Traffic Aggregation Research Articles

Study on the attractiveness of social e-commerce platforms from the consumers’ perspective based on the AISAS model

The traditional e-commerce’s traffic dividend is gradually declining, while social e-commerce as a new business model has attracted numerous enterprises to jump into by virtue of the advantages of viral traffic aggregation and efficient conversion. How to improve the core competitiveness and stand out from the Red Ocean battle of traffic competition is of great significance for the healthy and sustainable development of social e-commerce platforms. In view of this, this study focuses on the issues related to the attractiveness of social e-commerce platforms from the consumer’s perceptive, with the aim of providing theoretical support for social e-commerce platforms to enhance their core competitiveness and formulate relevant development strategies and decision-making mechanisms. First, four key factors affecting the attractiveness of social e-commerce platforms based on the AISAS model are proposed: the ability to attract consumers to access, promote consumers’ purchase conversion, maintain consumers’ platform loyalty, and attract to share experiences. Second, an attractiveness assessment model for social e-commerce platform including four secondary indicators and corresponding 14 tertiary indicators is constructed by using Analytic Hierarchy Process, and an arithmetic example is demonstrated. Finally, management suggestions to enhance the attractiveness of social e-commerce platforms are presented.

Dynamic Link Metric Selection for Traffic Aggregation and Multipath Transmission in Software-Defined Networks

Software-defined networks (SDNs) are expanding their presence beyond laboratories, campus networks, ISPs, and data centre networks, moving into various domains. Although originally designed for campus networks, SDNs face scalability challenges, especially with the use of OpenFlow. Addressing these challenges requires innovative traffic management mechanisms to efficiently handle the growing number of connected devices and the increasing volume of traffic from various types of applications. This article proposes an innovative method for link weight selection that incorporates multipath transmission and flow aggregation in the SDNs. This novel approach improves resource utilization in two key ways. First, it involves the preservation of bandwidth during congestion. Second, it minimizes internal resource usage, as illustrated by a reduction in the number of table entries in switches. Resources undergo optimization through the introduction of a novel mechanism for flow aggregation. This novel mechanism, coupled with multipath transmission, enables adaptive responses to dynamic changes in network conditions. The aggregation process leads to a reduced number of flow entries in the core switches compared to the conventional operation of OpenFlow. The proposed scenarios for link weight allocation allow for a reduction in the number of entries in the core switches by up to 99%. The application of the proposed method also results in an increase of 58% in traffic transmission.

Adaptive quality of service for packet loss reduction using OpenFlow meters.

Quality of Service (QoS) is a mechanism used in computer networks to prioritize, classify, and treat packets differently based on certain criteria. This helps the switching devices to schedule and reorder packets if there is congestion in the network. Edge routers experience high traffic congestion as a result of traffic aggregation from the internal network devices. A router can have multiple QoS classes configured, and each class could experience traffic at various rates. However, when a QoS class is underperforming or needs more bandwidth, some bandwidth can be borrowed or leased out to another QoS class to ensure the link is utilized to maximum capacity and the highest throughput is achieved. This article proposes a bandwidth allocation and distribution algorithm that purely uses the flow statistics from the OpenFlow switches to allocate bandwidth to different QoS classes optimally based on their current requirement. The algorithm does not guarantee in advance that the packet loss will be minimized but does guarantee the initial minimum bandwidth allocation. It adjusts the flows' rates with the aim to increase their current throughput. The algorithm uses the Software Defined Networking (SDN) controller's flow monitoring component to query the flow statistics from the switch to first approximate the traffic flow rate and then calculate the optimal bandwidth values to assign to each QoS class. The proposed algorithms will be applied to certain switches in the path with the assumption that all the switches are OpenFlow compatible. The algorithm's performance was compared with the Adaptive Quality of Service (AQoS) algorithm over various traffic scenarios. The results show that the proposed algorithm achieves an average of 9% performance gain compared to the AQoS algorithm.

Demand Clustering and Spectrum Allocation (DCSA) problem in P2MP network with time-varying traffic

In this paper, the Demand Clustering and Spectrum Allocation (DCSA) problem in a point-to-multipoint (P2MP) network with time-varying traffic is studied. This article introduces several heuristic techniques that can be applied to traffic aggregation for P2MP optical network architectures employing digital subcarrier multiplexing. Based on the transmitter constraint, the algorithms assign individual subcarriers (SCs) to receiving nodes with uncorrelated traffic profiles. The simulation results show that the proposed algorithms outperform the clustering methods.

