Enhance Bandwidth Utilization Research Articles

STAM-LSGRU: a spatiotemporal radar echo extrapolation algorithm with edge computing for short-term forecasting

With the advent of Mobile Edge Computing (MEC), shifting data processing from cloud centers to the network edge presents an advanced computational paradigm for addressing latency-sensitive applications. Specifically, in radar systems, the real-time processing and prediction of radar echo data pose significant challenges in dynamic and resource-constrained environments. MEC, by processing data near its source, not only significantly reduces communication latency and enhances bandwidth utilization but also diminishes the necessity of transmitting large volumes of data to the cloud, which is crucial for improving the timeliness and efficiency of radar data processing. To meet this demand, this paper proposes a model that integrates a spatiotemporal Attention Module (STAM) with a Long Short-Term Memory Gated Recurrent Unit (ST-ConvLSGRU) to enhance the accuracy of radar echo prediction while leveraging the advantages of MEC. STAM, by extending the spatiotemporal receptive field of the prediction units, effectively captures key inter-frame motion information, while optimizations to the convolutional structure and loss function further boost the model’s predictive performance. Experimental results demonstrate that our approach significantly improves the accuracy of short-term weather forecasting in a mobile edge computing environment, showcasing an efficient and practical solution for processing radar echo data under dynamic, resource-limited conditions.

Guaranteed cost control via dynamic output feedback for networked interval type-2 T–S fuzzy system with hybrid communication mechanism

This paper aims to investigate the guaranteed cost control via dynamic output feedback for nonlinear networked control systems (NCSs) with consideration of hybrid communication mechanism, data dropout and bounded disturbance. Interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy model is utilized to describe the nonlinear system with parameter uncertainties. To enhance bandwidth utilization and improve control performance, a hybrid communication mechanism involving both event-triggered mechanism (ETM) and time-triggered mechanism (TTM) is proposed. Two Bernoulli processes are invoked to describe the switching between two triggering mechanisms, and the data dropout phenomenon in communication network, respectively. The quadratic boundedness (QB) technique is employed to specify the closed-loop stability of a bounded disturbance networked system. The sufficient conditions for the stability of the system and the presence of a dynamic output feedback guaranteed cost controller are presented. In addition, the problem of controller design is converted to a convex optimization problem that can be tackled by linear matrix inequalities (LMIs) technique. At last, simulation experiment is carried out to explicate the availability and usefulness of the designed controller.

An Intelligent Data Fusion Technique for Improving the Data Transmission Rate in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are made up of multiple source-restricted wireless sensor nodes that gather, process, and transmit information. Existing research work proposed energy competence with trust as well as Quality of Service (QoS) multipath routing protocol for improving network lifetime and other QoS parameters, selection criteria for multipath. However, this protocol has some limitations, such as scalability, data redundancy, bandwidth utilization, and network traffic. The most important challenge lies in managing the voluminous data produced by the network’s sensors. As a result of this study, Intelligent Data Fusion Techniques (IDFTs) were presented, which can greatly minimize redundant data, decrease the quantity of transmitting data, broaden the network life cycle, enhance bandwidth utilization, and therefore, resolve the energy and bandwidth usage bottleneck. This paper proposes Improved Whale Optimization Algorithms (IWOAs) for intelligent data fusion where the amount of data collected from sensor sources is reduced and the information offered is enhanced by duplicate data, which also increases data dependability. IWOAs are used to combine the actual information from the cluster’s sensor nodes at the sink node, resulting in increased information and the ability to make local judgments about the particular events. The sink node transmits local decisions to base station on a regular basis that combines the local decisions and provides the ultimate judgment, easing the pressure on the base station to evaluate all of the data. As per the results obtained, the proposed intelligent data fusion method significantly increases the network’s robustness and accuracy.

Enhancing Bandwidth Utilization of IP Telephony Over IPv6 Networks

The demand for the telecommunication services, such as IP telephony, has increased dramatically during the COVID-19 pandemic lockdown. IP telephony should be enhanced to provide the expected quality. One of the issues that should be investigated in IP telephony is bandwidth utilization. IP telephony produces very small speech samples attached to a large packet header. The header of the IP telephony consumes a considerable share of the bandwidth allotted to the IP telephony. This wastes the network's bandwidth and influences the IP telephony quality. This paper proposes a mechanism (called Smallerize) that reduces the bandwidth consumed by both the speech sample and the header. This is achieved by assembling numerous IP telephony packets in one header and use the header's fields to carry the speech sample. Several metrics have been used to measure the achievement Smallerize mechanism. The number of calls has been increased by 245.1% compared to the typical mechanism. The bandwidth saving has also reached 68% with the G.28 codec. Therefore, Smallerize is a possible mechanism to enhance bandwidth utilization of the IP telephony.

