An emerging trend in Internet of Things (IoT) applications is to move the computation (cyber) closer to the source of the data (physical). This paradigm is often referred to as edge computing . If edge resources are pooled together, they can be used as decentralized shared resources for IoT applications, providing increased capacity to scale up computations and minimize end-to-end latency. Managing applications on these edge resources is hard, however, due to their remote, distributed, and (possibly) dynamic nature, which necessitates autonomous management mechanisms that facilitate application deployment, failure avoidance, failure management, and incremental updates. To address these needs, we present CHARIOT, which is orchestration middleware capable of autonomously managing IoT systems consisting of edge resources and applications. CHARIOT implements a three-layer architecture. The topmost layer comprises a system description language, the middle layer comprises a persistent data storage layer and the corresponding schema to store system information, and the bottom layer comprises a management engine that uses information stored persistently to formulate constraints that encode system properties and requirements, thereby enabling the use of satisfiability modulo theory solvers to compute optimal system (re)configurations dynamically at runtime. This article describes the structure and functionality of CHARIOT and evaluates its efficacy as the basis for a smart parking system case study that uses sensors to manage parking spaces.

Cyber-physical systems (CPS) are systems with a tight integration between the computational (also referred to as software or cyber) and physical (hardware) components. While the reliability evaluation of physical systems is well-understood and well-studied, reliability evaluation of CPS is difficult because software systems do not degrade and follow a well-defined failure model like physical systems. In this paper, we propose a framework for formulating the CPS reliability evaluation as a dependence problem derived from the software component dependences, functional requirements and physical system dependences. We also consider sensor failures, and propose a method for estimating software failures in terms of associated hardware and software inputs. This framework is codified in a domain-specific modeling language, where every system-level function is mapped to a set of required components using functional decomposition and function-component association; this provides details about operational constraints and dependences. We also illustrate how the encoded information can be used to make reconfiguration decisions at runtime. The proposed methodology is demonstrated using a smart parking system, which provides localization and guidance for parking within indoor environments.

Wider adoption, availability and ubiquity of wireless networking technologies, integrated sensors, actuators, and edge computing devices is facilitating a paradigm shift by allowing us to transition from traditional statically configured vertical silos of Cyber-Physical Systems (CPS) to next generation CPS that are more open, dynamic and extensible. Fractionated spacecraft, smart cities computing architectures, Unmanned Aerial Vehicle (UAV) clusters are all examples of extensible CPS wherein extensibility is implied by the dynamic aggregation of physical resources, affect of physical dynamics on availability of computing resources, and various multi-domain applications hosted on these systems. However, realization of extensible CPS requires resolving design-time and runtime challenges emanating from properties specific to these systems. In this paper, we first describe different properties of extensible CPS - dynamism, extensibility, remote deployment, security, heterogeneity and resilience. Then we identify different design-time challenges stemming from heterogeneity and resilience requirements. We particularly focus on software heterogeneity arising from availability of various communication middleware. We then present appropriate solutions in the context of a novel domain specific language and describe how this language and its features have evolved from our past work.

Component-based programming models are well-suited to the design of large-scale, distributed applications because of the ease with which distributed functionality can be developed, deployed, and validated using the models' compositional properties. Existing component models supported by standardized technologies, such as the OMG's CORBA Component Model (CCM), however, incur a number of limitations in the context of cyber physical systems (CPS) that operate in highly dynamic, resource-constrained, and uncertain environments, such as space environments, yet require multiple quality of service (QoS) assurances, such as timeliness, reliability, and security. To overcome these limitations, this paper presents the design of a novel component model called F6COM that is developed for applications operating in the context of a cluster of fractionated spacecraft. Although F6COM leverages the compositional capabilities and port abstractions of existing component models, it provides several new features. Specifically, F6COM abstracts the component operations as tasks, which are scheduled sequentially based on a specified scheduling policy. The infrastructure ensures that at any time at most one task of a component can be active - eliminating race conditions and deadlocks without requiring complicated and error-prone synchronization logic to be written by the component developer. These tasks can be initiated due to (a) interactions with other components, (b) expiration of timers, both sporadic and periodic, and (c) interactions with input/output devices. Interactions with other components are facilitated by ports. To ensure secure information flows, every port of an F6COM component is associated with a security label such that all interactions are executed within a security context. Thus, all component interactions can be subjected to Mandatory Access Control checks by a Trusted Computing Base that facilitates the interactions. Finally, F6COM provides capabilities to monitor task execution deadlines and to configure component-specific fault mitigation actions.