Software Defined Applications in Cellular and Optical Networks

abstract: Small wireless cells have the potential to overcome bottlenecks in wireless access through the sharing of spectrum resources. A novel access backhaul network architecture based on a Smart Gateway (Sm-GW) between the small cell base stations, e.g., LTE eNBs, and the conventional backhaul gateways, e.g., LTE Servicing/Packet Gateways (S/P-GWs) has been introduced to address the bottleneck. The Sm-GW flexibly schedules uplink transmissions for the eNBs. Based on software defined networking (SDN) a management mechanism that allows multiple operator to flexibly inter-operate via multiple Sm-GWs with a multitude of small cells has been proposed. This dissertation also comprehensively survey the studies that examine the SDN paradigm in optical networks. Along with the PHY functional split improvements, the performance of Distributed Converged Cable Access Platform (DCCAP) in the cable architectures especially for the Remote-PHY and Remote-MACPHY nodes has been evaluated. In the PHY functional split, in addition to the re-use of infrastructure with a common FFT module for multiple technologies, a novel cross functional split interaction to cache the repetitive QAM symbols across time at the remote node to reduce the transmission rate requirement of the fronthaul link has been proposed.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Bringing pervasive embedded networks to the service cloud: a lightweight middleware approach

The emergence of novel pervasive networks that consist of tiny embedded nodes have reduced the gap between real and virtual worlds. This paradigm has opened the Service Cloud to a variety of wireless devices especially those with sensorial and actuating capabilities. Those pervasive networks contribute to build new context-aware applications that interpret the state of the physical world at real-time. However, traditional Service-Oriented Architectures (SOA), which are widely used in the current Internet are unsuitable for such resource-constraint devices since they are too heavy. In this research paper, an internetworking approach is proposed in order to address that important issue. The main part of our proposal is the Knowledge-Aware and Service-Oriented (KASO) Middleware that has been designed for pervasive embedded networks. KASO Middleware implements a diversity of mechanisms, services and protocols which enable developers and business processing designers to deploy, expose, discover, compose, and orchestrate real-world services (i.e. services running on sensor/actuator devices). Moreover, KASO Middleware implements endpoints to offer those services to the Cloud in a REST manner. Our internetworking approach has been validated through a real healthcare telemonitoring system deployed in a sanatorium. The validation tests show that KASO Middleware successfully brings pervasive embedded networks to the Service Cloud

Managing Event-Driven Applications in Heterogeneous Fog Infrastructures

The steady increase in digitalization propelled by the Internet of Things (IoT) has led to a deluge of generated data at unprecedented pace. Thereby, the promise to realize data-driven decision-making is a major innovation driver in a myriad of industries. Based on the widely used event processing paradigm, event-driven applications allow to analyze data in the form of event streams in order to extract relevant information in a timely manner. Most recently, graphical flow-based approaches in no-code event processing systems have been introduced to significantly lower technological entry barriers. This empowers non-technical citizen technologists to create event-driven applications comprised of multiple interconnected event-driven processing services. Still, today’s event-driven applications are focused on centralized cloud deployments that come with inevitable drawbacks, especially in the context of IoT scenarios that require fast results, are limited by the available bandwidth, or are bound by the regulations in terms of privacy and security. Despite recent advances in the area of fog computing which mitigate these shortcomings by extending the cloud and moving certain processing closer to the event source, these approaches are hardly established in existing systems. Inherent fog computing characteristics, especially the heterogeneity of resources alongside novel application management demands, particularly the aspects of geo-distribution and dynamic adaptation, pose challenges that are currently insufficiently addressed and hinder the transition to a next generation of no-code event processing systems. The contributions of this thesis enable citizen technologists to manage event-driven applications in heterogeneous fog infrastructures along the application life cycle. Therefore, an approach for a holistic application management is proposed which abstracts citizen technologists from underlying technicalities. This allows to evolve present event processing systems and advances the democratization of event-driven application management in fog computing. Individual contributions of this thesis are summarized as follows: 1. A model, manifested in a geo-distributed system architecture, to semantically describe characteristics specific to node resources, event-driven applications and their management to blend application-centric and infrastructure-centric realms. 2. Concepts for geo-distributed deployment and operation of event-driven applications alongside strategies for flexible event stream management. 3. A methodology to support the evolution of event-driven applications including methods to dynamically reconfigure, migrate and offload individual event-driven processing services at run-time. The contributions are introduced, applied and evaluated along two scenarios from the manufacturing and logistics domain

The First Verification Test of Space-Ground Collaborative Intelligence via Cloud-Native Satellites

Recent advancements in satellite technologies and the declining cost of access to space have led to the emergence of large satellite constellations in Low Earth Orbit. However, these constellations often rely on bent-pipe architecture, resulting in high communication costs. Existing onboard inference architectures suffer from limitations in terms of low accuracy and inflexibility in the deployment and management of in-orbit applications. To address these challenges, we propose a cloud-native-based satellite design specifically tailored for Earth Observation tasks, enabling diverse computing paradigms. In this work, we present a case study of a satellite-ground collaborative inference system deployed in the Tiansuan constellation, demonstrating a remarkable 50\% accuracy improvement and a substantial 90\% data reduction. Our work sheds light on in-orbit energy, where in-orbit computing accounts for 17\% of the total onboard energy consumption. Our approach represents a significant advancement of cloud-native satellite, aiming to enhance the accuracy of in-orbit computing while simultaneously reducing communication cost.Comment: Accepted by China Communication