A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart agriculture.Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes.This paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks.The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies.The protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base station.The performance of the proposed protocol is evaluated through the network simulator NS3.40.For different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network lifetime.For 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.

Durability of Bridge Expansion Joints with Perforated Dowels Under Traffic Impact Loading

In design phases, expansion joints are required to have movement capacity, bearing capacity for static and dynamic loading, watertight, low noise emission and traffic safety. On the basis of the fact that failure due to dynamic loading is the main reason for the observed damages, attention is focused on the bearing capacity for dynamic loading governed by impact, because it differs from the static loading. In this study, from the viewpoint of durability, experimental studies for dynamic behavior were conducted for aluminium alloy expansion joints with perforated dowels. The validity of the perforated dowels against traffic impact loading was confirmed by both experimental and numerical studies.

An investigation on the strain accumulation of the lightly EICP-cemented sands under cyclic traffic loads

Industrial production of chemical cement leads to extreme emissions of greenhouse gases.Biological or bioinspired sustainable materials for soil treatment projects can be employed instead of chemical cement to heal the carbon cycle in the ecosystem.The enzyme-induced calcite precipitation(EICP)method is one of the novel bio-inspired technologies that can be employed in soil treatment projects to increase desired properties of soils.While the monotonic and cyclic behavior of the enzymatically treated sands has been investigated comprehensively,the strain accumulation pattern in these improved soils under cyclic traffic loads has not been evaluated yet.In this paper,confined and unconfined cyclic compression tests are applied to the enzymatically lightly cemented sands,and the effects of the different parameters on their strain accumulation pattern are investigated for the first time in the literature.This study uses two types of specimens with unconfined compression strengths(UCS)equal to 42 kPa and 266 kPa.It is shown that the treated specimens have a rate-dependent behavior where cyclic loads with low frequencies lead to more resilient and plastic strains in the specimens.The results show that by approaching the maximum applied stresses to the UCS of the specimens(by breaking more calcite bonds between sand particles),the rate dependency behavior of specimens will reduce.Investigation of the effects of the cementation level demonstrated that by increasing the amount of the precipitated calcite from 0.38%to 0.83%,accumulated plastic strains are reduced almost 95%under the same loading condition.Effects of the initial static loads,confining pressures,the number of cycles,and amplitudes of the cyclic loads are also evaluated.

Estimating the frequency of traffic overloading on road bridges

Load limits,which appear to be routinely exceeded by trucks,occasionally result in road bridge failures.Therefore,predicting failures is crucial for safeguarding road safety.Past studies have largely focused on forecasting bridge failure event probability using the reliability analysis method,whilst occasionally accounting for vehicular overloading effects.Only recently,a study has investigated design traffic overloading event frequency using generalised linear regression models(GLRMs),including a power component and negative binomial regressions(NBRs).However,as far as the authors know,artificial neural network models(ANNMs)have never been applied to this field.This paper is an attempt to fill in these gaps.First a frequencybased metric of traffic overloading was adopted as a driver of failure probability.Second,two alternative‘frequency'models were specified,calibrated,and validated.The former was based on a GLRM,the latter on ANNMs.Then,these models were compared using regression plots(RPs),measures of errors(Mo Es)and the ratio between the number of observed vs predicted design load overcoming events to evaluate their performance.The models analysed more than 2 million weigh-in-motion(WIM)data records from a pilot station on a bridge on a heavily used ring road in Brescia(Italy).Results showed that ANNMs outperformed GLRMs.ANNMs have a higher correlation coefficient(between predicted and target frequencies),lower Mo Es,and a closer-to-unity ratio(between predicted and target frequencies).These findings may increase prediction accuracy of design traffic overloading events and give road authorities more effective traffic management to protect bridges from load hazards.

