Traffic Load Variations Research Articles

A Priority-Based Self-Adaptive Random Early Detection Algorithm in IoT Gateways

Effective algorithms for queue management are crucial in place of guaranteeing maximum efficiency in gateway routers since network traffic continues to expand dramatically. An online researcher has suggested the Active Queue Management (AQM) strategy regarding the upcoming generation of gateway switches. The common active queue scheme remains (RED) Random Early Detection. Random early detection is susceptible to parameterization issues and lacks a self-adaptation mechanism. Several RED variants have been formed; nevertheless, variations in traffic load have an adverse effect on all of them. Due to the fact that each has a static drop pattern, to address the RED and its variation schemes, the SARED system, or the design of self-adaptive random early detection was created. But in order to prevent congestion, during the time when the queue length surpasses a present maximum threshold limit, SARED aggressively removes packets. This causes networks having a lot of traffic situations the average is expected to increase queue delay, so in those cases, SARED should be less aggressive. This paper develops a priority-based queuing congestion control method for IoT gateways to manage network congestion. Our method (priority-based algorithms) performs substantially better with regard to throughput, delay, and packet loss than the present methods of SARED. The outcomes of the conducted simulation experiments have shown that in scenarios with heavy traffic loads, priority-based self-adaptive random early detection (PSARED) has greatly decreased average queuing delay by 3%, minimized average throughput by 1%, and decreased the rate of packet loss by 10% in contrast to SARED.

Service-Life Estimation of a Reinforced Concrete Bridge Structure Exposed to Chloride-Contaminated Environments and Variable Traffic Loads

Service-Life Estimation of a Reinforced Concrete Bridge Structure Exposed to Chloride-Contaminated Environments and Variable Traffic Loads

Practical periodic strategy for 40/100 Gbps Energy Efficient Ethernet

The 40/100 Gbps Energy Efficient Ethernet (EEE) standardized by IEEE 802.3bj contains two power saving states. Correspondingly, the strategy determining the state transitions is crucial to both the power consumption and the incurred latency of frames. However, existing strategies hardly configure proper parameters for consistent good performance of power saving under variable traffic loads in reality. To address this issue, we design Practical Periodic Strategy (PPS) for the 40/100 Gbps EEE. Specifically, PPS periodically optimizes the power saving independently in each cycle. In this way, PPS decouples the incurred latency and the energy saving. (1) It limits the incurred delay by the length of the cycle. (2) It achieves good power saving by selecting a proper low power state based on the estimated traffic load in each cycle. Moreover, PPS is practical for two reasons. First, PPS involves just one cycle length parameter, which can be set according to either the given tail latency constraint or optimized automatically according to the cost function reflecting user preference. Second, the good performance of PPS is insensitive to traffic variation, because the traffic variation is smoothed by the cycles of PPS. Extensive simulations based on NS3 confirm that PPS outperforms existing strategies under different traffic patterns.

Mean stress effect in high‐frequency mechanical impact (HFMI)‐treated welded steel railway bridges

AbstractThe need for new railway bridges is driven by the growing volume of transportation demands for both passenger and freight traffic on railway networks. In the design of these bridges, the fatigue limit state is a criterion that usually limits the allowable applied load level and thus also the utilization of the high strength of the steel material. Therefore, improving the fatigue performance of welded details by high‐frequency mechanical impact (HFMI) treatment leads to a more efficient design. However, the fatigue performance of HFMI‐treated welds is known to be affected by the mean stress and this needs to be considered in the design of treated welded details in steel bridges. This is rather straightforward if the bridge is subjected to cycles from one type of train but becomes cumbersome when several different sets of trains (e. g. axle loads, axle distances) cross the bridge. In this article, a factor to take the mean stress effect (including self‐weight and traffic load variations) into account is derived from traffic data measured in Sweden. Moreover, the mean stress effect is also predicted using the different fatigue load models in the Eurocode. These models either consist of one‐load patterns such as LM71, SW/0, and SW/2 or are composed of different trains with different combinations. It was found that the mean stress effect is underestimated by the first group of models. On the other hand, the mean stress predicted by the light traffic mix is found to be close to that calculated using real traffic data, while other mixes (standard and heavy) underestimate the mean stress effect. Therefore, a correction factor to account for the mean stress effects in real traffic is derived (called here λHFMI). This factor can be used to correct the design stress range for fatigue verification of HFMI‐treated welded details in railway bridges.

