Traffic Load Fluctuations Research Articles

Congestion Transition on Random Walks on Graphs.

The formation of congestion on an urban road network is a key issue for the development of sustainable mobility in future smart cities. In this work, we propose a reductionist approach by studying the stationary states of a simple transport model using a random process on a graph, where each node represents a location and the link weights give the transition rates to move from one node to another, representing the mobility demand. Each node has a maximum flow rate and a maximum load capacity, and we assume that the average incoming flow equals the outgoing flow. In the approximation of the single-step process, we are able to analytically characterize the traffic load distribution on the single nodes using a local maximum entropy principle. Our results explain how congested nodes emerge as the total traffic load increases, analogous to a percolation transition where the appearance of a congested node is an independent random event. However, using numerical simulations, we show that in the more realistic case of synchronous dynamics for the nodes, entropic forces introduce correlations among the node states and favor the clustering of empty and congested nodes. Our aim is to highlight the universal properties of congestion formation and, in particular, to understand the role of traffic load fluctuations as a possible precursor of congestion in a transport network.

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.

Cyclical Trends of Network Load Fluctuations in Traffic Jamming

The transport of information packets in complex networks is a prototype system for the study of traffic jamming, a nonlinear dynamic phenomenon that arises with increased traffic load and limited network capacity. The underlying mathematical framework helps to reveal how the macroscopic jams build-up from microscopic dynamics, depending on the posting rate, navigation rules, and network structure. We investigate the time series of traffic loads before congestion occurs on two networks with structures that support efficient transport at low traffic or higher traffic density, respectively. Each node has a fixed finite queue length and uses next-nearest-neighbour search to navigate the packets toward their destination nodes and the LIFO queueing rule. We find that when approaching the respective congestion thresholds in these networks, the traffic load fluctuations show a similar temporal pattern; it is described by dominant cyclical trends with multifractal features and the broadening of the singularity spectrum regarding small-scale fluctuations. The long-range correlations captured by the power spectra show a power-law decay with network-dependent exponents. Meanwhile, the short-range correlations dominate at the onset of congestion. These findings reveal inherent characteristics of traffic jams inferred from traffic load time series as warning signs of congestion, complementing statistical indicators such as increased travel time and prolonged queuing in different transportation networks.

Dynamic Resource Scaling for VNF Over Nonstationary Traffic: A Learning Approach

Software defined networking (SDN) and network function virtualization (NFV) are key enablers for service-level customized network slicing in fifth generation (5G) core networks. Network slices are required to be isolated from each other in terms of service performance with traffic load fluctuations. In this article, the virtual network function (VNF) scalability issue is studied to meet the quality-of-service (QoS) requirement in the presence of nonstationary traffic, through joint VNF migration and resource scaling. A traffic parameter learning method based on change point detection and Gaussian process regression (GPR) is proposed, to learn traffic parameters in a fractional Brownian motion (fBm) traffic model for each stationary traffic segment within a nonstationary traffic trace. Then, the time-varying VNF resource demand is predicted from the learned traffic parameters based on an fBm resource provisioning model. With the detected change points and predicted resource demands, a VNF migration problem is formulated as a Markov decision process (MDP) with variable-length decision epochs, to maximize the long-term reward integrating load balancing, migration cost, and resource overloading penalty. A penalty-aware deep Q-learning algorithm is proposed to incorporate awareness of resource overloading penalty, with improved performance over benchmarks in terms of training loss reduction and cumulative reward maximization.

Dynamic analysis of concrete pipes under the coupled effects of traffic load and groundwater level fluctuations

