Microservices architectures are a departure from traditional Service Oriented Architecture (SOA). Influenced by Domain Driven Design (DDD), microservices architectures aim to help business analysts and enterprise architects develop scalable applications that embody flexibility for new functionalities as businesses develop, such as scenarios in the Internet of Things (IoT) domain. This article compares microservices architecture with SOA and identifies key characteristics that will assist application designers to select the most appropriate approach. Keywords-ServiceOriented Architecture (SOA), microservices, Domain Driven Design (DDD), Software Engineering I.

(2015) Approaching the Internet of things (IoT): a modelling, analysis and abstraction framework. Concurrency and Computation: Practice and Experience, 27 (8). pp. 1966-1984., DisclaimerThe University of Gloucestershire has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material.The University of Gloucestershire makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or any other warranty, express or implied in respect of any material deposited.The University of Gloucestershire makes no representation that the use of the materials will not infringe any patent, copyright, trademark or other property or proprietary rights.The University of Gloucestershire accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement. SUMMARYThe evolution of communication protocols, sensory hardware, mobile and pervasive devices, alongside social and cyber-physical networks, has made the Internet of things (IoT) an interesting concept with inherent complexities as it is realised. Such complexities range from addressing mechanisms to information management and from communication protocols to presentation and interaction within the IoT. Although existing Internet and communication models can be extended to provide the basis for realising IoT, they may not be sufficiently capable to handle the new paradigms that IoT introduces, such as social communities, smart spaces, privacy and personalisation of devices and information, modelling and reasoning. With interaction models in IoT moving from the orthodox service consumption model, towards an interactive conversational model, nature-inspired computational models appear to be candidate representations. Specifically, this research contests that the reactive and interactive nature of IoT makes chemical reaction-inspired approaches particularly well suited to such requirements. This paper presents a chemical reaction-inspired computational model using the concepts of graphs and reflection, which attempts to address the complexities associated with the visualisation, modelling, interaction, analysis and abstraction of information in the IoT.

In self-hosted environments it was feared that business intelligence (BI) will eventually face a resource crunch situation due to the never ending expansion of data warehouses and the online analytical processing (OLAP) demands on the underlying networking. Cloud computing has instigated a new hope for future prospects of BI. However, how will BI be implemented on Cloud and how will the traffic and demand profile look like? This research attempts to answer these key questions in regards to taking BI to the Cloud. The Cloud hosting of BI has been demonstrated with the help of a simulation on OPNET comprising a Cloud model with multiple OLAP application servers applying parallel query loads on an array of servers hosting relational databases. The simulation results reflected that extensible parallel processing of database servers on the Cloud can efficiently process OLAP application demands on Cloud computing

Approaches to the provision of data analytics for businesses offer methods to analyse and model data, enabling informed decision making to improve business performance and profitability. Typically, analytics processing is an intensive task and the demand for business insight, on-demand, means that organisations make use of elastic cloud provisioned resources to host such services. However, within the shared domains of multi-tenant cloud computing, business data and models are exposed to greater security threats and compromised privacy, since an unauthorised user may be able to gain access to highly sensitive, consolidated business-critical information. Business analytics processes are often composed from orchestrated, collaborating services, which are consumed by users from multiple cloud systems (in different security realms), which need to be engaged dynamically at runtime. If heterogeneous cloud systems located in different security realms do not have direct authentication relationships, then it is a considerable technical challenge to enable secure collaboration. In order to address this security challenge, a new authentication framework is required to establish trust amongst business analytics service instances and users by distributing a common session secret to all participants of a session. We address this challenge by designing and implementing a secure multiparty authentication framework for dynamic interaction, for the scenario where members of different security realms express a need to access orchestrated services. This novel framework exploits the relationship of trust between session members in different security realms, to enable a user to obtain security credentials that access cloud resources in a remote realm. The mechanism assists cloud session users to authenticate their session membership, thereby improving the performance of authentication processes within multiparty sessions. We see applicability of this framework beyond multiple cloud infrastructure, to that of any scenario where multiple security realms has the potential to exist, such as the emerging Internet of Things (IoT).

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