Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

Federated Machine Learning in Vehicular Networks: a Summary of Recent Applications

Future Intelligent Transportation Systems (ITS) can improve on-road safety and transportation efficiency and vehicular networks (VNs) are essential to enable ITS applications via information sharing. The development of 5G introduces new technologies providing improved support for connected vehicles through highly dynamic heterogeneous networks. Machine Learning (ML) can capture the high dynamics of VNs but the distributed data cause new challenges for ML hence requires distributed solutions. Federated learning (FL), a distributed ML framework, gives a distributed ML framework while ensuring information privacy protection and is an exciting area to explore in VNs. This article provides a detailed summary of recent FL applications in VNs and gives insights on current research challenges. The included research topics are resource management, performance optimization and applications based on VNs

Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural Scenes

Sensor or camera networks will play an important role in future applications, from surveillance tasks for workplace safety or security in general, over driver assisting systems in automotive and last but not least intelligent homes or assisted living for the elderly. Computer vision in sensor or camera networks defines a couple of currently unsolved problems. First of all, how can we calibrate cameras distributed arbitrarily in the scene without placing artificial or natural calibration patterns in the scene? Second, how do we select and fuse the information provided by different, also multimodal sensors to solve a given problem? Finally, can we handle reconstruction, recognition and tracking tasks in complex and highly dynamic natural scenes which are in almost all cases the environment camera networks are designed for

Intrusion Detection in Industrial Networks via Data Streaming

Given the increasing threat surface of industrial networks due to distributed, Internet-of-Things (IoT) based system architectures, detecting intrusions in\ua0 Industrial IoT (IIoT) systems is all the more important, due to the safety implications of potential threats. The continuously generated data in such systems form both a challenge but also a possibility: data volumes/rates are high and require processing and communication capacity but they contain information useful for system operation and for detection of unwanted situations.In this chapter we explain that\ua0 stream processing (a.k.a. data streaming) is an emerging useful approach both for general applications and for intrusion detection in particular, especially since it can enable data analysis to be carried out in the continuum of edge-fog-cloud distributed architectures of industrial networks, thus reducing communication latency and gradually filtering and aggregating data volumes. We argue that usefulness stems also due to\ua0 facilitating provisioning of agile responses, i.e. due to potentially smaller latency for intrusion detection and hence also improved possibilities for intrusion mitigation. In the chapter we outline architectural features of IIoT networks, potential threats and examples of state-of-the art intrusion detection methodologies. Moreover, we give an overview of how leveraging distributed and parallel execution of streaming applications in industrial setups can influence the possibilities of protecting these systems. In these contexts, we give examples using electricity networks (a.k.a. Smart Grid systems).We conclude that future industrial networks, especially their Intrusion Detection Systems (IDSs), should take advantage of data streaming concept by decoupling semantics from the deployment

Autonomic management of software defined networks : DAIM can provide the environment for building autonomy in distributed electronic environments - using OpenFlow networks as the case study

University of Technology Sydney. Faculty of Engineering and Information Technology.Next generation networks need to support a broad range of services and functionalities with capabilities such as autonomy, scalability, and adaptability for managing networks complexity. In present days, network infrastructures are becoming increasingly complex and challenging to administer due to scale and heterogeneous nature of the infrastructures. Furthermore, among various vendors, services, and platforms, managing networks require expert operators who have expertise in all different fields. This research relied on distributed active information model (DAIM) to establish a foundation which will meet future network management requirements. The DAIM is an information model for network solutions which considers challenges of autonomic functionalities, where the network devices can make local and overall network decisions by collected information. The DAIM model can facilitate networks management by introducing autonomic behaviours. The autonomic behaviours for communication networks lead networks to be self-managed and emerge as promising solutions to manage networks complexity. Autonomic networks management aims at reducing the workload on network operators from low-level tasks. Over the years, researchers have proposed a number of models for developing self-managed network solutions. One such example is the common information model (CIM), which is described as the managed environment that attempts to merge and extend the existing conventional management and also uses object-oriented constructs for overall network representation. However, the CIM has limitations coping in complex distributed electronic environments with multiple disciplines. The goal of this research is defined as development of a network architecture or a solution based on the DAIM model, which is effectively distribute and automate network’s functions to various network devices. The research first looks into the possibilities of local decision-making and programmability of network elements for distributed electronic environments with an intention to simplify network management by providing abstracted network infrastructures. After investigating and implementing different elements of the DAIM model in network forwarding devices by utilising virtual network switches, it discovers that a common high-level interface and framework for network devices are essential for the development of network solutions which will meet future network requirements. The outcome of this research is the development of (DAIM OS) specification. The DAIM OS is a network forwarding device operating system which is compliant with the DAIM model when it comes to network infrastructure management and provides a high-level abstracted application programming interface (DAIM OS API) for creating network service applications. Through the DAIM OS, network elements will be able to adapt to ever changing environments to meet the goals of service providers, vendors, and end users. Furthermore, the DAIM OS API aims to reduce complexity and time of network service applications development. If the developed DAIM OS specification is implemented and if it functions as predicted in the design analyses; that will result in a significant milestone in the development of distributed network management. This dissertation has an introduction in chapter 1 followed by five parts in order to draw a blueprint for information model as a distributed independent computing environment for autonomic network management. The five parts include lending weight to the proposition, gaining confidence in the proposition, drawing conclusions, supporting work and lastly is appendices. The introduction in chapter 1 includes motivations for the research, main challenges of the research, overall objectives, and review of research contributions. After that, to lend weight to the proposition as the first part of the dissertation, there is chapter 2 which presents the background and literature review, and chapter 3 which has a theoretical foundation for the proposed model. The foundation consists of a generic architecture for complex network management and agents to aggregate distributed network information. Moreover, chapter 3 is probably more about a state of the art in software engineering than about real implementation to engineer autonomic network management. The second part of the dissertation is to gain confidence in the proposition which includes attempting to implement the DAIM model in chapter 4 with some tests to report good performance regarding convergence and robustness for the service configuration process of network management. Also, the second part has a specification of true abstraction layers in chapter 5. The specification of true abstraction layers proposes a high-level abstraction for forwarding networking devices and provides an application program interface for network service applications developed by network operators and service providers. The implementation in chapter 4 is supported by the fourth part of the dissertation in chapter 10 which supports the theoretical foundation, designing, modelling, and developing the distributed active information model via simulation, emulation and real environments. The third part of this dissertation provides the way to draw conclusions as shown in chapter 7 which has the overall research summary, validation of the propositions, contributions and discussion, limitations and finally recommendations for future works. Finally are the appendices in Appendix A, Appendix B, Appendix C and Appendix D which provide a developing code of the core DAIM model and show different setting up for testbed environments