A hybrid intelligent model for network selection in the industrial Internet of Things

Industrial Internet of Things (IIoT) plays an important role in increasing productivity and efficiency in heterogeneous wireless networks. However, different domains such as industrial wireless scenarios, small cell domains and vehicular ad hoc networks (VANET) require an efficient machine learning/intelligent algorithm to process the vertical handover decision that can maintain mobile terminals (MTs) in the preferable networks for a sufficient duration of time. The preferred quality of service parameters can be differentiated from all the other MTs. Hence, in this paper, the problem with the vertical handoff (VHO) decision is articulated as the process of the Markov decision aimed to maximize the anticipated total rewards as well as to minimize the handoffs’ average count. A rewards function is designed to evaluate the QoS at the point of when the connections take place, as that is where the policy decision for a stationary deterministic handoff can be established. The proposed hybrid model merges the biogeography-based optimization (BBO) with the Markov decision process (MDP). The MDP is utilized to establish the radio access technology (RAT) selection’s probability that behaves as an input to the BBO process. Therefore, the BBO determines the best RAT using the described multi-point algorithm in the heterogeneous network. The numerical findings display the superiority of this paper’s proposed schemes in comparison with other available algorithms. The findings shown that the MDP-BBO algorithm is able to outperform other algorithms in terms of number of handoffs, bandwidth availability, and decision delays. Our algorithm displayed better expected total rewards as well as a reduced average account of handoffs compared to current approaches. Simulation results obtained from Monte-Carlo experiments prove validity of the proposed model

DEO: A Smart Dynamic Edge Offloading Scheme using Processing Resources of Nearby Wireless Devices to Form an Edge Computing Engine

Edge computing reduces connectivity costs and network traffic congestion over cloud computing, by offering local resources (processing and storage) at one hop closer to the end-users. I.e. it reduces the Round-Trip Time (RTT) for offloading part of the processing workload from end-nodes/devices to servers at the edge. However, edge servers are normally pre-setup as part of the overall computing resource infrastructure, which is tough to predict for mobile/IoT deployments. This paper introduces a smart Dynamic Edge Offloading scheme, (we named it DEO), that forms the “edge computing resource” on-the-go, as needed from nearby available devices in a cooperative sharing environment. This is especially necessary for hosting mobile/IoT applications traffic at crowded/urban situations, and, for example, when executing a processing intensive Mobile Cloud Computing Service (MCCS) on a Smartphone (SP). DEO implementation is achieved by using a short-range wireless connectivity between available cooperative end-devices, that will form the edge computing resource. DEO includes an intelligent cloud-based engine, that will facilitate the engagement of the edge network devices. For example, if the end-device is a SP running an MCCS, DEO will partition the processing of the MCCS into sub-tasks, that will be run in parallel on the newly formed “edge resource network” of other nearby devices. Our experiments prove that DEO reduces the RTT and cost overhead by 62.8% and 75.5%, when compared to offloading to a local edge server or a cloud-based server

A security and privacy scheme based on node and message authentication and trust in fog-enabled VANET

Security and privacy are the most important concerns related to vehicular ad hoc network (VANET), as it is an open-access and self-organized network. The presence of ‘selfish’ nodes distributed in the network are taken into account as an important challenge and as a security threat in VANET. A selfish node is a legitimate vehicle node which tries to achieve the most benefit from the network by broadcasting wrong information. An efficient and proper security model can be useful to tackle advances from attackers, as well as selfish nodes. In this study, a privacy-preserving node and message authentication scheme, along with a trust model was developed. The proposed node authentication ensures the legitimacy of the vehicle nodes, whereas the message authentication was developed to ensure the message's integrity. To deal with selfish nodes, an experience-based trust model was also designed. Additionally, to fulfill the privacy-preserving aspect, the mapping of each vehicle was performed using a different pseudo-identity. In this paper, fog nodes instead of road-side units (RSUs), were distributed along the roadside. This was mainly because of the fact that fog computing reduces latency, and results in increased throughput. Security analysis indicated that our scheme met the VANETs' security requirements. In addition, the performance analysis showed that the proposed scheme had a lower communication and computation overhead, compared to the other related works. Monte-Carlo simulation results were applied to estimate the false-positive rates (FPR), which also proved the validity of the proposed security scheme

