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.

There are a large number of workflow systems designed to work in various scientific domains, including support for the Internet of Things (IoT). One such workflow system is Node-RED, which is designed to bring workflow-based programming to IoT. However, the majority of scientific workflow systems, and specifically systems like Node-RED, are designed to operate in a fixed networked environment, which rely on a central point of coordination in order to manage the workflow. The main focus of the work described in this paper is to investigate means whereby we can migrate Node-RED workflows into a decentralized execution environment, so that such workflows can run on Edge networks, where nodes are extremely transient in nature. In this work, we demonstrate the feasibility of such an approach by showing how we can migrate a Node-RED based traffic congestion workflow into a decentralized environment. The traffic congestion algorithm is implemented as a set of Web services within Node-RED and we have architected and implemented a system that proxies the centralized Node-RED services using cognitively-aware wrapper services, designed to operate in a decentralized environment. Our cognitive services use a Vector Symbolic Architecture to semantically represent service descriptions and workflows in a way that can be unraveled on the fly without any central point of control. The VSA-based system is capable of parsing Node-RED workflows and migrating them to a decentralized environment for execution; providing a way to use Node-RED as a front-end graphical composition tool for decentralized workflows.

Future Multi-Domain Operations (MDO) will require the coordination of hundreds-even thousands-of devices and component services. This will demand the capability to rapidly discover the distributed devices/services and combine them into different workflow configurations, thereby creating the applications necessary to support changing mission needs. To meet these objectives, we envision a distributed Cognitive Computing System (CCS) that consists of humans and software that work together as a 'Distributed Federated Brain'. Motivated by neuromorphic processing models, we present an approach that uses hyperdimensional symbolic semantic vector representations of the services/devices and workflows. We show how these can be used to perform decentralized service/device discovery and workflow composition in the context of a dynamic communications re-planning scenario. In this paper, we describe how emerging analogue AI 'In Memory' and 'Near Memory' computing can be used to efficiently perform some of the required hyperdimensional vector computation (HDC). We present an evaluation of the performance of an energy-efficient phase change memory device (PCM) that can perform the required vector operations and discuss how such devices could be used in energy-critical 'edge of network' tactical MDO operations.

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A non-technical description is given of a new, powerful, low cost field system (Infra-red Active Determination of Insect Flight Trajectories or IRADIT) for detailed and automatic remote sensing studies of natural insect flight behaviour. The special requirements and difficulties of the detection problem are defined. A series of examples of field devices and techniques are presented to illustrate the key factors of the optical sensing and tracking of insects in flight. In the finally adopted IRADIT system, flying insects are differentially illuminated, under all natural light conditions, by an intense beam of pulsed near-infra-red radiation and detected using a shuttered image intensifier linked with a video camera operating at a rate of 50 frames per second. Immediate fully-automatic determination of the flight trajectories of several simultaneously detected insects was achieved, at this same high rate and in the presence of sky background photon noise, by processing the video signals with electronic circuits and a microcomputer. Flight trajectories are influenced by the local wind, whose vector must be subtracted to study insect flight behaviour. This was achieved by the use of a specially developed sensitive three-vector vane anemometer, providing digital data to the microcomputer at a minimum rate of 5 Hz. In tests of the prototype IRADIT-anemometer system in the field, insects with wing area of only 1-5 mm 2 and flying against the midday sky were readily tracked at ranges up to 15 m. A range of at least 100 m is expected for nocturnal moth tracking.

Numerous workflow systems span multiple scientific domains and environments, and for the Internet of Things (IoT), Node-RED offers an attractive Web based user interface to execute IoT service-based workflows. However, like most workflow systems, it coordinates the workflow centrally, and cannot run within more transient environments where nodes are mobile. To address this gap, we show how Node-RED workflows can be migrated into a decentralized execution environment for operation on mobile ad-hoc networks, and we demonstrate this by converting a Node-RED based traffic congestion detection workflow to operate in a decentralized environment. The approach uses a Vector Symbolic Architecture (VSA) to dynamically convert Node-Red applications into a compact semantic vector representation that encodes the service interfaces and the workflow in which they are embedded. 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 into the required workflow in a completely decentralized manner. The resulting system provides a convenient environment where the Node-RED front-end graphical composition tool can be used to orchestrate decentralized workflows. In this paper, we further extend this work by introducing a new dynamic VSA vector compression scheme that compresses vectors for on-the-wire communication, thereby reducing communication bandwidth while maintaining the semantic information content. This algorithm utilizes the holographic properties of the symbolic vectors to perform compression taking into consideration the number of combined vectors along with similarity bounds that determine conflict with other encoded vectors used in the same context. The resulting savings make this approach extremely efficient for discovery in service based decentralized workflows.

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Radar methods have been extended to measure the aerial density of small insects. Results obtained during an outbreak of the cereal aphid Metopolophium dirhodum (Walker) in south-eastern England were compared with simultaneous suction trap catches to study the sensitivity of trap effectiveness to windspeed. Two traps were studied: the Rothamsted Insect Survey trap (12-2-m) and a standard aerofoil trap. The Survey trap effectiveness is moderately sensitive to windspeed, decreasing exponentially by a factor of two for each 2-4 m/s (5 knots) of average windspeed. The two trap sensitivities did not differ significantly, but both results are very significantly different (P<0-001) from the published predictions, which were based upon a comparison of catches from suction traps and a combination of a rotary (whirligig) net and a tow net. These differences are discussed. The average catching rate is about 40% of that of an ideal trap. Seven-day catches could vary by a factor of 0-5-2-0 from average due to prolonged periods of extra strong or light winds. Systematic windspeed gradients can corrupt suction trap studies of insect dispersal in relation to vertical density profiles, diurnal flight patterns and geographical distribution. Absolute calibration of the aerofoil trap was achieved by using the remote-sensing IRADIT infra-red system to measure the aerial density of aphid-size insects near to the trap inlet in very light winds; the effectiveness was not statistically different from unity, and the Survey trap is expected to perform similarly. IntroductionThe Rothamsted Insect Survey (12-2-m) suction trap (Taylor & Palmer, 1972) has become a standard tool for monitoring the density of flying insects, particularly aphids. A network of traps, at present at 23 sites, has been managed by the Survey for 15 years in the United Kingdom, and in recent years similar traps have been operated throughout Europe (Taylor et ai, 1981). The Survey trap takes in air from a height of 12-2 m (40 ft) at the rate of approximately 0-8 m 3 /s, through a circular inlet pipe with a diameter of 0-254 m (10 in.) at a speed of about 16 m/s. Trapped insects are removed daily, the aphids identified and weekly bulletins distributed to the agricultural industry giving warnings of impending outbreaks (Woiwod et ai, 1984).The 'efficiency' of suction traps for quantifying the aerial density of passing insects has been assessed by Taylor (1962) by an indirect method. The insect catching rates of a variety of traps were measured relative to that of an aerofoil trap with an inlet diameter of