Reliable data delivery in the Internet of Things (IoT) is very important in order to provide IoT-based services with the required quality. However, IoT data delivery may not be successful for different reasons, such as connection errors, external attacks, or sensing errors. This results in data incompleteness, which decreases the performance of IoT applications. In particular, the recovery of missing data among the massive sensed data of the IoT is so important that it should be solved. In this paper, we propose a probabilistic method to recover missing (incomplete) data from IoT sensors by utilizing data from related sensors. The main idea of the proposed method is to perform probabilistic matrix factorization (PMF) within the preliminary assigned group of sensors. Unlike previous PMF approaches, the proposed model measures the similarity in data among neighboring sensors and splits them into different clusters with a K-means algorithm. Simulation results show that the proposed PMF model with clustering outperforms support vector machine (SVM) and deep neural network (DNN) algorithms in terms of accuracy and root mean square error. By using normalized datasets, PMF shows faster execution time than SVM, and almost the same execution time as the DNN method. This proposed incomplete data-recovery approach is a promising alternative to traditional DNN and SVM methods for IoT telemetry applications.

Recent interesting activities in spectrum analysis have introduced an additional band, the 5 GHz unlicensed spectrum, which has been primarily used for Wi-Fi. There are many challenges related to the coexistence of two different networks, a Wi-Fi network and an LTE network, sharing unlicensed bands but causing interference with each other. In this article, to solve the coexistence challenges, we propose a new protocol for carrier sensing and interference avoidance for heterogeneous networks: carrier sense LTE unlicensed access (CASLUA). The key idea of this protocol is that it listens to the channel by using a Wi-Fi air interface, but actually transmits data via an LTE air interface. This is achieved by using a proposed dual frame aggregation scheme where two frames (an L-frame and a U-frame) are allocated to licensed and unlicensed bands, respectively. Two implementations of CASLUA are carried out, one based on standalone operation (S-CASLUA)and the other operating with assistance from a software-defined network controller (SDN-CASLUA). SDN assistance lies in the monitoring of multiple network parameters, which are then used to make a decision on effective spectrum allocation with awareness of interference and capacity demands. Simulation results show that the CASLUA protocol helps to avoid interference and increases the average throughput by up to 40 percent for both Wi-Fi and LTE users in LTE-Unlicensed.

The rapid development and spread of communication technologies is now becoming a global information revolution. Customers have a need for communication services, which could be flexibly configured in accordance with their Quality of Experience (QoE) requirements. Realizing the close connection between customer experience and profitability, the service provider has been placing more and more attention on customer experience and QoE. The traditional quality of service management method based on SLA (Service Level Agreement) is not sufficient as a means to provide QoE-related contracts between service providers and customers. The current SLA method is mostly limited and focused on technical aspects of QoS (Quality of Service). Furthermore, they do not follow on the network the principles and semantic approach to the QoS specification for a communication service using QoE parameters. In this paper, we propose a customer-oriented quality of service management method for future IBN (Intent-Based Networking). It is based on a new QoE metric on a scale from 1 to 5, which allows one to take into account the commercial value of e-services for customers. Based on this approach, the network configuration and functionality of network equipment automatically changes depending on customer requirements. To implement the new method of service quality management, an algorithm for routing data packets in the network was developed, taking into account the current load of the forecast path. The algorithm of billing system functioning in conditions of customer-oriented quality management in telecommunication networks has been created. To investigate the effectiveness of the proposed method of service quality management with the traditional SLA method, we developed a simulation network model with the implementation of two approaches. By conducting a simulation, it was determined that the proposed method gives an average gain of 2–5 times for the criterion of the number of customers who require high quality of experience of the service.

The problem of analyzing a big amount of user data to determine their preferences and, based on these data, to provide recommendations on new products is important. Depending on the correctness and timeliness of the recommendations, significant profits or losses can be obtained. The task of analyzing data on users of services of companies is carried out in special recommendation systems. However, with a large number of users, the data for processing become very big, which causes complexity in the work of recommendation systems. For efficient data analysis in commercial systems, the Singular Value Decomposition (SVD) method can perform intelligent analysis of information. With a large amount of processed information we proposed to use distributed systems. This approach allows reducing time of data processing and recommendations to users. For the experimental study, we implemented the distributed SVD method using Message Passing Interface, Hadoop and Spark technologies and obtained the results of reducing the time of data processing when using distributed systems compared to non-distributed ones.

This paper considers concept content delivery network (CDN) system. We propose architecture, for select the optimum route and server for a user request, based on the objective functions. The main criterions of the objective function were taken delay time, server load and probability of packet lost. We will describe the main task of the load balancing system.

There is a spectrum of solutions are available for distributing content over the Internet today. One of these solutions is Content distribution networks (CDN). CDN need to make decisions, such as server selection and routing, to improve a performance of content distribution. But we must remember, that performance may be limited by various factors such as packet loss in the network, a small receive buffer at the client and so on. A CDN replicates content from the origin server to cache servers, in order to deliver content to end-users in a reliable and timely manner from nearby optimal surrogates. This article presents results of designing a Content Delivery Network, content distribution mechanisms, request redirection techniques, and performance measurement methodologies monitoring system for CDN resources.