From TikTok Hongxing Erke Live Marketing to See How Live Culture Shaped Consumer Groups

In recent years, with the development of mobile Internet, mobile live broadcasting platforms, social media and short video platforms have emerged one after another, and the "live +" model with live broadcasting as the core has gradually become a new trend in the development of the industry. This new advertising communication mode not only brings the change of traffic aggregation, content production and communication mode, but also subverts the traditional advertising communication mode to a certain extent. Therefore, the analysis of live broadcasting culture is extremely important for us to study the new media marketing theory in the information age. TikTok live broadcasting platform is an important part of domestic live broadcasting culture. Starting from TikTok live broadcasting will better help the author to study this issue. Therefore, this paper takes Hongxing Erke, a brand that has created new marketing methods on TikTok live streaming platform, as an example, analyzes the reasons for the rise of live streaming culture and the impact of live streaming culture on advertising communication effect, discusses the advantages and existing problems of live advertising communication mode, and puts forward countermeasures. It provides reference for the development of live advertising in the information age to promote the improvement of new media marketing theory.

Modelling, Simulation, and Performance Analysis of Intra-Vehicular Heterogeneous Networks

Vehicles today use a variety of network segments operated by different technologies and protocols within the car (CAN, LIN, Automotive Ethernet, MOST, FlexRay, etc.) to exchange data between different control modules, sensors, and actuators. The exchange of information between other network domains (heterogeneous networks) is enabled through various interconnection points called gateways/bridges. The resulting performance depends on its interconnection structure, network segment traffic aggregation scheme, and medium access technique. Although protocols such as CAN, LIN, FlexRay, and Ethernet have been used in network design for some time, performance modeling and analysis are still needed given the variety of traffic types and sources, new application limitations, and especially the lack of formal verification of network performance for different network scenarios and configurations. This paper presents an end-to-end throughput and delay performance analysis for a reference intra-vehicular network scenario. These models have been validated through simulations in which high correlation values were obtained from 98.7400 to 99.9999, with a low mean square error. The validation cases show that for different LIN, CAN, and Ethernet network configurations, the performance threshold values defined for most current vehicle applications are preserved. However, if the network configuration is modified, the proposed analytical models can be used to formally verify the corresponding performance and delay changes and thus validate whether or not the application requirements are met.

Optical channel aggregation based on modulation format conversion by coherent spectral superposition with electro-optic modulators

Spectrally efficient modulation formats become essential for optical network scaling as the demand for routed data streams exceeds the present wavelength-division multiplexing systems’ throughput. However, achieving high spectral efficiency at high data rates requires complex and bandwidth-intensive electronics. In this study, we propose an all-optical aggregation scheme that combines multiple low spectral efficiency optical wavelength channels from an optical frequency comb based transmitter into fewer channels with higher spectral efficiency. Our method utilizes coherent spectral superposition and optical vector summation, eliminating the need for optical nonlinearities and relying on linear signal processing with an electro-optic modulator. By adjusting the phase of the radio frequency signal driving the modulator, we can easily achieve the required optical phase tuning for vector addition in the I-Q plane. Through experimental demonstrations, we show that the proposed approach enables the generation of 10 GBd PAM-4 and 10 GBd quadrature phase shift keying (QPSK) signals by aggregating two 10 GBd binary phase shift keying signals. Similarly, we aggregate two 10 GBd QPSK signals into one 10 GBd quadrature amplitude modulation-16 (QAM-16) signal. The experiments employ both conventional and sinc-shaped Nyquist signals. Our in-line, all-optical aggregation concept significantly enhances operational capacity while reducing complexity. It offers a promising solution for realizing flexible integrated optical transmitters for advanced modulation format signals using lower-quality electronics. Additionally, it aligns with the requirements of future dynamically reconfigurable optical networks that leverage spectral traffic aggregation. Given its reliance on linear signal processing with an electro-optic modulator, the integration of the method into any integrated photonic platform is straightforward.

