Low Network Throughput Research Articles

Hierarchical Cross Traffic Scheduling Based on Time-Aware Shapers for Mobile Time-Sensitive Fronthaul Network

To solve the problem of jitter and low network throughput caused by the impact of background flows on IQ traffic in mobile fronthaul network, this paper proposed a new scheduling model for background flows, named hierarchical crossover traffic scheduling mechanism based on time-aware shaper (HC-TAS) by improving the traditional counterpart. Then, in this new model, we designed an inbound scheduling algorithm based on frame length matching and an outbound scheduling algorithm based on queue status, making sure that smaller data frames will not be blocked by large data frames. This greatly improves the utilization of timeslots in the scheduling process and reduces the jitter impact of background flows. To verify its performance, we conducted experiments in a simulated fronthaul network conforming to IEEE 802.1CM. The experimental results show that, under the condition that the jitter is guaranteed to be zero, compared with two mainstream scheduling schemes, Comb-FITting and TAS + Preemption, our proposed scheme can achieve lower maximum end-to-end delay and higher link utilization. The proposed HC-TAS meets the requirements of low jitter and high bandwidth utilization in 5G fronthaul network, and the research results provide a technical basis for the application and development of general time-sensitive networks as well.

An adaptive intelligent routing algorithm based on deep reinforcement learning

A mobile ad hoc network (MANET) is a self-organizing network composed of multiple mobile nodes. These nodes achieve distributed communication and wireless resource sharing through autonomous collaboration. However, typical routing protocols for MANETs suffer from uneven network load, low network throughput, poor anti-destruction performance, and low transmission reliability. In order to meet the routing protocol characteristics of distributed adaptability, reliability and anti-destruction, balance of load and energy consumption and guarantee of high QoS in MANETs, this paper proposes an adaptive intelligent routing algorithm based on the PER-D3QN model of deep reinforcement learning. To achieve better routing strategy selection, the routing problem is first modeled, a distributed multi-agent reinforcement learning routing framework is designed, and a deep reinforcement learning reward function considering multiple factors is used. Next, the implementation process of the adaptive intelligent routing algorithm using the PER-D3QN model is described in detail. Finally, a mobile self-organizing network environment was constructed based on Networkx, and corresponding data was collected to simulate the algorithm. The simulation results show that the adaptive intelligent routing algorithm proposed in this paper can balance the energy consumption of the network and the load of nodes, its average remaining energy has increased by more than 10% and PL is reduced by at least 10% compared to other algorithms, while guaranteeing high QoS performance of routing, that is, reducing the average end-to-end delay of data packet transmission by over 22% compared to other algorithms and maintaining a high packet delivery ratio.

High Value of Information Guided Data Enhancement for Heterogeneous Underwater Wireless Sensor Networks

Ensuring the freshness of high Value of Information (VoI) data has a significant practice meaning for marine observations and emergencies. The traditional forward method with an auv-aid is used to ensure the freshness of high VoI data. However, the methods suffer from two issues: an insufficient high VoI data throughput and random forwarding for cluster heads (CHs). The AUV (Autonomous Underwater Vehicle) with limited energy cannot meet the demand for the random generation of high VoI data. Low VoI data packets compete with high VoI data packets for channels, resulting in an insufficient high VoI data throughput and a low freshness. To address the above issues, we propose the Data Access Channel Scheme based on High Value of Information (DACS-HVOI), which is suitable for prioritizing the transmission packets with a high VoI. First, according to the level of VoI, the packets are divided into K classes, and the packets that are collected and forwarded by the AUV are defined as the highest K+1 class. Second, based on prior knowledge in the network, a Markov chain algorithm-based method is employed to predict which nodes should preferentially use the channel, to avoid conflict between a low and high VoI. Third, based on the stochastic fluid theory, a multilevel queueing system for CHs are constructed to avoid random forwarding. Last, compared with state-of-art protocols, experimental simulation shows that the proposed scheme has a low latency and high network throughput, while improving the throughput of high-VoI packets and ensuring the priority transmission of high-VoI packets.

