Constructing distributed time-critical applications using cognitive enabled services

Abstract

Time-critical analytics applications are increasingly making use of distributed service interfaces (e.g., micro-services) that support the rapid construction of new applications by dynamically linking the services into different workflow configurations. Traditional service-based applications, in fixed networks, are typically constructed and managed centrally and assume stable service endpoints and adequate network connectivity. Constructing and maintaining such applications in dynamic heterogeneous wireless networked environments, where limited bandwidth and transient connectivity are commonplace, presents significant challenges and makes centralized application construction and management impossible. In this paper we present an architecture which is capable of providing an adaptable and resilient method for on-demand decentralized construction and management of complex timecritical applications in such environments. The approach uses a Vector Symbolic Architecture (VSA) to compactly represent an application as a single semantic vector that encodes the service interfaces, workflow, and the timecritical constraints required. By extending existing services interfaces, with a simple cognitive layer that can interpret and exchange the vectors, we show how the required services can be dynamically discovered and interconnected in a completely decentralized manner. We demonstrate the viability of this approach by using a VSA to encode various time-critical data analytics workflows. We show that these vectors can be used to dynamically construct and run applications using services that are distributed across an emulated Mobile Ad-Hoc Wireless Network (MANET). Scalability is demonstrated via an empirical evaluation.

Editorial for FGCS Special issue on “Time-critical Applications on Software-defined Infrastructures”

“…The proposed solution can satisfy the requirements of time-sensitive networking for industrial automation with switch delay and achieves a jitter between 12.2μs and 0.12μs. [14] to tackle the software engineering challenges in constructing distributed time-critical applications. A novel cognitive component uses a symbolic vector architecture to semantically represent service descriptions, workflows, and time-critical QoS and QoE constraints.…”

Enabling Discoverable Trusted Services for Highly Dynamic Decentralized Workflows

“…As such, a mechanism is needed that can locate and orchestrate the required workflow in the face of these challenges, without central control since it in not possible to rely on centralised registries, or even to know the IP location of objects and devices as they come in and out of service. As described in [1], [2], [3], the VSA architecture can be used for peer-to-peer (P2P) discovery of appropriate devices and functional micro-services without service and device registries because the VSA representation is able to act as both the object description and the address of the object.…”

“…Our approach for creating semantically rich representation of services and workflows is to represent them as high level semantic concept vectors that are themselves constructed from semantic vectors representing their sub features in a recursive manner using vector binding and superposition operations as described in [3], [2]. Reviewing that X r represents a role vector and Y v a value vector, role vectors can be bound to filler vectors using the binding operation X r .…”

“…As a result, dynamic workflow configuration needs to be able to provide rapid and autonomous discovery and configuration of suitable resources from a plethora of available devices and services, based on factors such as capabilities and quality of service, and augmented by networks of trust. The author's previous work has shown that decentralized workflow mechanisms, such as those based on Vector Symbolic Architectures (VSA), can be used to facilitate efficient service discovery and workflow formulation in decentralized collaborative environments [1], [2], [3], without requiring central control [4]. Such decentralized mechanisms are well suited to the low latency, high capacity, and high bandwidth connectivity afforded to edge computing resources as part of 5G networks, and the business and research ecosystems that they will support.…”

Self-assemble-featured Internet of Things

“…On the other side, dynamic management in timecritical IoT middleware is very compositional and expressive, but the support for an end to end QoS in the specific context of service-oriented components is weak. Time-critical IoT middlewares provide the QoS links but do not take into account the QoS nodes [7,8,9,10]. To complete the modeling of the IoT ecosystem, we refer to the node/links model allowing us to have an architectural abstraction for dynamicity and a flexible engineering for a personalized user session.…”