A Smart Edge Computing Resource, formed by On-the-go Networking of Cooperative Nearby Devices using an AI-Offloading Engine, to Solve Computationally Intensive Sub-tasks for Mobile Cloud Services

The latest Mobile Smart Devices (MSDs) and IoT deployments have encouraged the running of “Computation Intensive Applications/Services” onboard MSDs to help us perform on-the-go sub-tasks required by these Apps/Services such as Analysis, Banking, Navigation, Social Media, Gaming, etc. Doing this requires that the MSD have powerful processing resources to reduce execution time, high connectivity throughput to minimise latency and high-capacity battery for power consumption so to not impact the MSD availability/usability in between charges. Offloading such Apps from the host-MSD to a Cloud server does help but introduces network traffic and connectivity overhead issues, even with 5G. Offloading to an Edge server does help, but Edge servers are part of a pre-planned overall computing resource infrastructure, that is tough to predict when demands/rollout is generated by a push from the MSDs/Apps makers and pull by users. To address this issue, this research work has developed a “Smart Edge Computing Resource”, formed on-the-go by the networking of cooperative MSDs/Servers in the vicinity of the host-MSD that is running the computing-intensive App. This solution is achieved by: Developing an intelligent engine, hosted in the Cloud, for profiling “computing-intensive Apps/Services” for appropriately partitioning the overall task into suitable sub-task-chunks so to be executed on the host-MSD together/in association with other available nearby computing resources. Nearby resources can include other MSDs, PCs, iPads and local servers. This is achieved by implementing an “Edge-side Computing Resource engine” that intelligently divides the processing of Apps/Services among several MSDs in parallel. Also, a second “Cloud-side AI-engine” to recruit any available cooperative MSDs and provide the host-MSD with decisions of the best scenario to partition and offload the overall App/Services. It uses a performance scoring algorithm to schedule the sub-tasks to execute on the assisting resource device that has a powerful processor and high-capacity battery power. We built a dataset of 600 scenarios to boost up the offloading decision for further executions, using a Deep Neural Network model. Dynamically forming the on-the-go resource network between the chosen assisting resource devices and the App/Service host-MSD based on the best wireless connectivity possible between them. This is achieved by developing an Importance Priority Weighting cost estimator to calculate the overhead cost and efficiency gain of processing the sub-tasks on the available assisting devices. A local peer-to-peer connectivity protocol is used to communicate, using “Nearby API and/or Post API”. Sub-tasks are offloaded and processed among the participating devices in parallel while results are retrieved upon completion. The results show that our solution has achieved, on average, 40.2% more efficient processing time, 28.8% less battery power consumption and 33% less latency than other methods of executing the same Apps/Services

