Real Time Conference Gateway For Heterogeneous Clients : Real Time Switching Clients And Inter-Asterisk Exchange Clients

Various standards organizations have considered signaling for voice and video over Internet Protocol(IP) from different approaches. The Inter-Asterisk eXchange (IAX) protocol is used as the promising VoIP protocol by the service provider because of its simplicity and NAT friendliness. Meanwhile, the Real time SWitching (RSW) has the ability to combine voice and video services. Incidentally, these two heterogeneous clients pose considerable problems for users who have to choose between two solutions offering different advantages and disadvantages. While RSW is being used in many areas, IAX is being deployed in many VoIP services. Hence, RSW interoperability and coexistence with IAX is considered very important to support new deployments that could use RSW as an alternative packet telephony signaling protocol. We proposed and implemented the conference gateway (CG), which enables the heterogeneous clients to communicate seamlessly. It has two modules, one is signaling, the other is media module. In signaling module, we have converted signaling and control messages of RSW and IAX respectively to achieve seamless signaling communication between heterogeneous clients via CG. The signaling module includes authentication of heterogeneous clients (RSW and IAX) before they start communication, conversion of Uniform Resource Indicator to reach remote clients, setup media calls and exchange media capability

QoS Design Consideration for Enterprise and Provider’s Network at Ingress and Egress Router for VoIP protocols

Compliance with the Service Level Agreement (SLA) metric is a major challenge in a Multiprotocol Label Switching Virtual Private Network (MPLS VPN) because mandatory models must be maintained on both sides of the MPLS VPN in order to achieve end-to-end service levels. The end-to-end service of an MPLS VPN can be degraded owing to various issues such as distributed denial of service (DDoS), and Random Early Detection (RED) that prevents congestion and differentiates between legitimate and illegitimate user traffic. In this study, we propose a centralized solution that uses a SLA Violation Detector (SLAVD) and intrusion detection to prevent SLA violation

AN INNOVATIVE FRAMEWORK FOR AUTO DYNAMIC SELECTION AND COMPOSITION OF WEB SERVICES

With the availability of ample amount of Web Services similar in functionality and varying in Quality of Service (QoS) over the web, it is essentially required to get the best-suited candidate services for the resultant composite service. QoS plays a decisive role in selecting web Services individually and Composite Web Service as a whole. Certainly, composition is one of the key properties of service-orientation to create new as well as advanced level services, by re-using the existing ones. In distributed environments, services having no quality guarantees, adversely affects the composition outcome. To find the best candidate services for the composition, researchers have opted either Users’ feedback or Providers’ published information but none of them have considered both of them together. In our approach, we have taken into consideration both the things (Users’ feedback and Providers’ published information) together in order to find the best candidate web services by cross verifying both of the information to ascertain the quality of the candidate web services. An innovative framework for the composition of web services along with the detailed methodology and algorithm has been discussed in the second half of the paper

Control and Media Sessions: lAX with RSW Control Criteria

This paper discusses technical issues related to delivery and control of IP multimedia services, such as multimedia conferencing, involving heterogeneous end terminals. In particular, it proposes the design of an experimental system for interworking between InterAsterisk eXchange Protocol and RSW session and call control signaling protocols

Biased-Power Allocation and Shared-Antenna Selection Techniques for Spatial Modulation-Based Layer Division Multiplexing Systems

