, we propose efficient iterative algorithms based on two-dimensional Markov chains. The accuracy of the proposed algorithms is verified via simulation.