Enhanced mobility management mechanisms for 5G networks

Many mechanisms that served the legacy networks till now, are being identified as being grossly sub-optimal for 5G networks. The reason being, the increased complexity of the 5G networks compared previous legacy systems. One such class of mechanisms, important for any wireless standard, is the Mobility Management (MM) mechanisms. MM mechanismsensure the seamless connectivity and continuity of service for a user when it moves away from the geographic location where it initially got attached to the network. In this thesis, we firstly present a detailed state of the art on MM mechanisms. Based on the 5G requirements as well as the initial discussions on Beyond 5G networks, we provision a gap analysis for the current technologies/solutions to satisfy the presented requirements. We also define the persistent challenges that exist concerning MM mechanisms for 5G and beyond networks. Based on these challenges, we define the potential solutions and a novel framework for the 5G and beyond MM mechanisms. This framework specifies a set of MM mechanisms at the access, core and the extreme edge network (users/devices) level, that will help to satisfy the requirements for the 5G and beyond MM mechanisms. Following this, we present an on demand MM service concept. Such an on-demand feature provisions the necessary reliability, scalability and flexibility to the MM mechanisms. It's objective is to ensure that appropriate resources and mobility contexts are defined for users who will have heterogeneous mobility profiles, versatile QoS requirements in a multi-RAT network. Next, in this thesis we tackle the problem of core network signaling that occurs during MM in 5G/4G networks. A novel handover signaling mechanism has been developed, which eliminates unnecessary handshakes during the handover preparation phase, while allowing the transition to future softwarized network architectures. We also provide a handover failure aware handover preparation phase signaling process. We then utilize operator data and a realistic network deployment to perform a comparative analysis of the proposed strategy and the 3GPP handover signaling strategy on a network wide deployment scenario. We show the benefits of our strategy in terms of latency of handover process, and the transmission and processing cost incurred. Lastly, a novel user association and resource allocation methodology, namely AURA-5G, has been proposed. AURA-5G addresses scenarios wherein applications with heterogeneous requirements, i.e., enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC), are present simultaneously. Consequently, a joint optimization process for performing the user association and resource allocation while being cognizant of heterogeneous application requirements, has been performed. We capture the peculiarities of this important mobility management process through the various constraints, such as backhaul requirements, dual connectivity options, available access resources, minimum rate requirements, etc., that we have imposed on a Mixed Integer Linear Program (MILP). The objective function of this established MILP problem is to maximize the total network throughput of the eMBB users, while satisfying the minimum requirements of the mMTC and eMBB users defined in a given scenario. Through numerical evaluations we show that our approach outperforms the baseline user association scenario significantly. Moreover, we have presented a system fairness analysis, as well as a novel fidelity and computational complexity analysis for the same, which express the utility of our methodology given the myriad network scenarios.Muchos mecanismos que sirvieron en las redes actuales, se están identificando