Dedicated Path Protection With Wavelength Aggregation in 5G Packet-Optical Xhaul Access Networks

Packet-optical xHaul transport networks are a promising solution for assuring low-cost connectivity between a large number of antennas, located at remote sites, and a central site (hub), in which traffic is gathered and baseband processing is performed, in dense 5G radio access networks (RANs). The demand for fiber connections in such networks can be reduced by means of optical add-drop multiplexers (OADMs), which allow to aggregate traffic from a number of remote sites onto a single optical transmission path. An important issue here is the protection of transmission paths since the failure of a single link may result in the loss of connectivity of a number of antennas. In this work, we focus on the problem of planning a survivable 5G packet-optical xHaul access network, in which the remote sites are connected with the hub by means of disjoint primary-backup paths. The network scenario is based on a passive wavelength division multiplexing (WDM) system in which the maximum transmission distance depends on the number of OADMs installed on the transmission path. In the solution proposed, network survivability is achieved using a dedicated path protection with wavelength aggregation (DPPWA) mechanism. The network planning problem is modeled and solved as an integer linear programming (ILP) problem. Numerical results indicate, among others, that cost savings of between 20%–40% can be achieved in lower traffic load scenarios due to the traffic aggregation by means of OADMs, and that the savings increase with the cost of dark fiber lease.

All-optical aggregation and de-aggregation between OOK, QPSK and 8QAM signals based on nonlinear effects

An all-optical aggregation and de-aggregation scheme between on–off keying (OOK) signals, quadrature phase shift keying (QPSK) signals and 8-ary quadrature amplitude modulation (8QAM) signals is proposed and numerically simulated based on nonlinear effects in the high nonlinear fiber (HNLF). In the de-aggregation processing, the input 30 Gbit/s 8QAM signal is firstly de-aggregated into one 20 Gbit/s QPSK signal and one 10 Gbit/s binary phase shift keying (BPSK) signal by deploying self-phase modulation (SPM), cross-phase modulation (XPM), four-wave mixing (FWM) and parameter amplification (PA) effects. One continuous optical carrier can be extracted from the converted BPSK signal by designing a feed-forward based modulation stripping configuration. The converted OOK signal can be obtained through vector superposition between the extracted optical carrier and the converted BPSK signal. In the aggregation processing, the converted 20 Gbit/s QPSK signal and the 10 Gbit/s OOK signal are fed to another HNLF and aggregated into one 30 Gbit/s 8QAM signal again by utilizing XPM and PA effects. Moreover, the aggregated 8QAM signal keeps the same wavelength and information integrity as the input 8QAM signal. the Error vector magnitude (EVM) and the bit error ratio (BER) for the 8QAM signal before and after aggregation and de-aggregation are measured to evaluate the scheme performance. The proposed all-optical aggregation and de-aggregation scheme for the advanced and simple modulation formats can be applied at the intermediate network node (INN) to solve the network traffic aggregation and de-aggregation with different modulation formats.

Mathematical Framework for Mixed Reservation- and Priority-Based Traffic Coexistence in 5G NR Systems

Fifth-generation (5G) New Radio (NR) systems are expected to support multiple traffic classes including enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC) at the same air interface. This functionality is assumed to be implemented by utilizing the network slicing concept. According to the 3rd Generation Partnership Project (3GPP), the efficient support of this feature requires statistical multiplexing and, at the same time, traffic isolation between slices. In this paper, we formulate and solve a mathematical model for a class of Radio Access Network (RAN) slicing algorithms that simultaneously include resource reservation and a priority-based service discipline allowing us to incur fine granularity in the service processes of different traffic aggregates. The system is based on a queueing model and allows parametrization by accounting for the specifics of wireless channel impairments. As metrics of interest, we utilize K-class session drop probability, K-class session pre-emption probability, and system resource utilization. To showcase the capabilities of the model, we also compare performance guarantees provided for URLLC, eMBB, and mMTC traffic when multiplexed over the same NR radio interface. Our results demonstrate that the performance trade-off is dictated by the offered traffic load of the highest priority sessions: (i) when it is small, mixed reservation/priority scheme outperforms the full reservation mechanism; (ii) for overloaded conditions, full reservations provides better traffic isolation. The mixed strategy is beneficial to traffic aggregates with short-lived lightweight sessions, such as URLLC and mMTC, while the reservation only scheme works better for elastic eMBB traffic. The most important feature is that the mixed strategy allows resource utilization to be improved up to 95%, which is 10–15% higher compared to the reservation-only scheme while still providing isolation between traffic types.

