The Internet-of-Things (IoT) envisages a future in which digital and physical things or objects (e.g., smartphones, TVs, cars) can be connected by means of suitable information and communication technologies, to enable a range of applications and services. The IoT's characteristics, including an ultra largescale network of things, device and network level heterogeneity, and the large number of events generated spontaneously by these things, will make development of the diverse applications and services a very challenging task. In general, middleware can ease the development process by integrating heterogeneous computing and communications devices, and supporting interoperability within the diverse applications and services. Recently, there have been a number of proposals for IoT middleware. These proposals mostly addressed Wireless Sensor Networks (WSNs), a key component of IoT, but do not consider Radio-Frequency IDentification (RFID), Machine to Machine (M2M) communications, and Supervisory Control and Data Acquisition (SCADA), other three core elements in the IoT vision. Taking a holistic view, in this article, we outline a set of requirements for IoT middleware, and present a comprehensive review of the existing middleware solutions against those requirements. In addition, open research issues, challenges and future research directions are highlighted.

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The proliferation of Internet of Things (IoT) and the success of resource-rich cloud services have pushed the data processing horizon towards the edge of the network. This has the potential to address bandwidth costs, and latency, availability and data privacy concerns. Serverless computing, a cloud computing model for stateless and event-driven applications, promises to further improve Quality of Service (QoS) by eliminating the burden of always-on infrastructure through ephemeral containers. Open source serverless frameworks have been introduced to avoid the vendor lock-in and computation restrictions of public cloud platforms and to bring the power of serverless computing to onpremises deployments. In an IoT environment, these frameworks can leverage the computational capabilities of devices in the local network to further improve QoS of applications delivered to the user. However, these frameworks have not been evaluated in a resource-constrained, edge computing environment. In this work we evaluate four open source serverless frameworks, namely, Kubeless, Apache OpenWhisk, OpenFaaS, Knative. Each framework is installed on a bare-metal, single master, Kubernetes cluster. We use the JMeter framework to evaluate the response time, throughput and success rate of functions deployed using these frameworks under different workloads. The evaluation results are presented and open research opportunities are discussed.

This paper proposes a new two-stage machine learning approach for bridge damage detection using the responses measured on a passing vehicle. In the first stage, an artificial neural network (ANN) is trained using the vehicle responses measured from multiple passes (training data set) over a healthy bridge. The vehicle acceleration or Discrete Fourier Transform (DFT) spectrum of the acceleration is used. The vehicle response is predicted from its speed for multiple passes (monitoring data set) over the bridge. Root-mean-square error is used to calculate the prediction error, which indicates the differences between the predicted and measured responses for each passage. In the second stage of the proposed method, a damage indicator is defined using a Gaussian process that detects the changes in the distribution of the prediction errors. It is suggested that if the bridge condition is healthy, the distribution of the prediction errors will remain low. A recognizable change in the distribution might indicate a damage in the bridge. The performance of the proposed approach was evaluated using numerical case studies of vehicle–bridge interaction. It was demonstrated that the approach could successfully detect the damage in the presence of road roughness profile and measurement noise, even for low damage levels.

The water distribution network (WDN) sectorisation problem is characterised by structural and hydraulic requirements that make existing graph partitioning techniques inadequate to find a good solution. Specifically, sector isolation and direct access to at least one source for each sector are not addressed. This study proposes a method to address structural requirements of water network sectorisation with minimum negative impact on the hydraulic requirements. This paper first elaborates the sectorisation problem and discusses the requirements of water network sectorisation. Then, it proposes a novel method, called WDN-PARTITION, which applies a new heuristic structural graph partitioning algorithm, combined with a many-objective optimisation procedure, to find near-optimal arrangements of nodes into sectors. The criteria of optimisation and their priorities can be specified for each case. The outcome of the method is a set of non-dominated sectorisation solutions, ranked lexicographically based on their values for the chosen criteria and their priorities, from which the final decision can be made by the domain experts. WDN-PARTITION has been implemented and integrated with a hydraulic network simulator. The simulation-based evaluation results demonstrate that WDN-PARTITION generally achieves its design objectives to partition a water network into isolated sectors with a minimal negative impact on the hydraulic performance criteria of the network.

For aspect-oriented software development (AOSD) to live up to being a software engineering method, there must be support for the separation of crosscutting concerns across the development lifecycle. Part of this support is traceability from one lifecycle phase to another.This paper investigates the traceability between one particular AOSD design-level language, Theme/UML, and one particular AOSD implementation-level language, AspectJ. This provides for a means to assess these languages and their incompatibilities, with a view towards eventually developing a standard design language for a broad range of AOSD approaches.

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