Experimental research on the development of residual strain in seasonal frozen soil under freezing-thawing and impact type traffic loads

Vehicle load is among the main factors affecting the deformation of subgrade soil.In this research study,the concept of impact type traffic load is introduced to investigate the effects of vehicle load based on the dynamic stress and displacement time histories acquired from seasonal frozen subgrade soils.Using freezing-thawing and dynamic triaxial tests and considering the amplitude and loading sequence of impact type traffic load,the residual deformation characteristics of subgrade soil under impact type traffic loads and freezing-thawing cycles is studied.It was found that under impact type traffic load,the residual deformation of soils increased sharply as the amplitude of impact type traffic load increased.It was also found that the increase in the amplitude of impact type traffic load led to the increase of residual deformation in a scale of power and exponential function.The amplitudes of impact type traffic load affect the development stress-strain path of the residual strain.After the soil experienced the proper amount of pre-vibration of the light load,residual deformation decreased by 15%.After freezing-thawing,the residual strain of soil increased as the amplitude of the impact type traffic loads increased.Also,when the amplification effect of freezing-thawing on the residual strain was basically stable,the residual deformation increased by about 10%.The peak impact type traffic load had a large effect on soil deformation after the freezing-thawing process,leading to the observation that of the earlier the peaks,the stronger the effect of freezing-thawing.After the soil was subjected to preloading with a small load,the influence of the freezing-thawing cycles gradually stabilized.The results may be useful in preventing and controlling the risk of subgrade soil failure when construction takes place spring thaw periods.

Design of Bridge Expansion Joints with Perforated Dowels Under Impact Loading

The expansion joints are expected to have movement capacity, bearing capacity for static and dynamic loading, water-tightness, low noise emission and traffic safety. In particular, the failure due to impact loading is the main reason for the observed damages. The problem of dynamic behavior of the expansion joints is so complex that we shall focus our attention on the impact factor for vehicle load that is governed by traffic impact. In order to overcome this difficulty, the cantilever-toothed aluminum joint (finger joint) is one of the promising joints under impact loading. In this study, from the viewpoint of design methodology, numerical studies for impact behavior were conducted for aluminum alloy expansion joints with perforated dowels. The design impact factor for the expansion joints with the perforated dowels against traffic impact loading was examined by using numerical simulations.

Energy-balanced clustering protocol for data gathering in wireless sensor networks with unbalanced traffic load

Energy-efficient data gathering in multi-hop wireless sensor networks was studied,considering that different node produces different amounts of data in realistic environments.A novel dominating set based clustering protocol (DSCP) was proposed to solve the data gathering problem in this scenario.In DSCP,a node evaluates the potential lifetime of the network (from its local point of view) assuming that it acts as the cluster head,and claims to be a tentative cluster head if it maximizes the potential lifetime.When evaluating the potential lifetime of the network,a node considers not only its remaining energy,but also other factors including its traffic load,the number of its neighbors,and the traffic loads of its neighbors.A tentative cluster head becomes a final cluster head with a probability inversely proportional to the number of tentative cluster heads that cover its neighbors.The protocol can terminate in O(n/lg n) steps,and its total message complexity is O(n2/lg n).Simulation results show that DSCP can effectively prolong the lifetime of the network in multi-hop networks with unbalanced traffic load.Compared with EECT,the network lifetime is prolonged by 56.6% in average.

Lower Bound on de Bruijn Graphs Out-degree for Lower Traffic Load in Peer-to-peer Networks

Designers search for N-nodes peer-to-peer networks that can have O （1） out-degree with O （log2 N） average distance. Peer-to-peer schemes based on de Bruijn graphs are found to meet this requirement. By defining average load to evaluate the traffic load in a network, we show that in order to decrease the average load, the average distance of a network should decrease while the out-degree should increase. Especially, given out-degree k and N nodes, peer-to-peer schemes based on de Bruijn graphs have lower average load than other existing systems. The out-degree k of de Bruijn graphs should not be O（1） but should satisfy a lower bound described by an inequality κ^κ≥N^2, to ensure that the average load in peer-to-peer schemes based on de Bruijn graphs will not exceed that in Chord system.

