Concurrency Controls in Event-Driven Programs

Functional reactive programming (FRP) is a programming paradigm that utilizes the concepts of functional programming and time-varying data types to create event-driven applications. In this paradigm, data types in which values can change over time are primitives and can be applied to functions. These values are composable and can be combined with functions to create values that react to changes in values from multiple sources. Events can be modeled as values that change in discrete time steps. Computation can be encoded as values that produce events, with combination operators, it enables us to write concurrent event-driven programs by combining the concurrent computation as events. Combined with the denotational approach of functional programming, we can write programs in a concise manner. The style of event-driven programming has been widely adopted for developing graphical user interface applications, since they need to process events concurrently to stay responsive. This makes FRP a fitting approach for managing complex state and handling of events concurrently. In recent years, real-time systems such as IoT (internet of things) applications have become an important field of computation. Applying FRP to real-time systems is still an active area of research.For IoT applications, they are commonly tasked to perform data capturing in real time and transmit them to other devices. They need to exchange data with other applications over the internet and respond in a timely manner. The data needs to be processed, for simple analysis or more computation intensive work such as machine learning. Designing applications that perform these tasks and remain efficient and responsive can be challenging. In this thesis, we demonstrate that FRP is a suitable approach for real-time applications. These applications require soft real-time requirements, where systems can tolerate tasks that fail to meet the deadline and the results of these tasks might still be useful.First, we design the concurrency abstractions needed for supporting asynchronous computation and use it as the basis for building the FRP abstraction. Our implementation is in Haskell, a functional programming language with a rich type system that allows us to model abstractions with ease. The concurrency abstraction is based on some of the ideas from the Haskell solution for asynchronous computation, which elegantly supports cancelation in a composable way. Based on the Haskell implementation, we extend our design with operators that are more suitable for building web applications. We translate our implementation to JavaScript as it is more commonly used for web application development, and implementing the RxJS interface. RxJS is a popular JavaScript library for reactive programming in web applications. By implementing the RxJS interface, we argue that our programming model implemented in Haskell is also applicable in mainstream languages such as JavaScript

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

Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

Federated Embedded Systems – a review of the literature in related fields

This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways