Norihiro Fukumoto

Objective Speech Quality Assessment Based on Payload Discrimination of Lost Packets for Cellular Phones in NGN Environment

A feature of services provided in a Next Generation Network (NGN) is that the end-to-end quality is guaranteed. This is quite a challenging issue, given the considerable fluctuation in network conditions within a Fixed Mobile Convergence (FMC) network. Therefore, a novel approach, whereby a network node and a mobile terminal such as a cellular phone cooperate with each other to control service quality is essential. In order to achieve such cooperation, the mobile terminal needs to become more intelligent so it can estimate the service quality, including the users perceptual quality, and notify the measurement result to the network node. Subsequently, the network node implements some kind of service control function, such as a resource and admission control function, based on the notification from the mobile terminal. In this paper, the role of the mobile terminal in such collaborative system is focused on. As a part of a QoS/QoE measurement system, we describe an objective speech quality assessment with payload discrimination of lost packets to measure the users perceptual quality of VoIP. The proposed assessment is so simple that it can be implemented on a cellular phone. We therefore did this as part of the QoS/QoE measurement system. By using the implemented system, we can measure the users perceptual quality of VoIP as well as the network QoS metrics, in terms of criteria such as packet loss rate, jitter and burstiness in real time.

Complex Event Processing to detect congestions in mobile network

With a wide spread of smartphones and tablets, a mobile network becomes frequently congested when many users concentrate to the same place. Especially when a large-scale event is held, a heavy network congestion interferes with the communication of the participants as well as local residents. In order to detect the network congestion, a large amount of traffic log should be analyzed in real time. In this paper, the proposed system attempts to detect a sign of the congestion by using a CEP (Complex Event Processing). First, by analyzing network status when the large-scale event, Nagaoka Fireworks festival, is held, it is observed that the network congestion can be effectively detected from the combination of (1) the RTT, (2) the specific type of TCP session termination (FTN-No-ACK) and (3) the number of retransmission packets. Next, we develop our proposed congestion detection system by using a CEP for detecting these metric in real-time. Through the experimental evaluation, it is concluded that the proposed system can scalably analyze a large amount of traffic log in real-time.

Autonomous Data Transmission Using Off-Peak Hours for Cellular-Based M2M Communications

This paper proposes autonomous data transmission using off-peak hours for cellular-based machine-to-machine (M2M) communications. In the near future, there will be an enormous number of machine type terminals (MTs) capable of connecting to cellular networks. Thus, an efficient scheme for accommodating M2M traffic in existing cellular networks is required. To tackle this challenge, we focus on the fact that there are a lot of delay-insensitive services in M2M communications. The goal of the proposed method is to shift such traffic to off-peak hours in a scalable, flexible and simple manner. We evaluate the proposed method through a field experiment and a computer simulation using traffic data obtained from a commercial cellular network.

A Practical Behavior Analysis of Video Application Users on Smart Phones

Mobile network operators are keeping a watchful eye on video applications because of their high impact on traffic volume. For optimum mobile network design it is desirable to know more about the characteristics of video traffic, which depend on the behavior of the video application users who generates that traffic. We conducted a practical behavior analysis of video application users on smart phones, using a traffic analysis approach that scales up well. We also present our findings about typical user behavior in video applications from a traffic analysis standpoint.

A Practical Evaluation Method of Network Traffic Load for Capacity Planning

Communications network operators are supposed to provide high quality network service at low cost. Operators always monitor the amount of traffic and decide equipment investment when the amount exceeds a certain threshold considering trade-offs between link capacity and its utilization. To find the proper threshold efficiently, this paper proposes a practical threshold definition method which consists of fine grained data collection and computer simulation. We evaluate the proposed method using commercial traffic data-set. The results show the proper timing for the equipment investment.

Development and Evaluation of Congestion Detection System Using Complex Event Processing for Mobile Networks

A congestion detection on mobile networks becomes the main challenge of cellular carriers and mobile network providers because the mobile network quality easily degrades when many users concentrate on a limited place. Especially when a large-scale event is held, a heavy network congestion interferes with the communication of the participants and local residents. Therefore, the congestion detection process has been performed by several network providers, but has been executed on a high-performance computing resource in a centralized manner, which markedly increases the computing cost. On the other hand, with the wide spread of a large-scale distributed computing environment (e.g., cloud computing), a Complex Event Processing (CEP) system has recently been made available for several purposes. The CEP is a distributed computing system which can identify meaningful events by analyzing a large amount of data stream (e.g., sensor data) in real time. Here, the congestion detection can be considered as a suitable application for the CEP system, where a large amount of traffic logs (i.e., data streams) should rapidly be analyzed in order to detect network congestions (i.e., meaningful events). Therefore, in this study, we propose a new system structure of the CEP-based congestion detection system using distributed computing resources. In the proposed system, processing components are deployed on multiple resources, and execute independent tasks that are carefully extracted from a system procedure of the congestion detection. Through experimental evaluation using computing resources on a popular cloud service (Amazon EC2), it is disclosed that the CEP-based system contributes to achieve the real time detection of congestions on the mobile networks.