On-site Energy Utilization Evaluation of Telecommunication Base Station: A Case Study of Western Uganda

Due to the widespread installation of Base Stations, the power consumption of cellular communication is increasing rapidly (BSs). Power consumption rises as traffic does, however this scenario varies from geolocation to geolocation because sites in rural and urban areas have variable traffic loads. Therefore, in order to address various power consumption issues, it is necessary to analyze these sites and offer validate data that network operators can employ. This study took into account the impact of traffic load on the energy consumption both in rural and urban locations in western Uganda because prior models did not adequately account for the impact of traffic load on both rural and urban sites. Regression models are used to examine these effects of traffic load on power consumption. Based on measurements taken for twenty-eight days in a row at six urban and rural areas, linear models have been presented. The findings showed that both rural and urban BTS were well-fitted by the suggested linear models. Depending on the layouts of the sites, it was found that energy consumption varied along with traffic, with the number of transceivers present having an impact on both the traffic load and energy consumption.

Development of integrated semi-active adaptive vibration control system for bridges subjected to traffic loads

Nowadays, the fluid viscous damper is the most conventional energy dissipation system implemented in bridge structures to control the vibrations due to traffic loads. However, to effectively protect the bridge against frequent and severer vibrations, it is required to adapt the function of the damper according to the variable traffic loads. In this research, an Integrated Semi-Active Adaptive Vibration Control System is developed for the bridge structures. This control system consists of a Semi-Active Bypass Fluid Damper (SABFD), a programmable logic controller (PLC), pressure transducers, and displacement sensors. Semi-Active Bypass Fluid Damper is a hydraulic cylinder with a pair of external bypass pipes with motorized electric flow control valves which are installed in the middle of pipes to control the flow rate of the fluid. A programmable logic controller (PLC) is implemented to manage the operation of motorized valves according to the movement of the bridge.Therefore, the integrated control system is able to function as a real-time controller during its operation. To develop the control system, the performance of the SABFD device has been assessed through analytical model of the various control valve positions. Then, according to the structure response, a fuzzy control algorithm has been adapted in the PLC controller.Afterward, the prototypes of the SABFD and the PLC controller have been fabricated and a series of cyclic load tests have been conducted by using a dynamic actuator. The outcomes of the numerical analysis and results of the experimental tests revealed that the developed device is capable of generating a wide range of forces during device operation. The developed fuzzy control algorithm is then implemented to the finite element model of the bridge equipped with SABFD, and the results proved that the real-time control system effectively limits the bridge displacements according to the pre-defined fuzzy control rules.

A novel hybrid deep learning approach for 5G network traffic control and forecasting

Summary5G is planned to link not just traditional devices such as tablets and smartphones, but also smart devices, smart homes, autonomous vehicles, and industry 4.0 which significantly increases the amount of traffic over the network. Network function virtualization and software defined networks will be used heavily to create scalably and on‐demand 5G architecture using virtual network functions. In this article, we proposed a unique approach to scaling 5G core network resources by predicting traffic load fluctuations using a hybrid model. Most researchers have presented deep learning models to anticipate regular traffic to improve services, however, these recommended models have failed to estimate traffic load during festivals to unexpected changes in traffic conditions. To solve this issue, we introduced CNN+LSTM, a hybrid model that combines CNN, and LSTM to forecast cumulative network traffic across particular intervals to scale up and properly estimate the availability of 5G network resources by leveraging traffic load variations. The suggested model surpasses the other tested deep learning models and existing techniques that forecast the output in both normal and abnormal traffic conditions, according to a comparison of the produced output with existing techniques.