AbstractFluctuations in the groundwater level make the working conditions of concrete pipes below the groundwater level more complex than those of concrete pipes above the groundwater level. This paper describes the application of a three‐dimensional (3‐D) refined finite element (FE) model to the analysis of a buried concrete pipe subjected to the coupled effects of traffic load and groundwater level fluctuations. First, the dynamic responses of the concrete pipes buried in dry soil were investigated with a full‐scale test and an FE model. The results show that the FE model predicted results similar to those observed in field pipes. Then, the dynamic responses based on the numerical results of pipes buried in dry soil under a traffic load and those of pipes buried in saturated soil under the coupled effects of a traffic load and groundwater level fluctuations were compared. Finally, a parametric analysis of the effects of the void ratio, permeability coefficient, and fluctuation period in the groundwater level in relation to the dynamic responses of the pipes was conducted. The results show that the mechanical behaviors of the pipes in dry soil were substantially different from those of pipes in saturated soil. Compared with pipes in dry soil under a traffic load, the stresses at the crown, springline, and invert of the bell under the coupled effects of the traffic load and groundwater level fluctuations were lowered by 44.8%, 52.0%, and 50.3%, respectively, while those of the spigot were lowered by 42.0%, 50.3%, and 49.6%, respectively. The maximum principal stress and the vertical displacement were proportional to the void ratio and the permeability coefficient, while their relationship to the groundwater level fluctuation period was less straightforward.

Drastic Energy Reduction With gDTX in Low Cost 5G Networks

Base station (BS) sleep modes handle the progressive deactivation of unused hardware components and bring a promising solution to the increasing energy bill and environmental concerns. Taking advantage of the 5G ultra-lean design and spaced synchronization signals, we propose a novel gDTX mode (for next-generation discontinuous transmission), based on flexible duty cycling . First, an inactive period enables the BS to enter deep sleep state for some tens of milliseconds, even if users are requesting service. We show that adapting the inactivity duration to the daily traffic load fluctuations provides significant energy reduction, reaching half of the time more than 45% gain in suburban environment and 78% in rural area. Second, an active period maintains some cell capacity and normal signaling, rendering the BS always available, even if not always on. Questioning the feasibility of gDTX regarding real-time delay-non-tolerant voice traffic, we analyze its impact on the overall jitter, end-to-end delay and estimated mean opinion score. We evidence that sleeping 60 ms every 80 ms while sustaining acceptable voice quality is not contradictory in most network conditions, for light to moderate loads. The proposed gDTX cycle definitely opens new perspectives on energy reduction, targeting primarily developing countries where powering BSs is still a priority to deploy reliable mobile services.

Dynamic switching off algorithms for pico base stations in heterogeneous cellular networks

Abstract The densification of pico base stations (PBSs) in heterogenous cellular networks (Hetnets) causes redundant energy consumption of the whole network during low traffic periods. In order to address this problem, we take advantage of the traffic load fluctuation over time and area to adapt the necessary resource to the actual traffic demand by introducing sleep mode to the PBSs. To achieve this target, we propose two centralized algorithms (i.e., the heuristic algorithm and the progressive algorithm) in this paper to dynamically switch off the unnecessary PBSs, both of which can track the traffic variation well. We design a utility function of some key factors considered particularly for PBSs in Hetnets. These algorithms rely on the utility function to switch off the redundant PBSs, enabling the working mode of all PBSs be reconfigured periodically. The progressive algorithm is proposed to overcome the inefficiency of the heuristic algorithm. The simulations demonstrate that the execution time of the progressive algorithm is at most one third of that of the heuristic algorithm, which enables the network to respond to the traffic variation more promptly. Besides, the progressive algorithm can switch off more PBSs than the heuristic algorithm while slightly affects the network blocking probability, which indicates that the progressive algorithm has a better potential to save energy. Moreover, simulations also reveal that some key parameters all have nonnegligible influence on the performance of our algorithms. These parameters should be tuned well to trade spare network resource for energy saving.

A Separation Architecture for Achieving Energy-Efficient Cellular Networking

Energy-efficient cellular networking has received considerable attention recently in hope of finding novel solutions to reduce network energy consumption. In this paper, a case study is conducted for a separation architecture in which two types of base stations (BSs) simultaneously serve a geographic area, one for providing reliable coverage and the other for handling user traffic. Based on a postulated BS power model, we demonstrate that the separation architecture, when replacing the conventional macro BS with a light-weight coverage BS (CBS) and multiple traffic BSs (TBSs), significantly reduces the overall energy consumption of a cellular network. Numerical results suggest that the separation architecture can usually reduce the energy consumption by 50% or even more compared with conventional macro BS. We then investigate dynamic TBS adaptation (i.e., BS switching on/off), based on traffic load fluctuations. Closed-form results are derived to suggest approximately linear adaptation of the intensity of TBSs in the separation architecture. Moreover, we consider the optimal deployment of TBSs over a long time scale, and derive closed-form results for the optimal intensity of TBSs for a given user intensity. Extensive simulations demonstrate that the proposed separation architecture is a promising solution to enable energy-efficient cellular networking.

