Voice traffic prediction is significant for network deployment optimization thus to improve the network efficiency. The real entropy based theorectical bound and corresponding prediction models have demonstrated their success in mobility prediction. In this paper, the real entropy based predictability analysis and prediction models are introduced into voice traffic prediction. For this adoption, the traffic quantification methods is proposed and discussed. Based on the real world voice traffic data, the prediction accuracy of N-order Markov models, diffusion based model and MF model are presented, among which, 25-order Markov models performs best and approach close to the maximum predictability. This work demonstrates that, the real entropy can also predict voice traffic well which broaden the understanding on the real entropy based prediction theory.
VoIP transfer voice over networks such as LAN. This technology is growing rapidly due to support of existing network infrastructure at low cost. Various simulations have been done and it is observed that by increasing the VoIP client, packet length and traffic arrival rate the performance of step network affected. In the current work packet dropped, packet received, voice traffic sent and end-to-end delay is estimated for various queuing disciplines like PQ, FIFO and WFQ. It is depicted that queuing disciplines effects the applications performance and utilization of resources.
Identifying those causes and parameters that affect the Quality of Service (QoS) of Voice-over-Internet Protocol (VoIP) through heterogeneous networks such as WiFi, WiMAX and between them are carried out using the OPNET simulation tool. Optimization of the network for both intra- and intersystem traffic to mitigate the deterioration of the QoS are discussed. The average value of the jitter of the VoIP traffic traversing through the WiFi-WiMAX network was observed to be higher than that of utilizing WiFi alone at some points in time. It is routinely surmised to be less than that of transiting a…
Performance Analysis of VoIP Traffic in WiMAX using various Service Classes
全球微波接入互操作性（Worldwide Interoperability for Microwave Access，WiMAX）是目前无线领域最热门的技术之一，它是基于IEEE 802.16无线技术的标准，能够提供长距离的高吞吐量宽带连接，支持点到多点（Point to MultiPoint，PMP）宽带无线接入。与此同时，基于互联网协议的语音是一种很有前途的新技术，它提供了基于互联网协议的网络上的语音通信的访问，它成为一个替代公共交换电话网，由于其传输语音的能力，作为分组在IP网络。因此，VoIP在很大程度上不能容忍延迟，因此它需要高优先级传输。在本文中，我们研究了最常见的VoIP编解码器，这是G711，G7231和G729在WiMAX网络使用各种服务类和NOAH作为传输协议的性能。为了分析QoS参数，使用流行的网络模拟器ns2。分析了决定实际应用场景和业务流的QoS的各种参数。我们的目标是比较不同类型的服务类的QoS参数，如吞吐量，平均抖动和平均延迟。
IPv6 activity is commonly reported as a fraction of network traffic per day. Within this traffic, however, are daily and weekly characteristics, driven by non-uniform IPv6 deployment across ISPs and regions. This paper discusses some of the more apparent patterns we observe today.
The adoption of Internet of Things (IoT) technologies in businesses is increasing and thus enterprise IoT (EIoT) is seemingly shifting from hype to reality. However, the actual use of EIoT over significant timescales has not been empirically analyzed. In other words, the reality remains unexplored. Furthermore, despite the variety of EIoT verticals, the use of IoT across vertical industries has not been compared. This paper uses a two-year EIoT dataset from a major Finnish mobile network operator to investigate device use across industries, cellular traffic patterns, and mobility patterns. We …
High Speed Downlink Packet Access (HSDPA) was introduced to UMTS radio access segment to provide higher capacity for new packet switched services. As a result, packet switched sessions with multiple diverse traffic flows such as concurrent voice and data, or video and data being transmitted to the same user are a likely commonplace cellular packet data scenario. In HSDPA, Radio Access Network (RAN) buffer management schemes are essential to support the end-to-end QoS of such sessions. Hence in this paper we present the end-to-end performance study of a proposed RAN buffer management scheme for…
Detecting the anomalous behavior of traffic is one of the important actions for network operators. In this study, we applied term frequency - inverse document frequency (TF-IDF), which is a popular method used in natural language processing, to detect unusual behavior from network access logs. We mapped the term and document concept to the port number and daily access history, respectively, and calculated the TF-IDF. With this approach, we could obtain ports frequently observed in fewer days compared to other port access activities. Such access behaviors are not always malicious activities; ho…
Simulation of VoIP (Voice over Internet Protocol) traffic through UMTS (Universal Mobile Telecommunication System) and WiFi (IEEE 802.11x) alone and together are analysed for Quality of Service (QoS) performance. The average jitter of VoIP transiting the WiFi-UMTS network has been found to be lower than that of either solely through the WiFi and the UMTS networks. It is normally expected to be higher than traversing through the WiFi network only. Both the MOS (Mean Opinion Score) and the packet end-to-end delay were also found to be much lower than expected through the heterogeneous WiFi-UMTS …
In this paper, we propose a novel algorithm to detect anomaly in terms of Key Parameter Indicators (KPI)s over live cellular networks based on the combination of Recurrent Neural Networks (RNN), and Convolutional Neural Networks (CNN), as Recurrent Convolutional Neural Networks (R-CNN). CNN models the spatial correlations and information, whereas, RNN models the temporal correlations and information. In this paper, the studied cellular network consists of 2G, 3G, 4G, and 4.5G technologies, and the KPIs include Voice and data traffic of the cells. The data and voice traffic are extremely import…
While the IEEE 802.11 protocol is being widely used, it is not specifically designed to handle multimedia traffic, which covers an important portion of the Internet traffic today. Voice and video multicast streaming is inefficient, as there is lack of transmission reliability in such approaches where delay is not guaranteed. In this work, we focus on the performance of Enhanced Distributed Channel Access (EDCA) mechanism proposed by IEEE 802.11e which provides traffic prioritization and since most of the previous works are done based on simulation results, we test the performance of this proto…