Collapse of Existing Bridges: From the Lesson of La Reale Viaduct to the Definition of a Partial Safety Coefficient of Variable Traffic Loads

Collapse of Existing Bridges: From the Lesson of La Reale Viaduct to the Definition of a Partial Safety Coefficient of Variable Traffic Loads

Influence of traffic load on the environmental impacts of roads: A1 and A2 highways in Austria

Professionals should aim to significantly reduce greenhouse gas (GHG) emissions by implementing the best road construction technologies to develop low-carbon projects. Although the traffic loads vary over the road length, the environmental impacts are assessed based on the average values of the traffic loads. Consequently, there is a gap between reality and the impacts calculated with fixed traffic load. This paper aims to assess the gap in terms of the environmental impacts of two roads by considering both a constant and a variable traffic load. With the help of a life cycle assessment (LCA), the environmental impacts of the A1 and A2 highways in Austria are calculated. We have calculated the impacts in the first scenario by considering an average traffic load. In the second scenario, based on real measurements, the environmental impacts of both highways are calculated for a variable traffic load. In the end, the results show a gap in the range of 25 %. This difference was because some parts of the roads required frequent repair. Besides, we figured out the optimal thickness of the wearing course, which improves the impact calculation and makes it less likely that the results will be different along the length of the road.

Deterministic Latency/Jitter-Aware Service Function Chaining Over Beyond 5G Edge Fabric

Deterministic Networking (DetNet) has recently attracted much attention. It aims at studying the deterministic bounded latency and low latency variation for time-sensitive applications (e.g., industrial automation). To improve the quality of service (QoS) guarantee and make the network management efficient, it is desirable for Internet Service Provider (ISP) to obtain an optimal service function chain (SFC) provision strategy while providing deterministic service performance for the time-sensitive applications. In this paper, we will study the deterministic SFC lifetime management problem in beyond 5G edge fabric with the objective of maximizing the overall profits and ensuring the deterministic latency and jitter of SFC requests. We first formulate this problem as a mathematical model with the maximal profits for ISP. Then, the novel Deterministic SFC Deployment algorithm (Det-SFCD) and SFC Adjustment algorithm (Det-SFCA) due to traffic load variation are proposed to efficiently solve the SFC lifetime management problem. Extensive simulation results show that our proposed algorithms can achieve better performance in terms of SFC request acceptance rates, overall profits and latency variation compared with the benchmark algorithm.

Permanent Deformation and Breakage Response of Recycled Concrete Aggregates under Cyclic Loading Subject to Moisture Change

Natural granular materials widely used in building and infrastructure development consume a considerable number of natural resources. To avoid depleting natural granular materials, recycled concrete aggregates (RCA) from construction and demolition waste are now commonly used as an alternative. The mechanical behavior of RCA used in road construction is highly influenced by field conditions such as traffic load and moisture variation. The particle breakage of RCA influences long-term pavement performance because it changes the RCA grading over time. However, the effect of moisture content (m.c.) on mechanical behavior and particle breakage during compaction and cyclic loading is often neglected. The aims of the study were to investigate the mechanism of permanent deformation development due to moisture change, the breakage response of RCA in this process, and the assessment of existing permanent deformation prediction model. The results showed that initial m.c. effectively controlled the deformation of RCA; the permanent axial strain (εpa) was enhanced, and the breakage of coarse fraction (19~9.5 mm) under cyclic loading was reduced at higher levels of m.c. Based on the experimental results, a modified model for predicting εpa was proposed, incorporating a deviation factor induced by m.c. The model fitted the experimental data well, suggesting that it is useful to have a quantitative estimation of εpa of RCA with different m.c. under cyclic loading.