A Firebug Optimal Cluster based Data Aggregation for Healthcare Application

Majority of Wireless Sensor Networks (WSNs) are made up of huge sensor nodes with minimum cost, processing, communication capability and limited sensing. Because sensor nodes have limited resources, it’s critical to enhance bandwidth utilization, network lifetime and minimize the data transmission. The term data aggregation defines the method of integrating the sensor data to minimize the data transmission. However, WSN-based healthcare applications face privacy, and security concerns. In this paper design of a Fire Bug Swarm Optimal Cluster-Based Data Aggregation (FSOCDA) in WSN has been presented which is a useful method for WSN to save energy and extend network lifetime. The efficient clustering is carried out using FSO, which is utilized to choose the CH from among various nodes in the cluster that serve as data aggregation nodes. By altering the network scale, the computational competence of the FSOCDA technique is compared to that of the non-aggregate approach. Further, the data aggregation method is helpful in healthcare applications in terms of data transferring from host hospital to other.

Hybrid-triggered interval type-2 fuzzy control for networked systems under attacks

In this paper, the security control problem is considered for nonlinear networked control systems under cyber attacks. The nonlinearities are described by interval type-2 fuzzy models. To enhance bandwidth utilization and improve network control performance, a hybrid-triggered scheme is proposed. The networked control systems contain parametric uncertainties and time delays and are subject to external disturbances and cyber attacks. A hybrid-triggered-based control method is established to ensure the robust stability and a prescribed performance of the resulting closed-loop systems against attacks. Numerical simulation and a practical example of the bolt-tightening tool are provided to illustrate the effectiveness of the new control design method.

End-to-End Service Delivery with QoS Guarantee in Software-Defined Networks

Software-Defined Network (SDN) is expected to have a significant impact on future networking. Although exciting progress has been made toward realizing SDN, application of this new networking paradigm in the future Internet to support end-to-end QoS provisioning faces some new challenges. The autonomous network domains coexisting in the Internet and the diverse user applications deployed upon the Internet call for a uniform Service Delivery Platform (SDP) that enables high-level network abstraction and inter-domain collaboration for end-to-end service provisioning. However, the currently available SDN technologies lack effective mechanisms for supporting such a platform. In this paper, we first present an SDP framework that applies the Network-as-a-Service (NaaS) principle to provide network abstraction and orchestration for end-to-end service provisioning in the SDN-based future Internet. Then we focus our study on two enabling technologies for such an SDP to achieve QoS guarantee; namely a network abstraction model and an end-to-end resource allocation scheme. Specifically, we propose a general model for abstracting the service capabilities offered by network domains and develop a technique for determining the required amounts of bandwidth in network domains for end-to-end service delivery with QoS guarantee. Both the analytical and numerical results obtained in this paper indicate that the NaaS-based SDP not only simplifies SDN service and resource management but also enhances bandwidth utilization for end-to-end QoS provisioning.

VMCD: A Virtual Multi-Channel Disk I/O Scheduling Method for Virtual Machines

In the era of cloud computing and big data, virtualization is gaining great popularity in storage systems. Since multiple guest virtual machines (DomUs) are running on a single physical device, disk I/O fairness among DomUs and aggregated throughput remain the challenges in virtualized environments. Although several methods have been developed for disk I/O performance virtualization among multiple DomUs, most of them suffer from one or more of the following drawbacks. (1) A fair scheduling mechanism is missing when requests converge together from multiple queues. (2) Existing methods rely on better performance of the underlying storage system such as solid state drive (SSD). (3) Throughput and latency are not considered simultaneously. To address these disadvantages, this paper presents a virtual multi-channel of disk I/O (VMCD) method that can be built on top of an ordinary storage utility, which mitigates the interference among multiple DomUs by using separated virtual channel (V-Channel) and an I/O request queue for each DomU. In our VMCD, several mechanisms are employed to enhance the I/O performance, including a credit allocation mechanism, a global monitoring strategy, and a virtual multi-channel fair scheduling algorithm. The proposed techniques are implemented on the Xen virtual disk and evaluated on Linux guest operating systems. Experiments results show that VMCD increases fairness by 70 percent approximately compared with CFQ and Anticipatory schedulers, by 30 percent approximately compared with Deadline scheduler; and enhances bandwidth utilization by 28 percent approximately compared with CFQ and Anticipatory schedulers, by 37 percent compared with Deadline in the case of three or more virtual DomUs running on the same physical host.