Usage of a computer cluster for physics simulations using bullet engine and OpenCL

The study focuses on using a computer cluster for implementing real-time physical simulations, responding to a growing need for such use in various sectors, including medicine, video processing, automated transport management, robotics, and visualisation. The object of research is cluster and cloud technologies for conducting costly physical simulations for specific sectors, particularly high-budget and entertainment ones, such as cinematography and interactive entertainment. Research methods include using a modified Bullet engine to carry out physical simulations, integrated with OpenCL to work with the cluster. The choice of these technologies was determined by their high performance and adaptability to cluster systems. The research was based on a typical Bullet framework’s benchmark falling tower scene with the primary goal of measuring computational performance in frames per second. Results showed that the use of clusters is not advisable in environments with a low network throughput and the use of non-uniform computers. Under those conditions, simulations using a cluster become unstable with many objects and contacts between them and show a degradation in performance by an average of 50–60 % (to values of 10–20 frames per second). Despite the intermediate results of calculations on the cluster, the study met the expectations within the goals set and resources available. These results have significant implications for the further development of cluster and cloud technologies in physical simulations, providing valuable information about the limitations and capabilities of these systems.

A Formal Verification of a Reputation Multi-Factor Authentication Mechanism for Constrained Devices and Low-Power Wide-Area Network Using Temporal Logic.

There are many security challenges in IoT, especially related to the authentication of restricted devices in long-distance and low-throughput networks. Problems such as impersonation, privacy issues, and excessive battery usage are some of the existing problems evaluated through the threat modeling of this work. A formal assessment of security solutions for their compliance in addressing such threats is desirable. Although several works address the verification of security protocols, verifying the security of components and their non-locking has been little explored. This work proposes to analyze the design-time security of the components of a multi-factor authentication mechanism with a reputation regarding security requirements that go beyond encryption or secrecy in data transmission. As a result, it was observed through temporal logic that the mechanism is deadlock-free and meets the requirements established in this work. Although it is not a work aimed at modeling the security mechanism, this document provides the necessary details for a better understanding of the mechanism and, consequently, the process of formal verification of its security properties.

Fluid-Flow Approximation in the Analysis of Vast Energy-Aware Networks

The paper addresses two issues: (i) modeling dynamic flows transmitted in vast TCP/IP networks and (ii) modeling the impact of energy-saving algorithms. The approach is based on the fluid-flow approximation, which applies first-order differential equations to analyze the evolution of queues and flows. We demonstrate that the effective implementation of this method overcomes the constraints of storing large data in numerical solutions of transient problems in vast network topologies. The model is implemented and executed directly in a database system. It can analyze transient states in topologies of more than 100,000 nodes, i.e., the size which was not considered until now. We use it to investigate the impact of an energy-saving algorithm on the performance of a vast network. We find that it reduces network congestion and save energy costs but significantly lower network throughput.

PIQI: perceptual image quality index based on ensemble of Gaussian process regression

Digital images contain a lot of redundancies, therefore, compression techniques are applied to reduce the image size without loss of reasonable image quality. Same become more prominent in the case of videos which contains image sequences and higher compression ratios are achieved in low throughput networks. Assessment of quality of images in such scenarios has become of particular interest. Subjective evaluation in most of the scenarios is infeasible so objective evaluation is preferred. Among the three objective quality measures, full-reference and reduced-reference methods require an original image in some form to calculate the image quality which is unfeasible in scenarios such as broadcasting, acquisition or enhancement. Therefore, a no-reference Perceptual Image Quality Index (PIQI) is proposed in this paper to assess the quality of digital images which calculates luminance and gradient statistics along with mean subtracted contrast normalized products in multiple scales and color spaces. These extracted features are provided to a stacked ensemble of Gaussian Process Regression (GPR) to perform the perceptual quality evaluation. The performance of the PIQI is checked on six benchmark databases and compared with twelve state-of-the-art methods and competitive results are achieved. The comparison is made based on RMSE, Pearson and Spearman’s correlation coefficients between ground truth and predicted quality scores. The scores of 0.0552, 0.9802 and 0.9776 are achieved respectively for these metrics on CSIQ database. Two cross-dataset evaluation experiments are performed to check the generalization of PIQI.