On Reliable Key Performance Indicators in Cognitive Radio Networks

Network serveability (NS), which considers both channel availability (CA) and service retainability (SR), is a key indicator to concisely express the performance of cognitive radio networks (CRNs). However, CA cannot guarantee connection setup if receiver’s accessibility ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RxA</i> ) is neglected. Likewise, SR yields imperfect results if <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RxA</i> is ignored. As such, the two rather incomplete performance indicators misrepresent NS and lead to an overestimated satisfaction level of users. Aiming at reliable and concise analysis of CRNs’ performance, this letter introduces the concept of connection availability (CoA), which encompasses both CA and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RxA</i> for a user. Besides, it introduces service maintainability (SM), which incorporates the impact of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RxA</i> into SR. Consequently, the performance is represented more concisely through network serviceability (NeS), a concept we introduce to consider both CA and SM. We show that CoA, SM, and NeS diverge with various proportions from CA, SR, and NS, respectively, under variable traffic loads and channel failure rates. This indicates the degree of performance difference <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RxA</i> introduces, and provides network designers the basis for dependable CRN budgeting.

Piezoelectric-sensored sustainable pads for smart railway traffic and track state monitoring: Full-scale laboratory tests

The present paper focuses on an initial assessment into the applicability of sensored sustainable pads, made from recycled polymers and embedded with commonly-accessible piezoelectrics. These sensing devices were used as smart rail pads and inside bituminous sub-ballast to monitor traffic and track state by measuring the stress variations in the components. A series of full-scale laboratory tests were carried out simulating train passage under diverse traffic scenarios and varying track section conditions in a testing box. Results indicated that the smart sustainable pads in both components showed the capacity to detect traffic load variations by measuring relative changes in signal amplitude of the sensor. Nonetheless, the smart rail pads presented higher accuracy to monitor axle loads, while the signals from the sub-ballast were influenced by the position of the sensor and so a higher potential to monitor track performance, rail-sleeper load distribution and detecting phenomena like hanging sleepers.

Time-dependent reliability analysis for a set of RC T-beam bridges under realistic traffic considering creep and shrinkage

Reinforced concrete bridges constitute the major part of existing bridges. The purpose of this paper is to present a serviceability evaluation methodology for RC bridges under probabilistic conditions. It will be based on analytical calculations with no need to complex modeling or advanced software. For this purpose, a realistic traffic model is simulated based on existing weigh-in-motion WIM data from some European sites. The probabilistic distributions of the time-dependent load effects, moment and deflection, are then deduced after hundreds of simulations. The degradation effects are introduced in the analysis by considering the concrete creep and shrinkage. A simplified model to introduce creep effect under variable traffic load is also proposed. The time dependent reliability indices are then calculated for a set of 21 simply supported RC T-beam bridges with varying parameters such as span lengths, number of girders, girder spacing and number of design lanes. The first order reliability method FORM, is used in the reliability calculation in order to evaluate the structural performance under the considered failure scenario.

The Effect of Traffic on Ballast Settlement

The main factor that contributes to the deterioration of track components is traffic load. Explanations on how the speed, load and repetition of traffic influence the long-term settlement of ballast in a ballasted track are very scarce. Having in mind that tracks subjected to the same load show different settlement behaviors, explanations of track settlements in accordance with the speed, load and repetition are needed. This study is motivated to show how traffic affects the long-term settlement of ballast and how the traffic parameters (speed, load and repetition) contribute to the process. Using finite element modeling software, the three-dimensional track is modeled and analyzed for different values of speed, load and number of repetitions. Drucker Prager plastic model is applied for the ballast and sub-ballast materials of the track. To get the parameters for the Drucker Prager plastic model of granular materials, triaxial test simulation is performed using discrete element software. Hertz’s contact theory is used to model the contact between the wheel and rail. The long-term settlement behavior of ballast material is analyzed by applying 8000 cycles of moving axel load. According to the analyses, a change in the speed and the number of repetitions of train movement changes the permanent settlement of ballast more than the variation in load. Increase in the speed of train movement by 20 km/hr. will increase the stress transferred to the subgrade by up to about 1000 kPa. Speed of train movement is the most contributing parameter in the degradation of ballast material more than the load and number of repetitions. In a conventional ballasted track after about 6000 repetitions of train movement ballast material will start to decrease its performance. The comparison of the effects of the variation of individual traffic parameters speed, load and number of repetitions on the settlement of ballast which is not touched by former researches is well addressed by this study which is very helpful for designing a new railway track and monitoring existing railway tracks. Based on the analysis of the model with the parameters from Ethio-Djibouti standard gauge railway track, the possible maintenance period of ballast material is predicted.