The dramatic growth in cellular traffic volume requires cellular network operators to develop strategies to carefully dimension and manage the available network resources. Forecasting traffic volumes is a fundamental building block for any proactive management strategy and is therefore of great interest in such a context. Differently from what found in the literature, where network traffic is generally predicted in the short-term, in this work we tackle the problem of forecasting busy hour traffic, i.e., the time series of observed daily maxima traffic volumes. We tackle specifically forecasti…
The usage of the mobile app is unassailable in this digital era. While tons of data are generated daily, user privacy security concerns become an important issue. Nowadays, tons of techniques, such as machine learning and deep learning traffic classifiers, have been applied to analyze users app traffic. These techniques allow the monitor to get the fingerprints of using apps while the user traffic is still encrypted, which raises a severe privacy issue. In order to fight against this type of data analysis, people have been researching obfuscation algorithms to confuse feature-based machine lea…
With small cell base stations (SBSs) densely deployed in addition to conventional macro base stations (MBSs), the heterogeneous cellular network (HCN) architecture can effectively boost network capacity. To support the huge power demand of HCNs, renewable energy harvesting technologies can be leveraged. In this paper, we aim to make efficient use of the harvested energy for on-grid power saving while satisfying the quality of service (QoS) requirement. To this end, energy-aware traffic offloading schemes are proposed, whereby user associations, ON-OFF states of SBSs, and power control are join…
Multicast/broadcast services (MBS) are able to provide video services for many users simultaneously. Fixed amount of bandwidth allocation for all of the MBS videos is not effective in terms of bandwidth utilization, overall forced call termination probability, and handover call dropping probability. Therefore, variable bandwidth allocation for the MBS videos can efficiently improve the system performance. In this paper, we propose a bandwidth allocation scheme that efficiently allocates bandwidth among the MBS sessions and the non-MBS traffic calls (e.g., voice, unicast, internet, and other ba…
A Heterogeneous Network (HetNet) comprises of multiple Radio Access Technologies (RATs) allowing a user to associate with a specific RAT and steer to other RATs in a seamless manner. To cope up with the unprecedented growth of data traffic, mobile data can be offloaded to Wireless Fidelity (WiFi) in a Long Term Evolution (LTE) based HetNet. In this paper, an optimal RAT selection problem is considered to maximize the total system throughput in an LTE-WiFi system with offload capability. Another formulation is also developed where maximizing the total system throughput is subject to a constrain…
During early 2020, the SARS-CoV-2 virus rapidly spread worldwide, forcing many governments to impose strict lockdown measures to tackle the pandemic. This significantly changed people's mobility and habits, subsequently impacting how they use telecommunication networks. In this paper, we investigate the effects of the COVID-19 emergency on a UK Mobile Network Operator (MNO). We quantify the changes in users' mobility and investigate how this impacted the cellular network usage and performance. Our analysis spans from the entire country to specific regions, and geodemographic area clusters. We …
Payload attribution systems (PAS) are one of the most important tools of network forensics for detecting an offender after the occurrence of a cybercrime. A PAS stores the network traffic history in order to detect the source and destination pair of a certain data stream in case a malicious activity occurs on the network. The huge volume of information that is daily transferred in the network means that the data stored by a PAS must be as compact and concise as possible. Moreover, the investigation of this large volume of data for a malicious data stream must be handled within a reasonable tim…
Large-scale mobile traffic analytics is becoming essential to digital infrastructure provisioning, public transportation, events planning, and other domains. Monitoring city-wide mobile traffic is however a complex and costly process that relies on dedicated probes. Some of these probes have limited precision or coverage, others gather tens of gigabytes of logs daily, which independently offer limited insights. Extracting fine-grained patterns involves expensive spatial aggregation of measurements, storage, and post-processing. In this paper, we propose a mobile traffic super-resolution techni…
Real Call Detail Records (CDR) are analyzed and classified based on Support Vector Machine (SVM) algorithm. The daily classification results in three traffic classes. We use two different algorithms, K-means and SVM to check the classification efficiency. A second support vector regression (SVR) based algorithm is built to make an online prediction of traffic load using the history of CDRs. Then, these algorithms will be integrated to a network planning tool which will help cellular operators on planning optimally their access network.
University of Washington（华盛顿大学）；Infoblox（Infoblox公司）
For network administration and maintenance, it is critical to anticipate when networks will receive peak volumes of traffic so that adequate resources can be allocated to service requests made to servers. In the event that sufficient resources are not allocated to servers, they can become prone to failure and security breaches. On the contrary, we would waste a lot of resources if we always allocate the maximum amount of resources. Therefore, anticipating peak volumes in network traffic becomes an important problem. However, popular forecasting models such as Autoregressive Integrated Moving A…