Influence of erosion voids and traffic loads on buried large-diameter reinforced concrete pipes

Geotechnical centrifuge tests were conducted to examine the influence of invert voids and surface traffic loads on 1400 mm diameter reinforced concrete pipes buried with a shallow soil cover depth of 700 mm.Void formation beneath the pipe was simulated during centrifuge testing.The test results revealed that before void formation,the surface load directly above the middle of the pipe caused a significant increase in not only the circumferential bending moments but also the longitudinal bending moments,the latter of which was considerable and could not be ignored.Void formation beneath the middle of the pipe led to a reduction in both the circumferential bending moments and longitudinal bending moments at all measuring positions,i.e.,crown,springline,and invert.The most significant reduction occurred at the invert,and there was even a reversal in the sign of the invert longitudinal bending moment.A comparison was made between centrifuge tests with erosion voids and surface loads at different horizontal positions,which had a marked influence even when the positions differed by half a pipe length.Joint rotation played an important role in relieving large bending moments of pipe barrels in a jointed pipeline when the void and surface load were located at the joint.

Study on the Girder-End Displacement of a Suspension Bridge Based on Field Measurements

The load-response correlation is a great concern for the management and maintenance agency of bridges. Based on both the load test data and the long-term structural health monitoring data, this study aims to characterize the variation in the girder-end longitudinal displacement of a long-span suspension bridge, i.e., the Zhaoyun Bridge in Guangdong Province of China. The load test provides a valuable chance to investigate the structural deformation in high loading levels, while the structural health monitoring system records the real-time, in-site, and long-term measurements in the normal operational stage of bridges. During the load test, the movement direction of the main girder is found to depend on the relative position of the center of gravity of the girder and the loading vehicles. However, over the period of normal operation, the quasi-static displacement at the ends of the main girder along the bridge axis is dominated by the temperature variations, rather than the traffic loading. The temperature-induced deformation is considerable so it should be filtered out from the structural total responses to highlight the live load effects or the anomalies of the bridge. As a case study, the temperature-displacement baseline model of the Zhaoyun Bridge is established and then utilized to identify the erroneous measurements in the structural health monitoring system. This paper serves as a reference for the structural behavior interpretation and performance evaluation of similar bridges.

Adaptive local routing strategy on a scale-free network

Due to the heterogeneity of the structure on a scale-free network, making the betweennesses of all nodes become homogeneous by reassigning the weights of nodes or edges is very difficult. In order to take advantage of the important effect of high degree nodes on the shortest path communication and preferentially deliver packets by them to increase the probability to destination, an adaptive local routing strategy on a scale-free network is proposed, in which the node adjusts the forwarding probability with the dynamical traffic load （packet queue length） and the degree distribution of neighbouring nodes. The critical queue length of a node is set to be proportional to its degree, and the node with high degree has a larger critical queue length to store and forward more packets. When the queue length of a high degree node is shorter than its critical queue length, it has a higher probability to forward packets. After higher degree nodes are saturated （whose queue lengths are longer than their critical queue lengths）, more packets will be delivered by the lower degree nodes around them. The adaptive local routing strategy increases the probability of a packet finding its destination quickly, and improves the transmission capacity on the scale-free network by reducing routing hops. The simulation results show that the transmission capacity of the adaptive local routing strategy is larger than that of three previous local routing strategies.

SWN: An SDN Based Framework for Carrier Grade WiFi Networks

With the rapid growth of mobile data traffic and vast traffic offloaded from cellular network, Wi-Fi has been considered as an essential component to cope with the tremendous growth of mobile data traffic. Although operators have deployed a lot of carrier grade Wi-Fi networks, but there are still a multitude of arrears for nowadays Wi-Fi networks, such as supporting seamless handover between APs, automatic network access and unified authentication, etc. In this paper, we propose an SDN based carrier grade Wi-Fi network framework, namely SWN. The key conceptual contribution of SWN is a principled refactoring of Wi-Fi networks into control and data planes. The control plane has a centralized global view of the whole network, can perceive the underlying network state by network situation awareness(NAS) technique, and bundles the perceived information and network management operations into northbound Application Programming Interface(API) for upper applications. In the data plane, we construct software access point(SAP) to abstract the connection between user equipment(UE) and access point(AP). Network operators can design network applications by utilizing these APIs and the SAP abstraction to configure and manage the whole network, which makes carrier grade Wi-Fi networks more flexible, user-friendly, and scalable.