An enhanced dynamic transmission opportunity scheme to support varying traffic load over wireless campus networks.

Transmission opportunity (TXOP) is a key factor to enable efficient channel bandwidth utilization over wireless campus networks (WCN) for interactive multimedia (IMM) applications. It facilitates in resource allocation for the similar categories of multiple packets transmission until the allocated time is expired. The static TXOP limits are defined for various categories of IMM traffics in the IEEE802.11e standard. Due to the variation of traffic load in WCN, the static TXOP limits are not sufficient enough to guarantee the quality of service (QoS) for IMM traffic flows. In order to address this issue, several existing works allocate the TXOP limits dynamically to ensure QoS for IMM traffics based on the current associated queue size and pre-setting threshold values. However, existing works do not take into account all the medium access control (MAC) overheads while estimating the current queue size which in turn is required for dynamic TXOP limits allocation. Hence, not considering MAC overhead appropriately results in inaccurate queue size estimation, thereby leading to inappropriate allocation of dynamic TXOP limits. In this article, an enhanced dynamic TXOP (EDTXOP) scheme is proposed that takes into account all the MAC overheads while estimating current queue size, thereby allocating appropriate dynamic TXOP limits within the pre-setting threshold values. In addition, the article presents an analytical estimation of the EDTXOP scheme to compute the dynamic TXOP limits for the current high priority traffic queues. Simulation results were carried out by varying traffic load in terms of packet size and packet arrival rate. The results show that the proposed EDTXOP scheme achieves the overall performance gains in the range of 4.41%—8.16%, 8.72%—11.15%, 14.43%—32% and 26.21%—50.85% for throughput, PDR, average ETE delay and average jitter, respectively when compared to the existing work. Hence, offering a better TXOP limit allocation solution than the rest.

A fully distributed approach for joint user association and RRH clustering in cloud radio access networks

Cloud radio access network (C-RAN) is a new centralized architecture to meet the exponential growing of demand of mobile traffic in 5G cellular wireless networks. However, C-RAN requires an efficient mechanism for the joint user association and the Remote Radio Head (RRH) clustering to improve network performance. In this paper, we investigate the problem of joint user association (UA) and RRH clustering (RC) in C-RAN. Our objective is to maximize the network utility function incurred by both network power consumption and total user throughput for both streaming and elastic traffic. The formulation of the joint optimization problem is a mixed-integer non-linear programming problem (MINLP), which is NP-hard and usually has no feasible solution. To solve it, we propose to decouple the joint problem into two sub-optimization problems: the user association (UA) sub-problem and the RRH clustering (RC) sub-problem. These two sub-problems are sequentially and iteratively solved until convergence is reached. Leveraging on the information delivered by the Call Detail Records (CDR), simulation results reveal the effectiveness of our heuristic solution for the RC sub-problem in enhancing network utility and adapting to the traffic load variation for both elastic and streaming traffic. It outperforms the performance of the state-of-the-art algorithms for RRH clustering solutions, including no-clustering and grand coalition methods. Moreover, the results show that our approach for the UA sub-problem provides close performance to the optimal UA sub-problem.