Multi-Objective Control Optimization for Congestion Avoidance in Computer Networks

Effective congestion control is an issue strongly impacting basic features demanded from modern network environment as reliability, high and stable throughput, and low delays. These characteristics define the quality of communication channels. Optimizing network nodes configuration for only one of mentioned features, can exacerbate other parameters. This paper focuses on avoiding and alleviating network congestions using multi-objective optimization for gain setting of used controllers. Unlike in other presented approaches, in this case the non-stationary, discrete, dynamical model is discussed. The significant advantage of this approach is in the better reflection of the real environment conditions, where the transmission delay is floating. As the further development of the control strategy, the controller with the memory of previous steps have been deployed. Such control strategy mitigates the unfavorable impact of extended delays. Both proposed control strategies tune the presented model of communication channel to alleviate the results of sudden, unexpected network state changes. It is obtained by maximization of available bandwidth usage combined with minimization of buffer utilization. This supports avoiding undesirable congestion effects like packet dropping, retransmissions, high delay, and low network throughput.

Preamble time-division multiple access fixed slot assignment protocol for secure mobile ad hoc networks

Mobile ad hoc networks are the “spontaneous networks” which create a temporary network in any place and any time without using any extra fixed radio device of a full infrastructure network. Each device in this network works as a router to develop end-to-end communication connections and move independently in any direction. Mostly, mobile ad hoc networks use the IEEE 802.11b protocol with carrier-sense multiple access with collision avoidance medium access control layer protocol for sharing a common medium among the nodes simultaneously. Due to this distributed medium, the routing and medium access control layer of the mobile ad hoc network are prone to attacks. Among several attackers, blackhole attacker is the dangerous one which causes the loss of all data packets of devices in the network. Efficient medium access control protocol designs in this respect play a key role in determining channel utilization, network delay, and, more importantly, network security. In the proposed work, preamble information is used with time-division multiple access medium access control. The preamble time-division multiple access uses time synchronization for each time slot and does not assign much time to the blackhole attacker due to a fixed time slot. As a result, blackhole is not stable in all communications and such an attack is effectively defended. Simulation results show that, in the presence of the blackhole attacker, carrier-sense multiple access with collision avoidance has a high packet loss ratio and low network throughput as compared to the proposed preamble time-division multiple access.

A smart Internet of Things–based mechanism for wireless communications in NoC

With the development of silicon integration technology, the network-on-chip (NoC) proposes a scalable communication architecture that can improve system performance. Future multi-core chips are expected to be heterogeneous and hierarchical in nature. Inter-frequency interference will occur between various 2.4-GHz wireless network communication cores integrated on the same chip, resulting in lower network throughput and higher communication latency. This article solves the problem of wireless co-channel mutual interference from the two aspects of time domain and frequency domain and designs a heterogeneous platform based on NoC architecture to achieve more stable parallel communication of multiple wireless co-frequency networks without mutual interference. When the system detects the interference, this article uses the chirped fractional Fourier transform to filter out the interference signal before the signal arrives and then spreads the frequency. According to the results, the method improves the anti-interference ability of the network and the utilization of spectrum resources. Compared with the traditional carrier sense multiple access method, the spectrum-aware channel cooperation method proposed in this article reduces the data average transmission delay by 0.02 s and the data packet reception rate is increased by about 30%, which provides a certain reference value for future wireless multi-core communication.

Channel-Aware Rate Adaptation for Backscatter Networks

Backscatter communication networks receive much attention recently due to the small size and low power of backscatter nodes. As backscatter communication is often influenced by the dynamic wireless channel quality, rate adaptation becomes necessary. Most existing approaches share a common drawback: they fail to take both spatial and frequency diversity into consideration at the same time. Consequently, the transmission rate may be improperly selected, resulting in low network throughput. In this paper, we propose a channel-aware rate adaptation framework (CARA) for backscatter networks. CARA incorporates three essential modules, a lightweight channel probing scheme that differentiates collisions from packet losses, a burstiness-aware channel selection mechanism benefiting as many backscatter nodes as possible, a rate selection method choosing the optimal rate, and a mobility detection that discovers location changes. We implement CARA on commercial readers, and the experiment results show that CARA achieves up to $4 \times$ goodput gain compared with the state-of-the-art rate adaptation scheme.