como extremadamente subóptimos para las redes 5G. Esto es debido a la mayor complejidad de las redes 5G. Un tipo de mecanismo importante para cualquier estándar inalámbrico, consiste en el mecanismo de gestión de la movilidad (MM). Los mecanismos MM aseguran la conectividad sin interrupciones y la continuidad del servicio para un usuario cuando éste se aleja de la ubicación geográfica donde inicialmente se conectó a la red. En esta tesis, presentamos, en primer lugar, un estado del arte detallado de los mecanismos MM. Bas ándonos en los requisitos de 5G, así como en las discusiones iniciales sobre las redes Beyond 5G, proporcionamos un análisis de las tecnologías/soluciones actuales para satisfacer los requisitos presentados. También definimos los desafíos persistentes que existen con respecto a los mecanismos MM para redes 5G y Beyond 5G. En base a estos desafíos, definimos las posibles soluciones y un marco novedoso para los mecanismos 5G y Beyond 5G de MM. Este marco especifica un conjunto de mecanismos MM a nivel de red acceso, red del núcleo y extremo de la red (usuarios/dispositivos), que ayudarán a satisfacer los requisitos para los mecanismos MM 5G y posteriores. A continuación, presentamos el concepto de servicio bajo demanda MM. Tal característica proporciona la confiabilidad, escalabilidad y flexibilidad necesarias para los mecanismos MM. Su objetivo es garantizar que se definan los recursos y contextos de movilidad adecuados para los usuarios que tendrán perfiles de movilidad heterogéneos, y requisitos de QoS versátiles en una red multi-RAT. Más adelante, abordamos el problema de la señalización de la red troncal que ocurre durante la gestión de la movilidad en redes 5G/4G. Se ha desarrollado un nuevo mecanismo de señalización de handover, que elimina los intercambios de mensajes innecesarios durante la fase de preparación del handover, al tiempo que permite la transición a futuras arquitecturas de red softwarizada. Utilizamos los datos de operadores y consideramos un despliegue de red realista para realizar un análisis comparativo de la estrategia propuesta y la estrategia de señalización de 3GPP. Mostramos los beneficios de nuestra estrategia en términos de latencia del proceso de handover y los costes de transmisión y procesado. Por último, se ha propuesto una nueva asociación de usuarios y una metodología de asignación de recursos, i.e, AURA-5G. AURA-5G aborda escenarios en los que las aplicaciones con requisitos heterogéneos, i.e., enhanced Mobile Broadband (eMBB) y massive Machine Type Communications (mMTC), están presentes simultáneamente. En consecuencia, se ha llevado a cabo un proceso de optimización conjunta para realizar la asociación de usuarios y la asignación de recursos mientras se tienen en cuenta los requisitos de aplicaciónes heterogéneas. Capturamos las peculiaridades de este importante proceso de gestión de la movilidad a través de las diversas restricciones impuestas, como son los requisitos de backhaul, las opciones de conectividad dual, los recursos de la red de acceso disponibles, los requisitos de velocidad mínima, etc., que hemos introducido en un Mixed Integer Linear Program (MILP). La función objetivo de este problema MILP es maximizar el rendimiento total de la red de los usuarios de eMBB, y a la vez satisfacer los requisitos mínimos de los usuarios de mMTC y eMBB definidos en un escenario dado. A través de evaluaciones numéricas, mostramos que nuestro enfoque supera significativamente el escenario de asociación de usuarios de referencia. Además, hemos presentado un análisis de la justicia del sistema, así como un novedoso análisis de fidelidad y complejidad computacional para el mismo, que expresa la utilidad de nuestra metodología.Postprint (published version