Capacity and flexibility improvement of traffic aggregation for fixed 5G: Key enabling technologies, challenges and trends

As the emergence of various high-bandwidth services and the requirements to support 5G/Wi-Fi 6 wireless networks, the next generation fixed networks, i.e. F5G, are expected to be realized in the 5G era. F5G is endowed with new characteristics, including ultra-high bandwidth, all-optical connections and optimal service experience. With the prospect of optical-to-everywhere, optical technologies are used for mobile front-haul, mid-haul, and back-haul. Optical access networks would play an important role in F5G to support radio access network and fixed access network. Low-latency PON is a key for cost effective-haul traffic aggregation. In terms of signal transmission, intensity modulation direct-detection (IM-DD) is a promising scheme due to its simple architecture. The fundamental challenge associated with direct-detection is the disappearance of the transmitted signal's phase. In access network, the flexibility and low latency are the two key factors affecting service experience. In this article, we review the evolution of PONs and the challenges of current PONs in detail. We analyze key enabling digital signal processing (DSP) techniques, including detection linearization for direct-detection and simplified coherent detection, adaptive equalizers, digital filer enabled flexible access network and low-latency inter-ONU communications. Finally, we discuss the developing trends of future optical access networks.

Efficient Load Balancing for Heterogeneous Radio-Replication-Combined LoRaWAN

LoRa wide area network (LoRaWAN), an emerging IoT protocol, has been popularized in large-scale applications, given its long-range and low-power properties. Hitherto, there is no appropriate traffic model for LoRaWAN to estimate the heterogeneous arriving traffic at the network server cluster (NSC). Inefficient computation power planning or even processing failure might be further caused. Radio replication, commonly existed in the arriving traffic at NSC in LoRaWAN, also causes difficulty estimating the makespan (i.e., mean processing time in NSC). To overcome the abovementioned limitations, a heterogeneous radio-replication-aware traffic aggregation model is proposed to estimate the arriving traffic for LoRaWAN. In addition, a radio-replication-combined supermarket model (RRC-SM), on top of HTAM, is proposed to achieve load balancing among servers in LoRaWAN. Furthermore, a nondominated sorting genetic algorithm based on multiobjective optimization is developed to simultaneously minimize cost and latency on NSC. Experiments reveal that the proposed HTAM and RRC-SM agree well with the simulation outcome. Under the arriving traffic estimated as 6.16 erlangs with four radio replications of each arriving packet on average, the proposed RRC-SM provides more than 50% reduction on the total processing latency and 75% reduction on the number of servers in NSC than other existing models.

IMSI Sharing-Based Dynamic and Flexible Traffic Aggregation for Massive IoT Networks

International mobile subscriber identity (IMSI) sharing-based aggregated communication aims to connect multiple Internet of Things (IoT) devices to the mobile operator’s core network over the same subscriber line. IoT devices with low data rates and long data sending intervals are first grouped together and assigned the same subscriber identity. They then take turns to perform their data exchanges using the same cellular connection, yielding huge savings in resource (e.g., number of active bearers) usage. Current solutions however do not consider different device traffic characteristics, the flexibility in traffic patterns, and dynamic network environments where new IoT devices join and existing ones leave the network. In this article, we study the problem of the grouping of IoT devices that will share the same subscriber identity based on their traffic patterns which can also be slightly shifted. We also study the efficient regrouping of these devices as the set of devices in the network changes. We first solve the optimal grouping and traffic aggregation problem for the initial and updated network states using integer linear programming (ILP). Then, to avoid the high complexity of ILP solutions, we develop heuristic-based solutions. Through extensive simulations, we show that heuristic-based algorithms can provide close to optimal ILP-based results while running much faster. The results also show that shifting-based grouping provides more resource saving compared to no-shifting-based aggregation and the proposed solution for dynamic environments can maintain the resource saving with a much lower complexity.