Traffic-Aware Dynamic Frequency Band Allocation Scheme for OFDMA System

The traffic load in a cellular network is typically unbalanced, changing both in the time domain and the spatial domain due to user mobility and activities. In this letter, a traffic-aware dynamic frequency band allocation scheme for OFDMA system is proposed. It is shown that the proposed scheme improves the network throughput and the spectral efficiency without increasing the cost of signaling interaction by dynamically allocating sub-bands in multi-cell network according to the traffic load fluctuations.

동적 레인 제어방식을 적용한 에너지 절감형 광 이더넷 시스템의 성능분석

In this paper, we propose a dynamic lane control scheme with a traffic predictor module and a rate controller for reconciling with commercial optical PHY modules in energy efficient optical Ethernet systems. The commercial high speed optical Ethernet system capable of 40/100Gbps employs 4 or 10 multiple optical transceivers over WDM or multiple optical links. Each of the transceivers is always turned on even if the link is idle. To save energy, we propose the dynamic lane control scheme. It allows that several links may be entirely turned off in a low traffic load and frames are handled on the remaining active links. To preserve the byte order even if the number of active links may be changed, we propose a rate controller to be sat on the reconciliation sublayer. The main role of the controller is to insert null byte streams into the xGMII of inactive lanes. For the PHY module, the null input streams corresponding to inactive lanes will be disregarded on inactive PMDs. It is very handy to implement the rate controller module with MAC in FPGA without any modification of commercial PHYs. It is very crucial to determine the number of active links based on the fluctuated traffic load, we provide a simple traffic predictor based on both the current transmission buffer size and the past one with different weighting factors for adapting to the traffic load fluctuation. Using the OMNET++ simulation framework, we provide several performance results in terms of the energy consumption.

Dynamics of traffic noise in a tropical city Varanasi and its abatement through vegetation

Noise level monitoring and its reduction with different width and height of vegetation belt were studied in the Varanasi city. Noise level monitoring of the Varanasi city revealed the fact that area category A (without vegetation) was highly polluted as compare to area category B (with vegetation) having less fluctuation of traffic load. Four plant species Putranjeva roxburghi, Cestrum nocturnum, Hibiscus rosasinensis and Murraya peniculata were tested for noise reduction study at different frequencies. Experiment revealed the fact that H. rosasinensis reduced noise highest at both low and high frequencies (100-500 Hz, 22 dB and 2.5-6.3 KHz 26 dB), followed by M. peniculata (100-500 Hz, 18 dB and 2.5-6.3 KHz 20 dB), P. roxburghi (100-500 Hz 15 dB and 2.5-6.3 KHz 17 dB) and C. nocturnum (100-500 Hz 9 dB and 2.5-6.3 KHz 14 dB). Significance of vegetation belt in noise reduction was established with multiple regression models.

Modeling end-to-end QoS management and real time agreement protocols for resource reservation for multimedia mobile radio network

Wireless networks’ Operators still face the dual face problem of end to end resource allocation management wile making efficient use of bandwidth. Relative considerations include user mobility, traffic characteristics, Quality of Service (QoS) parameters (throughput, delay, jitter, etc.). The satisfaction of the user depends on subjective parameters related to the rendering of the requested services (end-to-end quality of service). In order to accommodate these parameters, prescriptions have been formulated by the IETF within the framework of the IntServ/DiffServ group which targets network QoS control. The call admission control (CAC) is essential within this mobile communication architecture because the network resources are limited. The purpose of this work is to specify traffic threshold parameters and the constraints in terms of QoS for a resource allocation based on a call admission control mechanism in a mobile network. In our approach, this mechanism takes place in two stages : the first stage at the level of the New Call acceptation capability by Cell registered at mobile radio Level Agreement Service (SLA), where user mobility is considered as being a major constraint for call acceptance. The second stage takes place at the DiffServ operator network level. QoS acceptance is defined by the SLA contract specifying the parameters of the different levels of acceptance. At a global level, new call or handover call acceptance is based on a collective and consensual decision between the different participating networks. Such a consensus aims at taking a consistent decision to reserve resources according to one of the levels of service predefined by the caller SLA. Then allowing the caller to renegotiate the level of service QoS according to traffic load fluctuation, or to negotiate new resources for new applications requested during the session. The other participating networks can also initiate a renegotiation for the same reasons.

