Predicting Internet of Things Data Traffic Through LSTM and Autoregressive Spectrum Analysis

The rapid increase of Internet of Things (IoT) applications and services has led to massive amounts of heterogeneous data. Hence, we need to re-think how IoT data influences the network. In this paper, we study the characteristics of IoT data traffic in the context of smart cities. Aiming at analyzing the influence of IoT data traffic on the access and core network, we generate various IoT data traffic according to the characteristics of different IoT applications. Based on the analysis of the inherent features of the aggregated IoT data traffic, we propose a Long Short-Term Memory (LSTM) model combined with autoregressive spectrum analysis to predict the IoT data traffic. In this model, the autoregressive spectrum analysis is used to estimate the minimum length of the historical data needed for predicting the traffic in the future, which alleviates LSTM's performance deterioration with the increase of sequence length. A sliding window enables predicting the long-term tendency of IoT data traffic while keeping the inherent features of the data traffic. The evaluation results show that the proposed model converges quickly and can predict the variations of IoT traffic more accurately than other methods and the general LSTM model.Peer reviewe

Predicting Internet of Things Data Traffic Through LSTM and Autoregressive Spectrum Analysis

The rapid increase of Internet of Things (IoT) applications and services has led to massive amounts of heterogeneous data. Hence, we need to re-think how IoT data influences the network. In this paper, we study the characteristics of IoT data traffic in the context of smart cities. Aiming at analyzing the influence of IoT data traffic on the access and core network, we generate various IoT data traffic according to the characteristics of different IoT applications. Based on the analysis of the inherent features of the aggregated IoT data traffic, we propose a Long Short-Term Memory (LSTM) model combined with autoregressive spectrum analysis to predict the IoT data traffic. In this model, the autoregressive spectrum analysis is used to estimate the minimum length of the historical data needed for predicting the traffic in the future, which alleviates LSTM's performance deterioration with the increase of sequence length. A sliding window enables predicting the long-term tendency of IoT data traffic while keeping the inherent features of the data traffic. The evaluation results show that the proposed model converges quickly and can predict the variations of IoT traffic more accurately than other methods and the general LSTM model.Peer reviewe

Models and Methods for Network Selection and Balancing in Heterogeneous Scenarios

The outbreak of 5G technologies for wireless communications can be considered a response to the need for widespread coverage, in terms of connectivity and bandwidth, to guarantee broadband services, such as streaming or on-demand programs offered by the main television networks or new generation services based on augmented and virtual reality (AR / VR). The purpose of the study conducted for this thesis aims to solve two of the main problems that will occur with the outbreak of 5G, that is, the search for the best possible connectivity, in order to offer users the resources necessary to take advantage of the new generation services, and multicast as required by the eMBMS. The aim of the thesis is the search for innovative algorithms that will allow to obtain the best connectivity to offer users the resources necessary to use the 5G services in a heterogeneous scenario. Study UF that allows you to improve the search for the best candidate network and to achieve a balance that allows you to avoid congestion of the chosen networks. To achieve these two important focuses, I conducted a study on the main mathematical methods that made it possible to select the network based on QoS parameters based on the type of traffic made by users. A further goal was to improve the computational computation performance they present. Furthermore, I carried out a study in order to obtain an innovative algorithm that would allow the management of multicast. The algorithm that has been implemented responds to the needs present in the eMBMS, in realistic scenarios

Delay models for static and adaptive persistent resource allocations in wireless systems

A variety of scheduling strategies can be employed in wireless systems to satisfy different system objectives and to cater for different traffic types. Static persistent resource allocations can be employed to transfer small M2M data packets efficiently compared to dynamic packet-by-packet scheduling, even when the M2M traffic model is non-deterministic. Recently, adaptive persistent allocations have been proposed in which the volume of allocated resources can change in sympathy with the instantaneous queue size at the M2M device and without expensive signaling on control channels. This increases the efficiency of resource usage at the expense of a (typically small) increased packet delay. In this paper, we derive a statistical model for the device queue size and packet delay in static and adaptive persistent allocations which can be used for any arrival process (i.e., Poisson or otherwise). The primary motivation is to assist with dimensioning of persistent allocations given a set of QoS requirements (such as a prescribed delay budget). We validate the statistical model via comparison with queue size and delay statistics obtained from a discrete event simulation of a persistent allocation system. The validation is performed for both exponential and gamma distributed packet inter-arrivals to demonstrate the model generality

A review on orchestration distributed systems for IoT smart services in fog computing

This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agend

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Scalable software architecture for distributed MMORPG traffic generation based on integration of UrBBaN-Gen and IMUNES

We present a scalable software architecture for distributed traffic generation capable of producing Massively Multiplayer Online Role-Playing Game (MMORPG) packet flows in a statistically accurate manner for thousands of concurrent players. The main challenge, to achieve truly massive scale traffic generation, has been achieved by introducing kernel based virtualization, pioneered by the network simulator/emulator IMUNES, into the User Behaviour Based Network Traffic Generation (UrBBan-Gen, introduced in our earlier work). The UrBBan-Gen software architecture consists of four modules: Service repository, Control function and user interface, Behaviour process, and Traffic generation process. IMUNES has been integratedinto the virtualization part of the Traffic generation process,which has resulted in two improvements: 1) increasing thenumber of generated packet flows while accurately replicating the required statistical properties, and, 2) introducing the ability to run various network scenarios in simulated, as well as real networks, under realistic traffic loads. With respect to the traffic generation capabilities of the previous version of UrBBan-Gen, which was based on Linux containers, the IMUNES based solution demonstrates higher scalability, lower packet loss rates, and lower CPU load for both the UDP traffic at high packet rate and “thin” TCP traffic flows typical for MMORPGs

5G Outlook – Innovations and Applications

5G Outlook - Innovations and Applications is a collection of the recent research and development in the area of the Fifth Generation Mobile Technology (5G), the future of wireless communications. Plenty of novel ideas and knowledge of the 5G are presented in this book as well as divers applications from health science to business modeling. The authors of different chapters contributed from various countries and organizations. The chapters have also been presented at the 5th IEEE 5G Summit held in Aalborg on July 1, 2016. The book starts with a comprehensive introduction on 5G and its need and requirement. Then millimeter waves as a promising spectrum to 5G technology is discussed. The book continues with the novel and inspiring ideas for the future wireless communication usage and network. Further, some technical issues in signal processing and network design for 5G are presented. Finally, the book ends up with different applications of 5G in distinct areas. Topics widely covered in this book are: • 5G technology from past to present to the future• Millimeter- waves and their characteristics• Signal processing and network design issues for 5G• Applications, business modeling and several novel ideas for the future of 5

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Generation and analysis of service-based traffic flows

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The rapid availability of new services makes that network operators cannot exhaustively test their impact on the network or anticipate any capacity exhaustion. This situation will be worse with the imminent introduction of the 5G technology and the kind of totally new services that it will support. In this paper, we present CURSA-SQ, a methodology to analyze the network behavior when the specific traffic that would be generated by groups of service consumers is injected. CURSA-SQ includes input traffic flow modelling with second and sub-second granularity based on specific service and consumer behaviors. The methodology allows to accurately study traffic flows at the input and outputs of complex scenarios with multiples queues systems, as well as other metrics such as delays.This work was partially supported by the EC through the METRO-HAUL project (G.A. nº 761727), from the AEI/FEDER TWINS project (TEC2017-90097-R), and from the Catalan ICREA Institution.Peer ReviewedPostprint (author's final draft