Provision of Energy- and Wavelength-Efficient Traffic Grooming for Sparse WDM-Enabled Distributed Satellite Cluster Networks

Sparse wavelength division multiplex (WDM) enabled distributed satellite cluster networks (DSCNs) have emerged as a promising architecture to accommodate future extensive applications. Networking of the DSCNs will face the challenges of explosively increasing traffic requests, the limited number of wavelengths, and restricted energy provisioning. To address these issues, a novel approach, the two-phase traffic grooming based on the matching algorithm (TPTG_MA), is proposed in this paper. To analyze resource utilization, energy- and wavelength- minimized models are established. After that, we develop the MA to tackle the traffic grooming problem in two phases, including the first phase for traffic aggregation and sub-wavelength assignment (TAASA) and the second phase for sub-wavelength grooming (SG). To evaluate the performance of the proposed TPTG_MA, the direct lightpath grooming (DLG) heuristic and the genetic algorithm (GA) are simulated for comparison. The results demonstrate that the TPTG_MA and DLG_GA outperform TPTG and DLG in the average wavelength utilization ratio (AWUR), the energy consumption saving (ESC), and the blocking probability. Compared with the DLG_GA, the TPTG_MA achieves at most 18% and 23% higher AWUR in the 12-node and 22-node topologies, respectively. In addition, the TPTG_MA can actualize at most 10% ECS improvement over the DLG_GA. At last, the influence of the network size, the number of wavelengths, and the number of hops are discussed.

A Novel Framework for Generating Personalized Network Datasets for NIDS Based on Traffic Aggregation.

In this paper, we addressed the problem of dataset scarcity for the task of network intrusion detection. Our main contribution was to develop a framework that provides a complete process for generating network traffic datasets based on the aggregation of real network traces. In addition, we proposed a set of tools for attribute extraction and labeling of traffic sessions. A new dataset with botnet network traffic was generated by the framework to assess our proposed method with machine learning algorithms suitable for unbalanced data. The performance of the classifiers was evaluated in terms of macro-averages of F1-score (0.97) and the Matthews Correlation Coefficient (0.94), showing a good overall performance average.

Enabling Optical Network Technologies for 5G and Beyond

We review a series of innovative optical network technologies for 5G and beyond mobile networks, enabling high-throughput mobile any-haul (x-haul) via wavelength-division multiplexing, bandwidth-efficient mobile front-haul via hybrid digital-analog radio-over-fiber, Shannon-limit-approaching long-haul transmission for core networks via advanced coding and probabilistic constellation shaping, low-latency 50-Gb/s passive optical network for cost-effective x-haul traffic aggregation, and service-enabling optical transport network capable of bandwidth-guaranteed network slicing with fine granularity. The vision and main application scenarios of the 5^th generation fixed network (F5G) are also discussed. With its capability to support enhanced fixed broadband, guaranteed reliable experience, full fiber connection, energy-efficient broadband communication, real-time broadband communication, and harmonized communication and sensing, F5G is well positioned to not only support mobile networks, but also complement them to jointly meet the ever-increasing communication demands in the era of 5G and 6G.

THE CALCULATING METHOD OF NGN ACCESS NODE CHARACERISICS WHEN SERVICING VOICE AND DATA TRAFFIC

Access nodes of NGN networks provide traffic aggregation to various network services and its transfer to the transport layer, which allows calling such networks multiservice.1;2. These networks are used to simultaneously transmit voice, video, and data presented in the from of standard packets. At the same time, network services provide an unlimited set of telecommunication services with specified characteristics of quality of service.1;2 The selected technology of information distribution in the NGN determines the degree of complexity of access nodes and, of course, affects the quality of information exchange service between user terminals. One of the ways to ensure a given level of quality of service for each of the services is the introduction of priority service for certain traffic flows. Introducing priorities for packets is an effective way to manage the size of queues and the time spent in it. When a high-priority packet is received, a packet with a lower priority is either interrupted (absolute priority) or a high priority packet becomes the beginning of the packets queue (relative priority). In this paper, we study the characteristics of NGN access nodes as a two priority queuing system with a limited expectation.5. Formulas for calculating the probability of loss of speech packets, as well as data packets, and other characteristics of the access node have been proposed. The NGN's access nodes provide aggregation of traffic to various services directed by the Public Switched Telephone Network (PSTN) and its transportation to a higher level, which allows you to call such networks multiservice ones. The new generation networks allow simultaneous transmission of mixed streams (voice, video, and data) represented in the form of standard packets. One of the ways to ensure the specified quality of service is to introduce a priority method for servicing traffic flows 5.