Vibration reduction analysis of new barriers in large model experiment

A large model box was developed in our experiment to study the vibration reduction effect.Five hydraulic highperformance actuators are arranged in the upper part of the model box.There is a time difference between adjacent actuators,which can simulate the train induced vibration.To reduce vibration a composite barrier is designed;the barrier consists of a honeycomb concrete canvas and PE polymer water bags.The concrete canvas can be mixed with water to produce a hydration reaction to form a structure with a certain hardness.By simulating different train speeds and loads,vertical vibration velocity,and acceleration before and after the barrier are compared and analyzed.The experimental results show that the new barrier can achieve a good vibration reduction effect.When the simulated train speed increases,the damping effect of the barrier is improved.At a speed of 180 km/h,an amplitude of 1.5 m after the barrier is found to be 48.6%lower than that before the barrier.Velocity decreases by 24.2%at 36 km/h and by 38.1%at 108 km/h.

Dynamic Vehicular Clustering Enhancing Video on Demand Services Over Vehicular Ad-hoc Networks

Nowadays,video streaming applications are becoming one of the tendencies driving vehicular network users.In this work,considering the unpredictable vehicle density,the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load,and the limited radio range of the employed communication scheme,we introduce the“Dynamic Vehicular Clustering”(DVC)algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks(VANET).The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls,inspired by the different features and the performance of the Long Term Evolution(LTE)-Advanced network.Vehicles are clustered together to form dynamically ad-hoc sub-networks included in the vehicular network.The goal of our clustering algorithm is to take into account several characteristics,such as the vehicle’s position and acceleration to reduce latency and packet loss.Therefore,each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.Based on the exceptional features of the LTE-Advanced network(small cells and wireless backhauls)the DVC algorithm is a promising scheme for video streaming services over VANET systems.Experiments were carried out with a virtual topology of the VANET network created with four clusters to implement the DVC algorithm.The results were compared with other algorithms such as Virtual Trust-ability Data transmission(VTD),Named Data Networking(NDN),and Socially Aware Security Message Forwarding(SASMF).Our algorithm can effectively improve the transmission rate of data packets at the expense of a slight increase in end-to-end delay and control overhead.

Energy-Efficient Resource Optimization for Massive MIMO Networks Considering Network Load

This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output(MIMO)network in which each base station(BS)is equipped with a large number of antennas and each base station(BS)adapts the number of antennas to the daily load profile(DLP).This paper takes into consideration user location distribution(ULD)variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO system.ULD variation is modeled by dividing the cell into two coverage areas with different user densities:boundary focused(BF)and center focused(CF)ULD.All cells are assumed identical in terms of BS configurations,cell loading,and ULD variation and each BS is modeled as an M/G/m/m state dependent queue that can serve a maximum number of users at the peak load.Together with energy efficiency(EE)we analyzed deployment and spectrum efficiency in our adaptive massive MIMO system by evaluating the impact of cell size,available bandwidth,output power level of the BS,and maximum output power of the power amplifier(PA)at different cell loading.We also analyzed average energy consumption on an hourly basis per BS for the model proposed for data traffic in Europe and also the model proposed for business,residential,street,and highway areas.

