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Edge computing and CAV (Connected Autonomous Vehicle) fields can work as a team. With the short latency and high responsiveness of edge computing, it is a better fit than cloud computing in the CAV field. Moreover, containerized applications are getting rid of the annoying procedures for setting the required environment. So that deployment of applications on new machines is much more user-friendly than before. Therefore, this paper proposes a framework developed for the CAV edge computing scenario. This framework consists of various programs written in different languages. The framework uses Docker technology to containerize these applications so that the deployment could be simple and easy. This framework consists of two parts. One is for the vehicle on-board unit, which exposes data to the closest edge device and receives the output generated by the edge device. Another is for the edge device, which is responsible for collecting and processing big load of data and broadcasting output to vehicles. So the vehicle does not need to perform the heavyweight tasks that could drain up the limited power.

Boundary-layer flow over bodies such as aircraft wings or turbine blades is characterized by a pressure gradient due to the curved surface of the body. The boundary layer may experience modal and non-modal instability, and the type of dominant instability depends on whether the body is swept with respect to the oncoming flow or not. The growth of these disturbances causes transition of the boundary-layer flow to turbulence. Provided that they are convective in nature, the instabilities will only arise and persist if the boundary layer is continuously exposed to a perturbation environment. This may for example consist of turbulent fluctuations or sound waves in the free stream or of non-uniformities on the surface of the body. In engineering, it is of relevance to understand how susceptive to such perturbations the boundary layer is, and this issue is subject of receptivity analysis.   In this thesis, receptivity of simplified prototypes for flow past a wing is studied. In particular, the three-dimensional swept-plate boundary layer and the boundary layer forming on a flat plate with elliptic leading edge are considered. The response of the boundary layer to vortical free-stream disturbances and surface roughness is analyzed, receptivity mechanisms are identified and their efficiency is quantified. / QC 20101022 / 76218 VR Receptivity

Mobile edge computing (MEC) has recently been introduced as a key technology, emerging in response to the increased focus on the emergence of new heterogeneous computing applications, resource-constrained mobile devices, and the long delay of traditional cloud data centers. Although many researchers have studied how the heterogeneous latency-critical application requirements can interact with the MEC system, very few have addressed how to deploy a flexible and scalable MEC infrastructure at the mobile operator for the expected heterogeneous mobile traffic. The proposed system model in this research project relies on the Network Function Virtualization (NFV) concept to virtualize the MEC infrastructure and provide scalable and flexible infrastructure regardless of the underlying physical hardware. In NFV-enabled networks, the received mobile workload is often deployed as Service Function Chains (SFCs), responsible for accomplishing users' service requests by steering traffic through different VNF types and virtual links. Thus, efficient VNF placement and orchestration mechanisms are required to address the challenges of the heterogenous users' requests, various Quality of Service (QoS) requirements, and network traffic dynamicity. This research project addresses the scalable design and dimensioning of an agile NFV-enabled MEC infrastructure problem from a dual perspective. First, a neural network model (i.e., a subset of machine learning) helps proactively auto-scale the various virtual service instances by predicting the number of SFCs required for a time-varying mobile traffic load. Second, the Mixed-Integer Linear Program (MILP) is used to create a physical MEC system infrastructure by mapping the predicted virtual SFC networks to the MEC nodes while minimizing deployment costs. Numerical results show that the machine learning (ML) model achieves a high prediction accuracy of 95.6%, which demonstrates the added value of using the ML technique at the edge network in reducing deployment costs while ensuring delay requirements for different latency-critical applications with high acceptance rates. Due to the exponential nature of this MILP formulation, we also propose a scalable bender decomposition approach with near-optimal results at a significantly reduced design and dimensioning cost. Numerical results show the viability of the bender decomposition approach in its proximity to the optimal dimensioning cost and in its reasonable solution time.