Green Wireless Video Sensor Networks Using Low Power Out-of-Band Signalling

The availability of low cost networked wireless devices and video cameras is enabling wireless video sensor networks (WVSNs), which can be used in scenarios such as healthcare, agriculture, smart cities, intelligent transportation systems, and surveillance. These scenarios typically require that each node sends a video stream to a server located in the cloud. The IEEE 802.11 is considered a suitable technology for transmitting video wirelessly, as it supports high data rates. However, when using a multi-hop topology to extend the IEEE 802.11 coverage, the IEEE 802.11-based WVSNs suffer from three problems: low network capacity, throughput unfairness, and energy inefficiency. To overcome these problems, we propose a holistic solution, named Green wiReless vidEo sENsor NEtworks uSing out-of-band Signalling (GREENNESS). GREENNESS combines a node polling mechanism with the use of out-of-band signaling over a low power radio to signal when a video sensor should switch ON and OFF its IEEE 802.11 interface, thus saving energy. The results obtained for random network topologies show that GREENNESS can achieve energy savings up to 92%, and improve network capacity and throughput fairness when compared to state of the art CSMA/CA-based WVSN solutions.

Secure Healthcare Data Dissemination Using Vehicle Relay Networks

In the recent years, vehicular adhoc networks (VANETs) can be an attractive choice for collecting and transferring the healthcare data of the passengers to the remote healthcare centers. In VANETs, some of the intermediate nodes may act as relay nodes in which case, these networks are called as vehicular relay networks (VRNs). However, the transmitted information in VRNs can be captured by intruders during transmission. Moreover, an attacker can launch selective forwarding, blackhole, and sinkhole attacks in the network, which may in turn degrade the network performance parameters like high end-to-end delay, low packet delivery ratio (PDR) and network throughput. Hence, to address these issues, a secure data dissemination scheme using VRNs is proposed. In the proposed scheme, first, a secure vehicular medical relay network system is designed for the users belonging to disconnected rural areas. The collected information is filtered at zonal levels before transmission to a nearby road side units, which further pass it to the incoming vehicles. Second, a secure passenger health monitoring network is designed which continuously monitors health services of the passengers traveling in different vehicles. The information collected through small body sensors installed in the vehicles act as data sets that is forwarded to the on-board monitoring unit within the vehicle. This collected data is then transmitted to centralized healthcare centers for processing by using VRNs. Lastly, a strong elliptic curve cryptography-based cryptographic solution is designed for secure communication among different vehicles. The performance of the proposed scheme is evaluated in various network scenarios with respect to different selected parameters, such as throughput, network delay, PDR, jitter, transmission and computation overheads, and key distribution overhead. The obtained results indicate that the proposed scheme provides improvement of 52% in average delay and 5% in PDR. This further indicates effective message delivery even with high mobility of the vehicles.

Adaptive Load-Aware Congestion Control Protocol for Wireless Sensor Networks

Congestion control in wireless sensor networks (WSNs) is crucial. In this article, we discuss congestion control and the adaptive load-aware problem for sensor nodes in WSNs. When the traffic load of a specific node exceeds its the available capacity of the node, a congestion problem occurs because of buffer memory overflow. Congestion may cause serious problems such as packet loss, the consumption of power, and low network throughput for sensor nodes. To address these problems, we propose a distributed congestion control protocol called adaptive load-aware congestion control protocol (ALACCP). The protocol can adaptively allocate the appropriate forwarding rate for jammed sensor nodes to mitigate the congestion load. Through the buffer management mechanism, the congestion index of neighboring sensor nodes, and an adjustment of the adaptive forwarding rate, the degree of congestion is alleviated markedly. The performance in allocating the forwarding rate effectively to neighboring sensor nodes also improves. The ALACCP can avoid packet loss because of traffic congestion, reduce the power consumption of nodes, and improve the network throughput. Simulation results revealed that the proposed ALACCP can effectively improve network performance and maintain the fairness of networks.

PC-MAC: A Prescheduling and Collision-Avoided MAC Protocol for Underwater Acoustic Sensor Networks

The impact of the acoustic modem with long preamble characteristic on the collision feature of the media access control scheme in underwater acoustic sensor networks (UANs) is evaluated. It is observed that the collision probability is relatively high due to the extremely long duration of preamble. As a result, UANs generally have much lower network throughput. To address this problem, a prescheduling MAC protocol named PC-MAC for UANs is proposed, which leverages a novel prescheduling scheme for the exchange of control packet to alleviate the collision probability among control packets. PC-MAC is a reservation-based channel access scheme. In the proposed protocol, an extra guard time is introduced to avoid the influence of dynamic spatial-temporal uncertainty of the sender and receiver positions. Simulation results show that PC-MAC outperforms classic reservation-based MAC protocol named SFAMA in terms of network goodput and end-to-end delay and lowers collision probability among control packets in two representative network scenarios.