Protocol to Exploit Waiting Resources for UASNs.

The transmission speed of acoustic waves in water is much slower than that of radio waves in terrestrial wireless sensor networks. Thus, the propagation delay in underwater acoustic sensor networks (UASN) is much greater. Longer propagation delay leads to complicated communication and collision problems. To solve collision problems, some studies have proposed waiting mechanisms; however, long waiting mechanisms result in low bandwidth utilization. To improve throughput, this study proposes a slotted medium access control protocol to enhance bandwidth utilization in UASNs. The proposed mechanism increases communication by exploiting temporal and spatial resources that are typically idle in order to protect communication against interference. By reducing wait time, network performance and energy consumption can be improved. A performance evaluation demonstrates that when the data packets are large or sensor deployment is dense, the energy consumption of proposed protocol is less than that of existing protocols as well as the throughput is higher than that of existing protocols.

A Survey on TCP in VANET: Architecture, Issues

Vehicular communication is an important and emerging area of research in the field of vehicular technology. The improvement of programming and equipment in correspondence frameworks prompts the era of new systems. Many researches and projects have been conducted in this upcoming area. Many government projects have been implemented in the USA, Japan and the European Union. The principle goal of utilizing this new technology is to make an accident free environment. New architectures, protocols and implementations of vehicular ad-hoc network (VANET) have been made in recent years to provide Intelligent Transportation Services. This paper incorporates survey of overall examination chip away at different issue identified with TCP in VANET. The main issue is Congestion when congestion occur number of packets are drops, some packets are also lost. To overcome this problem congestion control algorithm is used when congestion occur this algorithm slow down the transmission rate. Additionally VANET has number of difficulties like technical, social and economical. To solve this issue numerous procedures to be utilized because of this it enhances bandwidth utilization and throughput.

Improving Hit Ratio and Byte Hit Ratio Using Combined Pre-Fetching and Web Caching

Combined caching and pre-fetching of web pages help to enhance bandwidth utilization, reduce access delay and also reduce the load on the server. Pre-fetching is the technique of fetching Web pages in advance that will be assumed to be needed or browsed in near future by the user and the caching process stores them in the memory. In the literature, number of works has been reported separately for caching and pre-fetching of Web pages. In this paper clustering based pre-fetching technique is combined with machine learning technique-SVM (Support Vector Machine)-LRU algorithm for Web proxy caching. With the help of real dataset it is demonstrated that the latter approach will be better than Clustering based pre-fetching technique with traditional caching policy like LRU in terms of bandwidth utilization and access latency.

Energy-efficient design for multi-granular optical transport networks with optical reach consideration

Energy consumption of the optical backbone is expected to contribute to a significant portion of the energy consumed by the telecommunication networks. As an enhanced bandwidth utilization and management extent of the optical Wavelength Division Multiplexing (WDM) technology, multi-granular switching concept has been shown to guarantee energy savings when compared to the traditional traffic grooming. However, Multi-Granular Optical Transport Network (MG-OTN) design and planning still calls for legitimate and self-contained design specifications. In this paper, we revisit the Routing and Multi-Granular Path Assignment (RMGPA) problem by having the objective of minimized power consumption and integrating the optical reach limitation of optical signals in the design and planning problem. The new problem is formulated as a Mixed Integer Linear Programming (MILP) model. For large scale design scenarios, we propose an efficient heuristic approach that is capable of solving the power minimization problem in feasible runtime. The heuristics is verified within 2% average approximation to the MILP solutions under small scale scenarios, and the numerical results of the design and planning problem heuristic show that significant power savings up to 55% in MG-OTNs can be achieved with the proper selection of the wavelength capacity, waveband size, number of wavebands per fiber, and the value of the optical reach. Furthermore, the proposed heuristic has been shown to guarantee high fairness among the nodes with respect to the power fairness index, which is at the order of 92–99% under various traffic scenarios.