Edge representations of operators on closed manifolds are known to induce large classes of operators that are elliptic on specific manifolds with edges, cf. [9]. We apply this idea to the case of boundary value problems. We establish a correspondence between standard ellipticity and ellipticity with respect to the principal symbolic hierarchy of the edge algebra of boundary value problems, where an embedded submanifold on the boundary plays the role of an edge. We first consider the case that the weight is equal to the smoothness and calculate the dimensions of kernels and cokernels of the associated principal edge symbols. Then we pass to elliptic edge operators for arbitrary weights and construct the additional edge conditions by applying relative index results for conormal symbols.

Let u and v be vertices of a graph G, such that the distance between u and v is two and x is a common neighbor of u and v. We define the edge lift of uv off x as the process of removing edges ux and vx while adding the edge uv to G. In this paper, we investigate the effect that edge lifting has on the total domination number of a graph. Among other results, we show that there are no trees for which every possible edge lift decreases the total domination number and that there are no trees for which every possible edge lift leaves the total domination number unchanged. Trees for which every possible edge lift increases the total domination number are characterized.

Let u and v be vertices of a graph G, such that the distance between u and v is two and x is a common neighbor of u and v. We define the edge lift of uv off x as the process of removing edges ux and vx while adding the edge uv to G. In this paper, we investigate the effect that edge lifting has on the total domination number of a graph. Among other results, we show that there are no trees for which every possible edge lift decreases the total domination number and that there are no trees for which every possible edge lift leaves the total domination number unchanged. Trees for which every possible edge lift increases the total domination number are characterized.

A set S of vertices in a graph G is a total dominating set of G if every vertex of G is adjacent to some vertex in S. The minimum cardinality of a total dominating set of G is the total domination number of G. A graph is total domination edge critical if the removal of any arbitrary edge increases the total domination number. On the other hand, a graph is total domination edge stable if the removal of any arbitrary edge has no effect on the total domination number. In this paper, we characterize total domination edge critical graphs. We also investigate various properties of total domination edge stable graphs.

This thesis introduces a novel framework for edge robotics, enabling the advancement of edge-connected and controlled robots. Autonomous robots, such as Unmanned Aerial Vehicles (UAVs), generate vast amounts of multi-sensor data and rely on complex algorithms. However, their computational requirements often necessitate large onboard computing units, limiting their flight time and payload capacity. This work presents a key contribution towards the development of frameworks that facilitate offloading computational processes from robots to edge computing clusters. Specifically, we focus on offloading computationally intensive Model Predictive Control (MPC) algorithms for UAV trajectory control. To address the time-critical nature of these procedures, we also consider latency and safety measures. By leveraging edge computing, we can achieve the required computational capacity while minimizing communication latency, making it a promising solution for such missions. Furthermore, edge computing enhances the performance and efficiency of MPCs compared to traditional onboard computers. We evaluate this improvement and compare it to conventional approaches. Additionally, we leverage Docker Images and Kubernetes Clusters to take advantage of their features, enabling fast and easy deployment, operability, and migrations of the MPC instances. Kubernetes automates, monitors, and orchestrates the system’s behavior, while the controller applications become highly portable without extensive software dependencies. This thesis focuses on developing real architectures for offloading MPCs either for controlling the trajectory of single robots or multi-agent systems, while utilizing both on-premises small-scale edge computing setups and edge computing providers like the Research Institutes of Sweden (RISE) in Luleå. Extensive simulations and real-life experimental setups support the results and assumptions presented in this work.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / When designing data transport systems, Telemetry and Communications engineers always face the risk that their chosen hardware will not be available or supported soon after the hardware has been installed. The best way to reduce this risk and ensure the longevity of the system is to select an open architecture standard that is supported by multiple manufacturers. This open architecture should also have the ability to be easily upgraded and provide for all of the features and flexibility that are required to be a reliable carrier-grade edge-device. The PCI Industrial Computer Manufacturers Group (PICMG) developed the MicroTCA open standard to address the specific needs of these Communications and Network System Engineers. This paper describes the MicroTCA architecture and how it can be applied as the ideal edge-device solution for Networked Telemetry Systems applications.