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    Item type:Publication,
    Context-aware routing in fog computing systems
    Fog computing enables the execution of IoT applications on compute nodes which reside both in the cloud and at the edge of the network. To achieve this, most fog computing systems route the IoT data on a path which starts at the data source, and goes through various edge and cloud nodes. Each node on this path may accept the data if there are available resources to process this data locally. Otherwise, the data is forwarded to the next node on path. Notably, when the data is forwarded (rather than accepted), the communication latency increases by the delay to reach the next node. To avoid this, we propose a routing mechanism which maintains a history of all nodes that have accepted data of each context in the past. By processing this history, our mechanism sends the data directly to the closest node that tends to accept data of the same context. This lowers the forwarding by nodes on path, and can reduce the communication latency. We evaluate this approach using both prototype- and simulation-based experiments which show reduced communication latency (by up to 23%) and lower number of hops traveled (by up to 73%), compared to a state-of-the-art method.
    Publicationtype: Journal Article
      63
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    Item type:Publication,
    Towards Extensibility-Aware Scheduling of Industrial Applications on Fog Nodes
    Fog computing has been identified as an enabler for many modern technologies like connected vehicles and the Industrial Internet of Things (IIoT). Such technologies are characterized by the integration of applications with different levels of criticality on shared platforms, which are referred to as mixed-criticality systems. Mixed-criticality systems typically use static scheduling for critical tasks; however, static scheduling is not suitable for scenarios where fog nodes run dynamic noncritical applications that implement, e.g., maintenance checks and data analytics. To address this challenge, in this paper, we differentiate between critical tasks that are statically allocated (called 'native') and dynamic non-critical tasks that may migrate across fog nodes (called 'temporary'). We propose a static scheduling approach that maximizes the number of temporary tasks that can be added at runtime, without negatively impacting the already scheduled native tasks. This approach enables fog nodes to become more suitable for IIoT environments by configuring them with extensible schedules for the native tasks. To evaluate our approach, we perform experiments considering several test cases, which show that given a number of native tasks, the generated extensible schedules enable the fog nodes to run a larger number of temporary tasks at the same time. Furthermore, the extensible schedules exhibit 7.8 % less missed deadlines (on averaae), compared to the non-extensible schedules. To address this challenge, in this paper, we differentiate between critical tasks that are statically allocated (called 'native') and dynamic non-critical tasks that may migrate across fog nodes (called 'temporary'). We propose a static scheduling approach that maximizes the number of temporary tasks that can be added at runtime, without negatively impacting the already scheduled native tasks. This approach enables fog nodes to become more suitable for IIoT environments by configuring them with extensible schedules for the native tasks. To evaluate our approach, we perform experiments considering several test cases, which show that given a number of native tasks, the generated extensible schedules enable the fog nodes to run a larger number of temporary tasks at the same time. Furthermore, the extensible schedules exhibit 7.8 % less missed deadlines (on averaae), compared to the non-extensible schedules.
    Publicationtype: Conference Paper
      18
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    Item type:Publication,
    Nomadic applications traveling in the fog
    The emergence of the Internet of Things introduces new challenges like network congestion or data privacy. However, it also provides opportunities, such as computational resources close to data sources, which can be pooled to realize Fogs to run software applications on the edge of the network. To foster this new type of resources, we revisit the concept of mobile agents and evolve them to so-called nomadic applications, which allow addressing vital challenges for the Internet of Things. In this paper, we propose a system design to realize nomadic applications and discuss several challenges that need to be addressed in order to apply them to real-world scenarios.
    Publicationtype: Conference Paper
      22