Aug 23
The IUP Journal of Telecommunications
Focus
This issue contains three papers, mainly addressing the challenges and solutions related to wireless mobile network in terms of superior This issue contains three papers, mainly addressing issues of VoIP, mobile IP and digital signal processing techniques to manoeuvre the digital data for better throughput through limited bandwidth of network link.
VoIP allows the transport of voice traffic over the IP-based packet-switched network and ensures a virtual connection by utilizing the available bandwidth more effectively. The first paper, "Setting Up a VoIP Phone System Using Open Source Tools", by G P D Chamoth Madushan Jayasekara, proposes a test lab setup using open-source tools to experiment with VoIP implementation and operation. It also provides experimental results on call sessions, Internet bandwidth, latency of network, and jitters in the network for a better characterization of VoIP system.
The second paper, "Mobile IP Framework for Seamless Global Roaming Across Heterogeneous Networks", by Fidelis I Onah, presents a mobile IP framework and methodology for supporting seamless global roaming within a geographic mobility domain. It discusses an adaptive generic algorithm to select, optimize and maintain transparent network connectivity for mobile users on the move in a heterogeneous network environment.
Obviously, the channel bandwidth is a precious component of wireless link in a communication network, especially if the network is handling multi-standard traffic including real-time data and multimedia traffic. These network capabilities require robust algorithms and efficient digital signal processing techniques to convert raw image video data into a well-compressed format suitable for efficient transmission through limited bandwidth links of the desired networks. The last paper, "Accurate EEG-Based Emotion Detection Using Feature Optimization and Machine Learning Algorithm", by Nayana Vaity and Ankit Temurnikar, proposes feature optimization and detection method based on the bee scout algorithm and derived support vector machines (DSVM) to reduce network training time, and thus claims an improvement in the network performance. The proposed method considers the raw data and decomposes this using discrete wavelet transform into a sequence of frequencies before the feature extraction using four pre-trained SVM procedure. The findings demonstrate superior performance of the proposed methodology over the existing emotion detection approaches.
Consulting Editor
Setting Up a VoIP Phone System Using Open Source Tools
Voice over Internet Protocol (VoIP) is simply the transport of voice traffic over the Internet or any IP-based packet-switched network. This is in contrast with the traditional telephone network, carrying voice data over dedicated circuit-switched transmission lines. A major challenge to implementing VoIP is to ensure sufficient bandwidth, and access to the available bandwidth is controlled and prioritized. Sufficient bandwidth is required to maintain high-quality voice. On the other hand, controlling it limits bandwidth-hogging applications and guarantees access to delay-sensitive applications. The objective of this paper is to familiarize the readers with building a test VoIP lab setup using open-source tools; experimenting how different network impairments would affect VoIP quality; and explaining the lab setup activities, investigations, data analysis and research. Subsequently, the paper gives an overview of various technicalities such as operating system, servers, codec selection, signaling protocols, etc. involved in achieving network quality-of-service.
Mobile IP Framework for Seamless Global Roaming Across Heterogeneous Networks
With the appearance of more and more bandwidth consuming applications in today's mobile data services market, telecom operators can no longer rely on price to attract and retain subscribers. Seamless roaming has become an important value-added service for improving back-end billing, subscriber relationships, bandwidth preservation through aggregation, quality of service and revenue generation. The paper presents the Mobile IP framework and methodology for supporting seamless global roaming within a geographic mobility domain. The goals and challenges of secured and seamless roaming solution are investigated. The responsibility of individual layers of the TCP/IP protocol stack is ill-defined with respect to mobility. The paper highlights the need for an adaptive generic algorithm to select, optimize and maintain transparent network connectivity for mobile users on the move, despite changing connection types and locations in a heterogeneous network environment.
Accurate EEG-Based Emotion Detection Using Feature Optimization and Machine Learning Algorithm
This paper proposes a feature optimization and detection method based on the bee scout algorithm and derived support vector machine (DSVM). The DSVM approach reduces network training time by removing unused features. First, the raw EEG data is decomposed using discrete wavelet transform (DWT) into a sequence of frequencies. Before the feature extraction procedure, the spatiotemporal component of the decomposed EEG signal is represented as a two-dimensional spectrogram using the shifting. To extract features, four pre-trained SVMs are employed. Dimensional reduction and feature selection are accomplished by bee scout-based EEG channel selection and DSVM approach. The proposed algorithm is tested on MAHNOB dataset. The results suggest that the proposed algorithm is more efficient than existing algorithms.