A Cross-layer Loss Discrimination Scheme for DCCP over the Wireless Network

DCCP (Datagram Congestion Control Protocol) is a transport layer protocol that provides congestion control for unreliable data transmission. The congestion control mechanism embedded in DCCP adjusts the packet sending rate according to network condition. However, DCCP does not discriminate congestion losses and wireless link errors resulted from fading and thus it leads to unnecessary rate adjustment. In this paper, we proposed a mechanism to enhance bandwidth utilization of DCCP over wireless network. We employed a cross-layer loss discrimination scheme to distinguish congestion loss and fading loss. The cross-layer based mechanism detects frame loss in the data link layer in real-time to infer the actual fading loss rate. Thereafter, the fading loss can be excluded from the packet loss observed in the transport layer. Once the accurate congestion loss rate is calculated, the sender can make appropriate adjustment on the transmission rate that reflects the current congestion state along the transmitting path using the DCCP rate control procedure. Simulation results show that DCCP with our proposed CCID 3 rate control scheme can discriminate fading loss and achieve from 4.7% to 15.5% improvement on transmission throughput when the fading loss rate varies from 5% to 15% in wireless network.

Enhanced Bandwidth Utilization in Image Steganography with Enhanced Data Security

this paper, a new method is proposed for image steganography that involves double encryption as well as compression of a message followed by its subsequent hiding in a digital image. In the first instance, original data is encrypted using flexible matrix. Further, encrypted data is encrypted and compressed using Chinese Remainder Theorem (CRT) for extra layer of security and increased the data hiding capacity. The proposed method enhances bandwidth utilization besides ensuring three layered security to the message. The underlying principle of this method involves decomposition of each image-pixel into two blocks. One block is called Parity Reflecting Block (PRB) whereas other is known as Pixel Adjustment Block (PAB). The information about hidden bit is reflected by parity condition in the Parity Reflecting Block. The Pixel Adjustment Block is used to perform local pixel adjustment in order to reduce the degradation effect in the cover image produced as a result of alteration in the moderate bit. The performance of the proposed algorithm is evaluated in terms of Image Quality Measures (IQM) including Mean Square Error (MSE), Peak- Signal-to-Noise Ratio (PSNR), Entropy, Correlation, Mean Value and Standard Deviation. Security analysis is also carried by comparing the histograms of the cover and stego- images. The results of this study are quite promising.

Novel DSA Scheme that Uses Traffic Characteristics to Enhance Throughput Performance of Wide Area Ubiquitous Wireless Networks

Wide area ubiquitous wireless networks, which consist of access points (APs) connected to the fixed network and a great many wireless terminals (WTs), can offer a wide range of applications everywhere. In order to enhance network performance, we need to collect different kinds of data from as many WTs as possible; each AP must be capable of accommodating more than 103 WTs. This requirement can be achieved by employing DSA, a typical centralized media access control scheme, since it has high resource utilization efficiency. In this paper, we propose a novel DSA scheme that employs three new techniques to enhance throughput performance; (1) considering that most terminals tend to send data periodically, it employs both polling-based schemes, i.e. request-polling and data-polling, and a random access scheme. (2) In order to enhance bandwidth utilization effectiveness by polling, the polling timing is decided according to the data generation timing. (3) The AP decides the polled data size according to the latest distribution of data size and polls the WT for the data directly. If the data-polling size can not be determined with confidence, the AP uses request-polling instead of data-polling. Simulations verify that the proposed scheme offers better transmission performance than the existing schemes.

Performance analysis of an adaptive bandwidth reservation scheme for ATM virtual path traffic

Adaptive, in-call, bandwidth reservation may be used to enhance bandwidth utilization in a policed ATM virtual path shared by traffic streams originated by many bursty sources. The mechanism is found to be effective when large changes in the aggregate traffic rate are slow in comparison to the feedback delay with which a requested change in the reserved rate is obtained. We present a model, based on Markov-modulated sources and stochastic fluid methods, for performance analysis of the proposed mechanism. The model, corroborated by simulations, is used to study achievable bandwidth gain and the effects of feedback delay and competing reservation processes.