A time‐efficient shrinkage algorithm for the Fourier‐based prediction enabling proactive optimisation in software‐defined networks

SummaryThis paper focuses on the problem of time‐efficient traffic prediction. The prediction enables the proactive and globally scoped optimisation in software‐defined networks (SDNs). We propose the shrinkage and selection heuristic method for the trigonometric Fourier‐based traffic models in SDNs. The proposed solution allows us to optimise the network for an upcoming time window by installing flow entries in SDN nodes before the first packet of a new flow arrives. As the mechanism is designed to be a part of a sophisticated routing‐support system, several critical constraints are considered and taken into account. Specifically, the system is traffic‐ and topology‐agnostic, thus the prediction mechanism must be applicable to the networks with highly variable traffic loads (e.g., observed inside intra‐DCNs: datacentre networks). Furthermore, the system must effectively optimise routing in large‐scale SDNs comprised of numerous nodes and handling millions of flows of a dynamic nature. Therefore, the prediction must be simultaneously accurate as well as being time efficient and scalable. These requirements are met by our Fourier‐based solution, which subtracts consecutive harmonics from the original signal and compares the result with an adaptive threshold adjusted to the signal's standard deviation. The evaluation is performed by comparing the proposed heuristic with the well‐known Lasso method of proven accuracy. The results show that our solution is able to retain prediction accuracy at a comparable level. Moreover, in accordance with our main aim, we operate in a manner which is always significantly faster. In some cases, computation times are reduced by as much as 50 times.

Telecommunication customer satisfaction using self‐organized network‐based heuristic algorithm

SummaryThe emerging network including long‐term evolution‐advanced (LTE‐A) aims at enhancing the telecommunication customer satisfaction in numerous aspects including system capacity, network coverage, handover management, and quality of service (QoS). Effective handover (HO) management reduces HO failure and hence enhances the data rate and supports user mobility. There are numerous challenges that increase the call drop rate. Among the main challenges that increase the call drop rate, the variable user speeds and variable traffic loads are the major ones. Hence, the time to trigger (TTT), HO margin (HOM), and HO offset (HOO) are used to evaluate the HO management using self‐organized network‐based heuristic algorithm under variable user speeds and variable traffic loads. In recent researches, different HO management techniques were applied to manage the HO decision including fuzzy‐logic tactics and Q‐learning. However, they did not apply intelligent optimization techniques that adapt the variable user speeds and dynamic traffic loads. This paper aims at increasing the telecom customer satisfaction by decreasing the call drop rate using particle swarm optimization (PSO), which adaptively manages the handover control parameters according to the user speed and traffic loads. The simulation results have shown that the proposed optimization tool results in significant call drop rate reduction compared to the ordinary HO management.

Physical layer security in shotgun cellular systems over correlated/independent shadow fading channels

The shotgun cellular systems (SCSs) (modeling, generally, a dense cellular or wireless data network deployment and non-ideal regular hexagonal grid with site-acquisition difficulties, variable traffic load) are wireless communication systems with randomly placed base stations (BSs) over the entire plane according to a stochastic (e.g., Poisson) point process in n dimensions (n = 1, 2, and 3). Due to the good performance and the importance of the SCSs in today’s communications, the physical layer security of these systems is practically of importance, specifically, in more realistic channel propagation models. In this paper, by assuming that the channel coefficients are known at the receiver, we analyze the performance of the physical layer security for the classic Wyner’s three-node model in the SCSs over correlated/independent log-normal shadow fading channels. For this purpose, first, we calculate the signal-to-interference-plus-noise ratio (SINR) performance at a mobile station (MS) in an SCS. Then, the average secrecy capacity (ASC), the probability of non-zero secrecy capacity (PNSC), the secure outage probability (SOP), and the lower bound of SOP (LSOP) are obtained, and also, their approximated closed-form expressions are derived. Finally, analytical results are validated numerically.