Augmenting DiffServ operations with dynamically learned classes of services

In this work, we provide a Machine Learning framework for augmenting the Differentiated Services (DiffServ) protocol with fine-grained dynamic traffic classification. The framework is called L-DiffServ. It is composed of two classification algorithms able to detect the QoS classes of incoming packets only looking at three packet header fields; the first algorithm, referred to as Inter-L-DiffServ, is a semi-supervised classification procedure able to replicate DiffServ classification; the second one, referred to as Intra-L-DiffServ, is an unsupervised algorithm for intra-class classification, useful for classes taking large portions of the overall traffic. We apply the latter to the low priority best-effort class. The performance evaluation shows that our solution is able to dynamically classify packets and to detect new QoS sub-classes hence adapting to traffic aggregate characteristics. We also show that network resource management can be improved exploiting the new generated QoS sub-classes: two active queue management algorithms based on WRED and CHOKe show a reduction of the number of sessions affected by packet losses up to 40% with respect to the legacy DiffServ procedure.

Dynamic parking charge–perimeter control coupled method for a congested road network based on the aggregation degree characteristics of parking generation distribution

Homogeneous traffic density is the precondition of macroscopic fundamental diagrams (MFDs) that exist in a regional road network. However, traffic density may be transformed by the effects of traffic flow transmission and parking generation in a dynamic system. Once the homogeneous and uniform traffic density is changed, the shape of the MFD curve is likely affected, and thus, the output efficiency of the road network decreases.Based on the existing research of the aggregation evaluation model of parking generation in a regional road network, the study analyses the relationship between the variation in parking generation aggregation and the variation ratio in the trip completion flow of the network through further analysis. On this basis, a dynamic parking charge–perimeter control coupled (DPCPCC) method in a macro road network is proposed to balance the traffic flow density in a dynamically congested sub-region that exists in multiple public parking lots and to improve the efficiency of traffic flow for the entire road network. Furthermore, the method optimizes the entire parking charge rate of each MFD sub-region, aiming for the lowest generalized cost, reduces the delay time of the road network by adjusting the perimeter control rate, and changes the traffic aggregation index by dynamic charging strategies to improve the congested sub-region outflow efficiency. Finally, the regional road network in the Binhu New District of Hefei is taken as an example, and three control scenarios consisting of the DPCPCC method, the static parking charge–perimeter control coupled (SPCPCC) method, and the proportional–integral (PI) method are analysed and compared.According to the analysis of the relationship between the parking generation aggregation index and MFD changes and the application of this relationship to verify the regional road network dynamic charging model, the results reveal that the DPCPCC method can reduce the marginal social cost and improve the operation efficiency of the road network compared with the SPCPCC and PI control methods.

Practical Consistency of Ethernet-Based QoS with Performance Prediction of Heterogeneous Microwave Radio Relay Transport Network

Microwave line-of-sight radio relay (RR) systems are a constitutive part of a telecom operator transport network, as an alternative to optical transmission systems when the latter are not technically possible or rational to implement. Nowadays, RR links are quite often used in the access network for connecting mobile radio base stations, thus also enabling traffic aggregation, and so on. In this paper, we focus on a practical, real-life, five-section heterogeneous RR network, comprising classic synchronous digital hierarchy (SDH) and SDH new generation network (NGN) architecture, hybrid parallel and mutually independent transmission of native Ethernet and TDM services, and all-IP network parts. Specifically, the main task of this work is to answer whether such a diverse RR system could satisfy the quality norms for Ethernet-based services, meaning whether a tolerable RR unavailability will necessarily imply the according Ethernet quality of service (QoS) degradation. This question is addressed by the comprehensive in-service and out-of-service testing of an operational hybrid RR transmission system. After extensive practical testing and appropriate analysis of the achieved results, it came out that the impact of RR-level impairments that determine the performance prediction affected the Ethernet QoS to the extent that BER values increased to the acceptability threshold values. We believe that the preliminary results reported here could serve as a hint and a framework for a more comprehensive cross-layer test strategy in terms of both test diversity and repeating rate, which contemporary network operators need to implement in order to enable the appropriate quality of experience for users of their services.