Intelligent Service Migration in Multi-Domain Cellular Networks based on Profile Predictions

Wireless network virtualization (WNV) is considered as a reliable and effective solution to enhance the capacity and resource utilization in emerging 5G cellular wireless networks. WNV supports network sharing and multi-tenancy by allowing application or service providers with limited resources to lease network resources from mobile network operators. Several works in the literature surveyed various aspects of resource allocation and network slicing methods to implement virtualization in wireless networks. In this paper, we focus on economic aspects of WNV and study auction theory as a fundamental tool for designing business models for virtualization of wireless networks, 5G cellular networks in particular. Starting with the concept of WNV in 5G cellular networks, we describe the basic principles and solution approaches in auction theory for heterogeneous and multi-commodity scenarios. Subsequently, we review the recent advances in WNV based on auction models. We conclude by outlining the open challenges and future research directions related to applications of auctions in WNV.

One of the challenges of the mobile industry is to cope with the growth of mobile traffic demand expected for the next years, primarily driven by the increasing usage of mobile video services. Indeed, the existence of increasingly powerful terminals is encouraging the consumption of high-quality video content. Usually, video services are identified with linear Television (TV) and scheduled broadcast (point-to-multipoint (p-t-m)) distribution. However, the consumption of video content over mobile networks is different from traditional fixed TV because contents are mainly consumed on-demand with unicast point-to-point (p-t-p) connections. Then, the convergence of linear TV and on-demand content delivery represents a challenge that requires a combined broadcast/unicast transmission model. This dissertation addresses the use of broadcasting technologies for the provision of mobile multimedia services in Fourth Generation (4G) mobile broadband networks and beyond. Specifically, the dissertation focuses on the broadcast technology included in 4G Long Term Evolution (LTE) and LTE Advanced (LTE-A) networks, known as Enhanced Multicast Broadcast Multimedia Services (eMBMS). It analyses the benefits of the eMBMS physical layer aspects regarding Multimedia Broadcast Multicast Services over a Single Frequency Network (MBSFN) deployments and identifies the current limitations of eMBMS at physical layer by comparing with the broadcast technology of the other 4G mobile system, the Institute of Electrical and Electronics Engineers (IEEE) 802.16m standard. Those limitations are the use of a dedicated carrier and Multiple-Input Multiple-Output (MIMO) techniques for broadcast transmissions. Our investigations employ a complete simulation platform including link-level and system-level simulations to evaluate the performance of broadcast transmissions in these real technologies. The research on eMBMS services is aimed at finding the optimum delivery of streaming and file download services focusing on the Radio Resource Management (RRM) problem and trade-off between Physical layer ? Forward Error Correction (PHY-FEC) and Application Layer - Forward Error Correction (AL-FEC). Concerning streaming services, results show that the use of AL-FEC increases the coverage level and, then, the maximum service data rate. The gain due to AL-FEC is greater in scenarios with high mobility users, although, this gain is limited if low zapping times are desired. Regarding file delivery services, this dissertation analyses the duration of the transmission required to guarantee the correct file reception and the reduction in the mean throughput of unicast users with different delivery modes. They are the unicast delivery, the eMBMS delivery and a hybrid approach, which combines a first eMBMS delivery with a post-delivery error repair phase with unicast transmissions. Our results show that the hybrid delivery is the most efficient configuration in terms of file download time, although it further reduces unicast performance. On the other hand, as an exemplary use case, this dissertation also investigates the use of LTE networks for the provision of vehicular safety services comparing both unicast and eMBMS delivery modes. Results highlight the significant benefits in terms of resource usage, end-to-end latency and cost delivery saving that can be achieved by using eMBMS for the delivery of road safety applications. In addition, research also addresses the problem associated with the support of road safety applications over the current eMBMS architecture, the configuration of the Intelligent Transportation Systems (ITS) server in charge of distributing safety messages as well as on its interaction with the mobile network operator. Finally, this dissertation analyzes feasible options of convergence between mobile and broadcast industry to ensure the success of the mobile broadcasting deployments in the future. A separated evolution of the broadcast technologies of both industries would lead to a scenario with two complete different industries, with different network infrastructures and business models competing for market and spectrum. This dissertation proposes an approach by which the definition of the future Fifth Generation (5G) mobile broadband communication system could bring together the cellular and broadcast industries to form a single fixed and mobile converged network and offer a full alternative to terrestrial TV broadcasting as a universal service

