Christian Inzinger

Bio: Christian Inzinger is an academic researcher from University of Zurich. The author has contributed to research in topics: Cloud computing & Smart city. The author has an hindex of 17, co-authored 35 publications receiving 777 citations. Previous affiliations of Christian Inzinger include Vienna University of Technology.

Winds of Change: From Vendor Lock-In to the Meta Cloud

Abstract: The emergence of yet more cloud offerings from a multitude of service providers calls for a meta cloud to smoothen the edges of the jagged cloud landscape. This meta cloud could solve the vendor lock-in problems that current public and hybrid cloud users face.

A Scalable Framework for Provisioning Large-Scale IoT Deployments

Abstract: Internet of Things (IoT) devices are usually considered external application dependencies that only provide data or process and execute simple instructions. The recent emergence of IoT devices with embedded execution environments allows practitioners to deploy and execute custom application logic directly on the device. This approach fundamentally changes the overall process of designing, developing, deploying, and managing IoT systems. However, these devices exhibit significant differences in available execution environments, processing, and storage capabilities. To accommodate this diversity, a structured approach is needed to uniformly and transparently deploy application components onto a large number of heterogeneous devices. This is especially important in the context of large-scale IoT systems, such as in the smart city domain. In this article, we present LEONORE, an infrastructure toolset that provides elastic provisioning of application components on resource-constrained and heterogeneous edge devices in large-scale IoT deployments. LEONORE supports push-based as well as pull-based deployments. To improve scalability and reduce generated network traffic between cloud and edge infrastructure, we present a distributed provisioning approach that deploys LEONORE local nodes within the deployment infrastructure close to the actual edge devices. We show that our solution is able to elastically provision large numbers of devices using a testbed based on a real-world industry scenario.

Application-level performance monitoring of cloud services based on the complex event processing paradigm

Abstract: Monitoring of applications deployed to Infrastructure-as-a-Service clouds is still an open problem. In this paper, we discuss an approach based on the complex event processing paradigm, which allows application developers to specify and monitor high-level application performance metrics. We use the case of a Web 2.0 sentiment analysis application to illustrate the limitations we currently experience with regard to cloud monitoring, and show how our approach allows for more expressive definitions of monitored metrics. Furthermore, we indicate how the higher-level metrics produced by our approach can be used to increase application elasticity in an existing cloud middleware.

Cost-Efficient and Application SLA-Aware Client Side Request Scheduling in an Infrastructure-as-a-Service Cloud

Abstract: Providers of applications deployed in an Infrastructure-as-a-Service cloud permanently face the decision of whether it is more cost-efficient to scale up(i.e., rent more resources from the cloud) or to delay incoming requests, even though doing so may lead to dissatisfied customers and broken service level agreements. This decision is further complicated by the fact that not all customers have the same agreements, and not all requests require the same amount of resources devoted to them. In this paper, we present an approach for optimally scheduling incoming requests to virtual computing resources in the cloud, so that the sum of payments for resources and loss incurred by service level agreement violations is minimized. We discuss our approach based on an illustrative use case. Furthermore, we present a numerical evaluation based on real-life request data, which shows that our agreement-aware algorithm improves upon earlier work, which does not take service level agreements into account.

Enabling a Smart City Application Ecosystem: Requirements and Architectural Aspects

Abstract: Cities are becoming increasingly "smart," but they need an underlying foundation that handles and manages all the lower-level complexities. In this article, the authors discuss relevant challenges and building blocks of a Smart City Application Ecosystem (SCALE).

Smart Cities: A Survey on Data Management, Security, and Enabling Technologies

Abstract: Integrating the various embedded devices and systems in our environment enables an Internet of Things (IoT) for a smart city. The IoT will generate tremendous amount of data that can be leveraged for safety, efficiency, and infotainment applications and services for city residents. The management of this voluminous data through its lifecycle is fundamental to the realization of smart cities. Therefore, in contrast to existing surveys on smart cities we provide a data-centric perspective, describing the fundamental data management techniques employed to ensure consistency, interoperability, granularity, and reusability of the data generated by the underlying IoT for smart cities. Essentially, the data lifecycle in a smart city is dependent on tightly coupled data management with cross-cutting layers of data security and privacy, and supporting infrastructure. Therefore, we further identify techniques employed for data security and privacy, and discuss the networking and computing technologies that enable smart cities. We highlight the achievements in realizing various aspects of smart cities, present the lessons learned, and identify limitations and research challenges.

Distributed event-based systems

Abstract: This book provides an in-depth description of event-based systems, covering topics ranging from local event matching and distributed event forwarding algorithms, through a practical discussion of software engineering issues raised by the event-based style, to state-of-the-art research in event-based systems like composite event detection and security. The authors offer a comprehensive overview, and show the power of event-based architectures in modern system design, encouraging professionals to exploit this technique in next generation large-scale distributed applications like information dissemination, network monitoring, enterprise application integration, or mobile systems.

Containerization and the PaaS Cloud

Abstract: Containerization is widely discussed as a lightweight virtualization solution. Apart from exhibiting benefits over traditional virtual machines in the cloud, containers are especially relevant for platform-as-a-service (PaaS) clouds to manage and orchestrate applications through containers as an application packaging mechanism. This article discusses the requirements that arise from having to facilitate applications through distributed multicloud platforms.

A Supervised Intrusion Detection System for Smart Home IoT Devices

Abstract: The proliferation in Internet of Things (IoT) devices, which routinely collect sensitive information, is demonstrated by their prominence in our daily lives. Although such devices simplify and automate every day tasks, they also introduce tremendous security flaws. Current insufficient security measures employed to defend smart devices make IoT the “weakest” link to breaking into a secure infrastructure, and therefore an attractive target to attackers. This paper proposes a three layer intrusion detection system (IDS) that uses a supervised approach to detect a range of popular network based cyber-attacks on IoT networks. The system consists of three main functions: 1) classify the type and profile the normal behavior of each IoT device connected to the network; 2) identifies malicious packets on the network when an attack is occurring; and 3) classifies the type of the attack that has been deployed. The system is evaluated within a smart home testbed consisting of eight popular commercially available devices. The effectiveness of the proposed IDS architecture is evaluated by deploying 12 attacks from 4 main network based attack categories, such as denial of service (DoS), man-in-the-middle (MITM)/spoofing, reconnaissance, and replay. Additionally, the system is also evaluated against four scenarios of multistage attacks with complex chains of events. The performance of the system’s three core functions result in an ${F}$ -measure of: 1) 96.2%; 2) 90.0%; and 3) 98.0%. This demonstrates that the proposed architecture can automatically distinguish between IoT devices on the network, whether network activity is malicious or benign, and detect which attack was deployed on which device connected to the network successfully.