Joint channel assignment and routing protocol for cognitive radio ad hoc networks

Conventional single channel wireless ad hoc networks usually suffer from low network throughput owing to the higher number of packet transmissions required for multi-hop communication. Using multiple channels within a single network can improve the network throughput. In multi-channel communication networks, the channels must be assigned appropriately to maximise network performance. Existing channel assignment methods are usually based on the approach of interference reduction/minimisation, for example, by making a link to operate on only one channel and different links to operate on different channels. In this paper, we go in the opposite direction and propose to make links to operate on more channels. A new distributed joint channel assignment and routing protocol for cognitive radio ad hoc networks called cognitive radio-enhanced AOMDV is proposed. Simulation studies showed that our method outperforms other methods.

An efficient proxy adaptive gateway discovery algorithm based on quality of service parameters

Integration of MANET with internet requires gateways for increasing its usability and accessibility to fixed IP networks. However, such integrations prove complex owing to differences in mobility, routing and addressing between mobile ad hoc networks and fixed IP networks. Existing gateway discovery schemes suffer from low network throughput and performance trade-off. In our proposed gateway discovery scheme, apart from considering timestamp factor, hop count and interface queue length for selection of an optimal gateway, stability of link along the route is also taken into account. Stability of link ensures that message exchange after gateway discovery procedure will not be lost during transit. The proposed approach performance is evaluated through simulation and also analytically validated. Results show our approach has found to be outperforming other ones.

An aggregated technique for optimization of SOAP performance in communication in Web services

Simple Object Access Protocol (SOAP) among other techniques implements Web Services (WS). SOAP offers a lightweight and simple mechanism for exchange of structured and typed information among computing devices in a decentralized, distributed computing environment. However, SOAP transmits data in Extensible Markup Language (XML) format. XML documents are huge in size and verbose thus becoming a major hindrance in performance for high-performance applications that process lots of data. In this paper, we develop, implement and evaluate SOAP performance optimization aggregated architecture in a disadvantaged network, i.e., 10 Mbps bandwidth. The aggregated architecture entailed: client side caching, document---literal Web Services Description Language (WSDL) description, simple database queries on the server side and Gzip compression technique. The experimental results showed a relatively high turnaround time and low network throughput. Nevertheless, improved performance of SOAP is evident in terms of bandwidth utilization and transfer time. This can be useful in disadvantaged networks.

Improving network coding in wireless ad hoc networks

Wireless ad hoc networks usually have lower network throughput than wireless infrastructure networks due to the inherent nature of multi-hop communication on a shared channel in wireless ad hoc networks. Network coding is a method that can improve the network throughput by reducing the amount of workload in the network while still ensuring that all user data is transferred. With network coding, a node can improve its transmission efficiency by combining (encoding) several packets together and sending only the resultant encoded packet if the coding conditions are satisfied. In this paper, we propose the Network Coding Routing (NCRT) protocol which consists of a new set of coding conditions, and a new routing metric that takes into consideration both coding opportunities and network workload. Comprehensive simulation studies showed that NCRT gives promising performance.

Joint Channel Assignment and Routing Protocol for Cognitive Radio Ad Hoc Networks

Conventional single channel wireless ad hoc networks usually suffer from low network throughput owing to the higher number of packet transmissions required for multi-hop communication. Using multiple channels within a single network can improve the network throughput. In multi-channel communication networks, the channels must be assigned appropriately to maximise network performance. Existing channel assignment methods are usually based on the approach of interference reduction/minimisation, for example, by making a link to operate on only one channel and different links to operate on different channels. In this paper, we go in the opposite direction and propose to make links to operate on more channels. A new distributed joint channel assignment and routing protocol for cognitive radio ad hoc networks called cognitive radio-enhanced AOMDV is proposed. Simulation studies showed that our method outperforms other methods.