The 3rd Generation Partnership Project (3GPP) uses three standard algorithms to achieve confidentiality in the 4th Generation (4G) cellular network. The latest one is Evolved Packet System Encryption Algorithm (EEA3), depend's on ZUC algorithm. EEA3 is a stream cipher used in the Long Term Evolution (LTE) network. This paper discusses a brief description for the EEA3 algorithm. C implementation of the algorithm based on 3GPP standard is introduced, solving the last Ciphertext word in case of padding. Also, an FPGA implementation of the EEA3 algorithm is presented using the VHDL language on a XILINX Spartan6 board. An analysis and evaluation of the implemented algorithm and the used resources are discussed.

Performance analysis of dual connectivity in control/user-plane split heterogeneous networks

Differentiated quality-of-Service (QoS) techniques are widely used to distinguish between different service classes and prioritize service needs in mobile networks. Mobile Network Operators (MNOs) utilize QoS techniques to develop strategies that are supported by the mobile network infrastructure. However, QoS deployment strategy can ensure that the radio resources provided by the base station are easily consumed if it is not used correctly or when different techniques are used all together. In this paper, we propose a scheduling algorithm and compare two different QoS deployment strategies for prioritized User Equipment (UEs) (with higher scheduling rates and dedicated bandwidth) that MNOs can use in the current infrastructure, using a commercial real-time Long Term Evolution (LTE) network in different test scenarios. Moreover, we expose the real-time user experience in terms of uplink throughput and analyze results of the UE’s real-time key performance indicators (KPIs) in detail. Experiment results are evaluated considering the implications of different QoS support types on network coverage and capacity planning optimizations. Our results demonstrate that even though pre-configured resource allocations can be given to prioritize UEs, the experience of all the UEs can be affected unexpectedly in the presence of many UEs who have received different QoS deployment support. Our experimental observations have revealed that location of the UEs with respect to Base Station (BS) and the availability of dedicated bandwidth UEs inside cell may have implications on the apriori defined resource allocation strategies of the other UEs.

Due to drastic development of smart phone devices, there is a considerable increase in mobile traffic flow that is provided difficulty on the fifth generation (5G) cellular networks. The growing quantity of communication data along with the need for maximum peak data rate, enhanced reliability and minimum delay in 5G network poses several challenging issues. At the same time mobile traffic flow prediction in 5G network is a challenging topic. In this aspect, this paper proposed a novel DL based mobile traffic flow prediction (DLMTFP) model in 5G networks. The goal of the DLMTFP technique is to differentiate the user’s mobile traffic, application usage and traffic patterns. In addition, the DLMTFP technique involves the modelling of bidirectional long short term memory (BiLS TM) model for the estimation of the mobile traffic flow. Moreover is employed for the hyper parameter optimization of the BiLSTM model. The exploitation of the hyper parameter optimization process helps to significantly boost the predictive outcome of the BiLSTM model. The DLMTFP technique is able to predict the traffic flow in peak range. For validating the improved predictive performance of the proposed DLMTFP technique a comprehensive simulation analysis takes place over the other state of the techniques.

With the extensive growth of the web as well as cellular networks, secure multimedia transmission through cellular networks is needed. Currently, fifth-generation (5G) cellular networks are utilized to perform secure multimedia transmission. Numerous studies have been conducted to design efficient resource allocation approaches for secure video transmission in 5G cellular networks. However, this approach does not offer complete video security related to security against dynamic eavesdroppers or patent defilements. Thus, a resource allocation algorithm named Tasmanian devil whale optimization (TDWO) is introduced for secure video transmission in 5G networks. Here, the recorded educational videos are considered and are transmitted over 5G network transmission resources initially. The resources in 5G networks are allocated via the TDWO model by considering fitness parameters such as the data rate, achievable data rate, and quality of experience (QoE). Here, the deep convolutional neural network (DCNN) model is deployed for the prediction of the QoE in resource allocation. Moreover, extensive experiments are performed to identify the resource allocation performance of the designed TDWO model. The experimental results prove that the TDWO resource allocation algorithm yields significant experimental outcomes, with throughput, bit error rate (BER), QoE and fitness values of 25.557 Mbps, 0.021, 18.332 and 0.013, respectively.