Enhanced mobility management mechanisms for 5G networks

Many mechanisms that served the legacy networks till now, are being identified as being grossly sub-optimal for 5G networks. The reason being, the increased complexity of the 5G networks compared previous legacy systems. One such class of mechanisms, important for any wireless standard, is the Mobility Management (MM) mechanisms. MM mechanismsensure the seamless connectivity and continuity of service for a user when it moves away from the geographic location where it initially got attached to the network. In this thesis, we firstly present a detailed state of the art on MM mechanisms. Based on the 5G requirements as well as the initial discussions on Beyond 5G networks, we provision a gap analysis for the current technologies/solutions to satisfy the presented requirements. We also define the persistent challenges that exist concerning MM mechanisms for 5G and beyond networks. Based on these challenges, we define the potential solutions and a novel framework for the 5G and beyond MM mechanisms. This framework specifies a set of MM mechanisms at the access, core and the extreme edge network (users/devices) level, that will help to satisfy the requirements for the 5G and beyond MM mechanisms. Following this, we present an on demand MM service concept. Such an on-demand feature provisions the necessary reliability, scalability and flexibility to the MM mechanisms. It's objective is to ensure that appropriate resources and mobility contexts are defined for users who will have heterogeneous mobility profiles, versatile QoS requirements in a multi-RAT network. Next, in this thesis we tackle the problem of core network signaling that occurs during MM in 5G/4G networks. A novel handover signaling mechanism has been developed, which eliminates unnecessary handshakes during the handover preparation phase, while allowing the transition to future softwarized network architectures. We also provide a handover failure aware handover preparation phase signaling process. We then utilize operator data and a realistic network deployment to perform a comparative analysis of the proposed strategy and the 3GPP handover signaling strategy on a network wide deployment scenario. We show the benefits of our strategy in terms of latency of handover process, and the transmission and processing cost incurred. Lastly, a novel user association and resource allocation methodology, namely AURA-5G, has been proposed. AURA-5G addresses scenarios wherein applications with heterogeneous requirements, i.e., enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC), are present simultaneously. Consequently, a joint optimization process for performing the user association and resource allocation while being cognizant of heterogeneous application requirements, has been performed. We capture the peculiarities of this important mobility management process through the various constraints, such as backhaul requirements, dual connectivity options, available access resources, minimum rate requirements, etc., that we have imposed on a Mixed Integer Linear Program (MILP). The objective function of this established MILP problem is to maximize the total network throughput of the eMBB users, while satisfying the minimum requirements of the mMTC and eMBB users defined in a given scenario. Through numerical evaluations we show that our approach outperforms the baseline user association scenario significantly. Moreover, we have presented a system fairness analysis, as well as a novel fidelity and computational complexity analysis for the same, which express the utility of our methodology given the myriad network scenarios.Muchos mecanismos que sirvieron en las redes actuales, se están identificando como extremadamente subóptimos para las redes 5G. Esto es debido a la mayor complejidad de las redes 5G. Un tipo de mecanismo importante para cualquier estándar inalámbrico, consiste en el mecanismo de gestión de la movilidad (MM). Los mecanismos MM aseguran la conectividad sin interrupciones y la continuidad del servicio para un usuario cuando éste se aleja de la ubicación geográfica donde inicialmente se conectó a la red. En esta tesis, presentamos, en primer lugar, un estado del arte detallado de los mecanismos MM. Bas ándonos en los requisitos de 5G, así como en las discusiones iniciales sobre las redes Beyond 5G, proporcionamos un análisis de las tecnologías/soluciones actuales para satisfacer los requisitos presentados. También definimos los desafíos persistentes que existen con respecto a los mecanismos MM para redes 5G y Beyond 5G. En base a estos desafíos, definimos las posibles soluciones y un marco novedoso para los mecanismos 5G y Beyond 5G de MM. Este marco especifica un conjunto de mecanismos MM a nivel de red acceso, red del núcleo y extremo de la red (usuarios/dispositivos), que ayudarán a satisfacer los requisitos para los mecanismos MM 5G y posteriores. A continuación, presentamos el concepto de servicio bajo demanda MM. Tal característica proporciona la confiabilidad, escalabilidad y flexibilidad necesarias para los mecanismos MM. Su objetivo es garantizar que se definan los recursos y contextos de movilidad adecuados para los usuarios que tendrán perfiles de movilidad heterogéneos, y requisitos de QoS versátiles en una red multi-RAT. Más adelante, abordamos el problema de la señalización de la red troncal que ocurre durante la gestión de la movilidad en redes 5G/4G. Se ha desarrollado un nuevo mecanismo de señalización de handover, que elimina los intercambios de mensajes innecesarios durante la fase de preparación del handover, al tiempo que permite la transición a futuras arquitecturas de red softwarizada. Utilizamos los datos de operadores y consideramos un despliegue de red realista para realizar un análisis comparativo de la estrategia propuesta y la estrategia de señalización de 3GPP. Mostramos los beneficios de nuestra estrategia en términos de latencia del proceso de handover y los costes de transmisión y procesado. Por último, se ha propuesto una nueva asociación de usuarios y una metodología de asignación de recursos, i.e, AURA-5G. AURA-5G aborda escenarios en los que las aplicaciones con requisitos heterogéneos, i.e., enhanced Mobile Broadband (eMBB) y massive Machine Type Communications (mMTC), están presentes simultáneamente. En consecuencia, se ha llevado a cabo un proceso de optimización conjunta para realizar la asociación de usuarios y la asignación de recursos mientras se tienen en cuenta los requisitos de aplicaciónes heterogéneas. Capturamos las peculiaridades de este importante proceso de gestión de la movilidad a través de las diversas restricciones impuestas, como son los requisitos de backhaul, las opciones de conectividad dual, los recursos de la red de acceso disponibles, los requisitos de velocidad mínima, etc., que hemos introducido en un Mixed Integer Linear Program (MILP). La función objetivo de este problema MILP es maximizar el rendimiento total de la red de los usuarios de eMBB, y a la vez satisfacer los requisitos mínimos de los usuarios de mMTC y eMBB definidos en un escenario dado. A través de evaluaciones numéricas, mostramos que nuestro enfoque supera significativamente el escenario de asociación de usuarios de referencia. Además, hemos presentado un análisis de la justicia del sistema, así como un novedoso análisis de fidelidad y complejidad computacional para el mismo, que expresa la utilidad de nuestra metodología