Efficient Resource Allocation for Policy-Based Wireless/Wireline Interworking

This paper proposes efficient resource allocation techniques for a domain-based wireless/wireline interworking architecture. Resource allocation is driven by the service level agreement (SLA). Each wireless domain can freely choose its internal resource management schemes to guarantee the customer access SLA (CASLA), while the border-crossing traffic is served by a DiffServ/MPLS core network according to the transit domain SLA (TRSLA). Specifically, we propose an engineered priority scheme for a cellular wireless domain, where the CASLA for each service class is met with efficient resource utilization and the interdomain TRSLA bandwidth requirement can be obtained conveniently. In the transit domain, the traffic load fluctuation from upstream access domains is tackled with an inter-TRSLA resource sharing technique, where the spare capacity from underloaded TRSLAs can be exploited by the overloaded TRSLAs to improve resource utilization.

Lightweight proactive queue management

The quest for better resource control has been the driving force behind Active Queue Management (AQM) research. Random Early Detection (RED), the defacto standard and its variants have been proposed as simple solutions to the AQM problem. These approaches, however, are known to suffer from problems like parameter sensitivity and inability to capture input traffic load fluctuations accurately, thereby resulting in instability. This paper presents a proactive queue management algorithm called PAQMAN that captures input traffic load fluctuations accurately and regulates the queue size around the desirable level. PAQMAN draws from the predictability in the underlying traffic by employing the Recursive Least Squares (RLS) algorithm to forecast the average queue size over the next prediction interval using the average queue size information of the past intervals. The packet drop probability is then computed as a function of this predicted average queue size. The performance of PAQMAN has been evaluated and compared against existing AQM schemes through ns-2 simulations that encompass varying network conditions for networks comprising of single as well as multiple bottleneck links. Simulation results demonstrate that PAQMAN maintains a relatively low queue size, while at the same time achieving high link utilization and low packet loss. Moreover, the computational overhead of PAQMAN is negligible (lightweight) which further justifies its use.

Performance analysis for the dynamic virtual path bandwidth control method in ATM networks

AbstractBroadband ISDN (integrated services digital network) should provide various kinds of communication services for multimedia traffic, including voice, computer data, still picture and motion video, and an ATM (asynchronous transfer mode) technology is expected to satisfy those demands. In ATM networks, a VP (virtual path) concept is introduced for simplifying the network resource management. However, if the bandwidth of each VP is fixed, it cannot absorb traffic load fluctuation. In this case, it is likely to happen that one VP has no remaining bandwidth while other VPs on the same physical link have free capacities. Another extremity is that a VP is not introduced, and that all VCs along the same physical link share the whole bandwidth of the link. This can achieve an efficient use of the link, but it apparently requires complicated call set‐up procedures.In this paper, we propose a new dynamic VP bandwidth control method, in which the bandwidth allocated to each VP is dynamically changed according to traffic fluctuation. More specifically, in the case that multiple VPs are multiplexed on the same link between two nodes, when the utilization of some VP is increased, that VP requests an additional bandwidth. When the traffic load becomes low and the utilization of a VP is decreased, a part of the assigned bandwidth is released. We consider two methods for this purpose; one is the basic method in which the bandwidth increase request is issued after the VP bandwidth is exhausted. The other is the look‐ahead method where the bandwidth increase is requested in advance before the bandwidth starvation. An approximate analysis for the above methods is provided, and the validation of its accuracy is assessed by comparing with simulation results. Through numerical examples, we show that our methods can provide performance improvement in terms of call loss probabilities of each VP.