Mobile edge computing (MEC) provides a promising approach to significantly reduce network operational cost and improve quality of service (QoS) of mobile users by pushing computation resources to the network edges, and enables a scalable Internet of Things (IoT) architecture for time-sensitive applications (e-healthcare, real-time monitoring, and so on.). However, the mobility of mobile users and the limited coverage of edge servers can result in significant network performance degradation, dramatic drop in QoS, and even interruption of ongoing edge services; therefore, it is difficult to ensure service continuity. Service migration has great potential to address the issues, which decides when or where these services are migrated following user mobility and the changes of demand. In this paper, two conceptions similar to service migration, i.e., live migration for data centers and handover in cellular networks, are first discussed. Next, the cutting-edge research efforts on service migration in MEC are reviewed, and a devisal of taxonomy based on various research directions for efficient service migration is presented. Subsequently, a summary of three technologies for hosting services on edge servers, i.e., virtual machine, container, and agent, is provided. At last, open research challenges in service migration are identified and discussed.

Recently, there has been a tremendous increase in mobile data usage with widespread proliferation of smartphone like devices and increasing popularity of video streaming services such as YouTube. This is already causing overloading of 3G cellular access networks. It is estimated that even the 4G LTE (Long Term Evolution) technology which has significantly higher spectral efficiency than 3G will also face overloading in near future. As a result, it has become important to find out ways and means of offloading the traffic from the LTE network. One possible solution is offloading it to Wi-Fi to gain extra capacity and improve overall network performance. In this paper we have considered an outdoor macro cell LTE Network being offloaded by a Wi-Fi network. We study the loading of LTE Network in different types of user and traffic distribution and investigate how offload to Wi-Fi APs can help in easing the congestion in LTE network and thereby lead to better per user throughputs and better quality of experience to end users using NS-3. Also, among the various scheduling algorithms that have been defined for efficient resource allocation in LTE, three schedulers have been considered: Round Robin (RR), Proportional Fair (PF) and Priority Set Scheduler (PSS) schedulers and their performance has been evaluated in the offloading scenario.

As we progress towards the fifth generation (5G) wireless systems to meet the data rate requirements, it becomes difficult for the conventional cellular networks to provide connectivity in the uplink to a huge number of connected devices. Hence, the adoption of the millimeter wave (mmWave) technology will ease the integration of IoT devices into the 5G cellular network. In this paper, we consider a stochastic geometry model to investigate baseline Random Access scheme’s success probability in the Internet of things (IoT) that uses millimeter wave (mmWave) cellular communication technology. Specifically, to obtain novel insights, we analyze probability of success of the random access scheme in the following three scenarios: i) Success probability as a function of the signal power-to-noise ratio (SNR), ii) Success probability as a function of the signal power-to-interference ratio (SIR), and iii) Success probability in terms of signal power-to-interference plus noise ratio (SINR). Furthermore, we approximate the probability of success in LOS region using a simplified ball model for a large number of IoT devices. Using Monte Carlo simulations, the approximation of LOS-ball comes out to be sufficiently accurate with the analytical results for typical IoT intensity.

Development of Mobile handset applications, new standard for cellular networks have been defined. In this Paper, author intend to propose a Novel mobile Antenna that can cover more of LTE (Long Term Evolution) Bands (4G cellular networks). The proposed antenna uses structure of planar monopole antenna. Bandwidth of antenna is 0.87-0.99 GHz, 1.65-3.14 GHz and has high efficiency unlike the previous structures. The dimension of the antenna is 18mm×21mm and has FR4 substrate by 1.5mm thickness that is very compact antenna respect to the other expressed antenna.