SPN-Based Performance Analysis of Multiple Users’Behaviors for SNS

With the rapid development of various applications of Information Technology,big data are increasingly generated by social network services(SNS)nowadays.The designers and providers of SNS distribute different client applications for PC,Mobile phone,IPTV etc.,so that users can obtain related service via mobile or traditional Internet.Good scalability and considerably short time delay are important indices for evaluating social network systems.As a result,investigating and mining the principle of users’behaviors is an important issue which can guide service providers to establish optimal systems with SNS.On the basis of analyzing the characteristics of social network system,this paper constructed a Stochastic Petri Net(SPN)model for describing the behaviors of three users for SNS.Moreover,the scalability of users’behaviors of SNS was studied by extending the SPN model of three users to the one of four users.Furthermore,average time delay was chosen as the performance index to evaluate the performance of these two constructed SPN models with Stochastic Petri Net Package(SPNP)6.0.For different parameters of number of connections,traffic load and buffer size,various trends and numerical results are derived thereby.The methodology of modeling and simulation in this paper can be further used to study the performance of SNS.

OpenFIow Based Flow Slice Load Balancing

Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.

Grouping Decision Algorithm for Dynamic Terminals in Random Access Networks

This paper proposes a grouping decision algorithm for random access networks with the carrier sense multiple access (CSMA) mechanism, which can balance the traffic load and solve the hidden terminal issue. Considering the arrival characteristics of terminals and quality of service (QoS) requirements, the traffic load is evaluated based on the effective bandwidth theory. Additionally, a probability matrix of hidden terminals is constructed to take into account the dynamic nature of hidden terminal relations. In the grouping process, an income function is established with a view to the benefits of decreasing the probability of hidden terminal collisions and load balancing. Then, we introduce the grey wolf optimization (GWO) algorithm to implement the grouping decision. Simulation results demonstrate that the grouping algorithm can effectively alleviate the performance degradation and facilitate the management of network resources.

Short-term traffic forecasting based on principal component analysis and a generalized regression neural network for satellite networks

With the rapid growth of satellite traffic, the ability to forecast traffic loads becomes vital for improving data transmission efficiency and resource management in satellite networks. To precisely forecast the short-term traffic loads in satellite networks, a forecasting algorithm based on principal component analysis and a generalized regression neural network （PCA-GRNN） is proposed. The PCA-GRNN algorithm exploits the hidden regularity of satellite networks and fully considers both the temporal and spatial correlations of satellite traffic. Specifically, it selects optimal time series of spatio-temporally correlated historical traffic from satellites as forecasting inputs and applies principal component analysis to reduce the input dimensions while preserving the main features of the data. Then, a generalized regression neural network is utilized to perform the final short-term load forecasting based on the obtained principal components. The PCA-GRNN algorithm is evaluated based on real-world traffic traces, and the results show that the PCA-GRNN method achieves a higher forecasting accuracy, has a shorter training time and is more robust than other state-of-the-art algorithms, even for incomplete traffic datasets. Therefore, the PCA- GRNN algorithm can be regarded as a preferred solution for use in real-time traffic forecasting for realistic satellite networks.

Application of semi-analytical finite element method to analyze asphalt pavement response under heavy traffic loads

Accurate assessment of the impact of heavy traffic loads on asphalt pavements requires a computational model which is able to calculate the response of the pavement fast and precisely. Currently the most finite element analysis programs based on traditional methods have various limitations. A specific program SAFEM was developed based on a semi-analytical finite element method to overcome the problems. It is a three-dimensional FE program that requires only a two-dimensional mesh by incorporating the semi- analytical method using Fourier series in the third dimension. The computational accuracy and efficiency of the program was verified by analytical verification previously. The experimental verification is carried out in this paper and the results show that the SAFEM is able to predict the mechanical responses of the asphalt pavement. Using the program SAFEM, the impact of heavy traffic loads was analyzed in terms of stress and strain dis- tribution, surface deflection and fatigue life. The results indicate that if the asphalt pave- ment is subjected to the heavy traffic load more, the thicknesses and stiffness of the pavement structural layers should be increased adequately in order to support the surface deflection, The compressive stress in asphalt binder course is relatively large and increases more significantly compared with that in the other asphalt layers when the axle load becomes larger. With comparison of the predicted fatigue life, the increase of the axle load will lead to the destruction of the asphalt pavement extremely easily.