peer reviewedThis study proposes two approaches for improving the effectiveness of spatial modulation integrated into layer division multiplexing (SM-LDM) in broadcasting systems: biased-power allocation (Bi-PA) and shared antenna selection (SAS). Even though different data rates are employed in SM-LDM systems, Bi-PA enhances bit error rate (BER) fairness across layers. The ideal power ratios are adaptively determined by balancing signal-to-interference plus noise ratios with a preference for the lower layer (LL) that involves a higher modulation order. SAS alleviates the complexity of successive interference cancellation and enhances spectral and energy efficiencies. Both the LL and upper layer (UL) share the antenna selection decision and transmit using a single antenna. The UL carries a space shift keying signal while the entire power is allocated for the LL. We analyze the spectral efficiency for the SAS-based SM-LDM system with finite alphabet inputs. Numerical results demonstrate the advantages of the proposed approaches. Compared to pre-assigned-PA (Pre-PA), Bi-PA shows nearly identical BERs for both layers and solves the error floor problem. The sharing property and common layer transmission of SAS-based SM-LDM yield a significant BER reduction relative to conventional SM-LDM. It provides gains ranging from 7 to 15 dB for LL at BER equal to 10−3, while UL performance ranges from slight gain to minor loss. Furthermore, both Bi-PA and SAS techniques enhance the achievable LL rate and sum-rate at low and intermediate signal-to-noise ratio values. They can achieve an improvement of up to two bits in LL rate and less than one bit in sum-rate at a signal-to-noise ratio of −0.5 dB. These findings show that both proposed techniques have a considerable impact on enhancing the fairness, BER performance, and feasible rates of SM-LDM systems, making them promise for broadcast system designs

Zeroize: A New Method to Improve the Utilization of 5G Networks When Running VoIP over IPv6

5G technology is spreading extremely quickly. Many services, including Voice Over Internet Protocol (VoIP), have utilized the features of 5G technology to improve their performance. VoIP service is gradually ruling the telecommunication sector due to its various advantages (e.g., free calls). However, VoIP service wastes a substantial share of the VoIP 5G network’s bandwidth due to its lengthy packet header. For instance, the share of the packet header from bandwidth and channel time reaches 85.7% of VoIP 5G networks when using the IPv6 protocol. VoIP designers are exerting considerable efforts to solve this issue. This paper contributes to these efforts by designing a new technique named Zeroize (zero sizes). The core of the Zeroize technique is based on utilizing the unnecessary fields of the IPv6 protocol header to keep the packet payload (voice data), thereby reducing or “zeroizing” the payload of the VoIP packet. The Zeroize technique substantially reduces the expanded bandwidth of VoIP 5G networks, which is reflected in the wasted channel time. The results show that the Zeroize technique reduces the wasted bandwidth by 20% with the G.723.1 codec. Therefore, this technique successfully reduces the bandwidth and channel time of VoIP 5G networks when using the IPv6 protocol

Privacy-Preserving Convolutional Bi-LSTM Network for Robust Analysis of Encrypted Time-Series Medical Images

Deep learning (DL) algorithms can improve healthcare applications. DL has improved medical imaging diagnosis, therapy, and illness management. The use of deep learning algorithms on sensitive medical images presents privacy and data security problems. Improving medical imaging while protecting patient anonymity is difficult. Thus, privacy-preserving approaches for deep learning model training and inference are gaining popularity. These picture sequences are analyzed using state-of-the-art computer aided detection/diagnosis techniques (CAD). Algorithms that upload medical photos to servers pose privacy issues. This article presents a convolutional Bi-LSTM network to assess completely homomorphic-encrypted (HE) time-series medical images. From secret image sequences, convolutional blocks learn to extract selective spatial features and Bi-LSTM-based analytical sequence layers learn to encode time data. A weighted unit and sequence voting layer uses geographical with varying weights to boost efficiency and reduce incorrect diagnoses. Two rigid benchmarks—the CheXpert, and the BreaKHis public datasets—illustrate the framework’s efficacy. The technique outperforms numerous rival methods with an accuracy above 0.99 for both datasets. These results demonstrate that the proposed outline can extract visual representations and sequential dynamics from encrypted medical picture sequences, protecting privacy while attaining good medical image analysis performance

A Three Layered Decentralized IoT Biometric Architecture for City Lockdown During COVID-19 Outbreak

In this article, we have built a prototype of a decentralized IoT based biometric face detection framework for cities that are under lockdown during COVID-19 outbreaks. To impose restrictions on public movements, we have utilized face detection using three-layered edge computing architecture. We have built a deep learning framework of multi-task cascading to recognize the face. For the face detection proposal we have compared with the state of the art methods on various benchmarking dataset such as FDDB and WIDER FACE. Furthermore, we have also conducted various experiments on latency and face detection load on three-layer and cloud computing architectures. It shows that our proposal has an edge over cloud computing architecture