the fusion of cellular network and wireless sensor network is the key research problem of Internet of Things (IoT) technology at present. The design and implementation of wireless sensor cellular network based on Android platform is mainly studied. Firstly, wireless sensor network and cellular network, Android platform, cellular network and Wireless Sensor Network (WSN) fusion strategy, and Wireless Sensor Network (WSN) gateway platform are introduced. Then related functions are introduced, mainly including terminal registration management, connection management, authentication management, terminal fault management, and communication message design on the gateway and sensor network side. Finally, related functional tests are conducted. The results show that the designed application layer gateway system can connect the sensor network with the cellular network. Time Division-Synchronization Code Division Multiple Access (TD-SCDMA) and cellular network covers the whole world, while cellular network has been interconnected with the Internet through Access Network Technologies such as General Packet Radio Service (GPRS), The Fourth Generation of Mobile Phone Mobile Communication Technology Standards (4G) and Long Term Evolution (LTE), thus enabling the sensor network to access the Internet anytime and anywhere

<title>Abstract</title> Optimal channel allocation in fifth-generation (5G) cellular networks plays a vital role in ensuring quality of service and reducing call blocking rates. In this study, an innovative model based on the hippopotamus optimization algorithm (HOA) is proposed to enhance channel allocation efficiency. To evaluate performance, six simulation scenarios were designed under various conditions, ranging from heavy traffic to abundant resource availability. In these scenarios, the number of active users varied between 30,000 and 40,000, the available channels ranged from 3,000 to 5,000, the call arrival rate spanned 0.7 to 0.99 calls per hour, and the average call duration ranged from 3.6 to 28.5 minutes. Compared with three well-established methods—genetic algorithm, Ant colony optimization, and particle swarm optimization —the proposed HOA demonstrated, on average, a 19% reduction in call blocking rates and achieved faster convergence speed. Despite these advantages, limitations such as increased computational complexity in very large-scale scenarios remain, which may define directions for future research. The results highlight the significant potential of HOA in improving spectrum efficiency, enhancing network capacity, and elevating user experience in 5G cellular networks.

Traffic offloading in Long Term Evolution (LTE) networks is a key process in cellular networks so a mobile device chooses one of the available femtocells. In the last few years, several network selection methods have been proposed based on multiple attribute decision making (MADM) techniques for traffic offloading in LTE. The Analytic Network Process (ANP) is an MADM method that has been barely studied for network selection in cellular networks; ANP configures the decision making problem as a network of attributes in order to derive priority scales of individual judgments. We propose in this paper NetANPI (Network selection ANP-based mechanism with Ideal network comparison), which is an ANP decision making mechanism for traffic offloading in LTE. We show its effectiveness by contrasting it with MADM methods proposed in the literature as AHP, ELECTRE, TOPSIS, GRA, and SAW. We also introduce a mechanism to rank the MADM algorithm using utility theory. Our results show that NetANPI outperforms the most used MADM mechanism for the interactive and conversational traffic classes.

It is mightily envisaged that cellular networks have often been deployed ensuring seamless accommodation of users growing demand with deep valuation of felicitous usability and feasibly aspects. In this regard, several mobile network operators (MNOs) in low income countries often fall through unabated implementation that imperiled the business due to limitations while evaluating socio-economic status, information communication technology (ICT) literacy status, device eco system, traffic usage trend & other essential technical preempts that are needed to be addressed in pre-deployment stages. This work has brought an allusive and attestation guideline for mobile network operators while executing radio frequency (RF) signal performance evaluation, optimization and upgrading. Moreover, it tips-off economical and an apt RF solutions where the applicability & feasibility are pragmatically justified in addressing existing network problem. An indispensable field reliant drive testing is incorporated to collect real time data of RF environment & logs are analyzed for both third generation (3G) and fourth generation (4G) cellular networks of Jimma town. The analysis & evaluation of both test scenarios depicts that poor coverage, quality and throughput distributions that are observed in numerous parts of the town that are associated with capacity limitations & RF optimization setbacks. Post optimization RF performance and HSDPA peak rate are visualized using Atoll and WinProp simulation tools; a far-reaching optimization & an apt Evolved High Speed Packet Access (HSPA+) release 9 upgrading is adapted & simulated in purpose of picturing improvements in coverage, capacity and quality of the network. Thus, an application of 46 RF adjustments & changes has improved RSCP & ${{E}_{c}}{{I}_{o}}$ over 39.84% & 27.31% of coverage area respectively.