Middleware Solutions Research Articles

A dynamic skyline technique for a context-aware selection of the best sensors in an IoT architecture

The integration of the Internet of Things (IoT) paradigm into web services and cloud computing allows us to handle thousands of sensors and their data. In this regard, sensing as a service model has recently emerged and the data generated by these sensors can be reused by different users and applications within IoT middleware solutions. With the huge number of sensors available in the IoT environment, the crucial challenge is how to efficiently search and select the best sensors depending on the users’ requirements. This paper aims to exploit the power of a dynamic skyline operator in the field of multi-criteria decision making, to reduce the search space for the purpose of improving the efficiency of context-awareness and selecting the best sensors following the users’ request. The architecture adopted in this proposition is composed by several gateways distributed in the network and connected with a server, where each gateway must respond to user requests locally. Hereafter, the server will aggregate the results of all gateways and give the final answer. The experimentation shows the efficiency of our method in comparison to existing ones.

Legal Protection of Indigenous Knowledge Systems through IKS for Large-Scale Enterprises

The formation of the Association of Southeast Asian Nations (ASEAN) Economic Community (AEC) in 2015 has created new challenges for small and medium-sized businesses (SMEs) in Malaysia. These challenges are in addition to the consequences of globalization that have already been experienced by low-cost nations such as India and China. It is critical for small and medium-sized firms (SMEs) to keep their competitive edge because they are the backbone of the Malaysian economy. A business can increase its competitiveness by implementing the kaizen idea of continuous improvement. Challenges and opportunities for small and medium-sized firms to adopt kaizen are explored in this article. Several factors were found to play a role in the effective execution of Kaizen. Among these were an articulated business plan, effective management of company information, employee agency, and two-way dialogue between upper and lower-level management. Another important factor was having a Kaizen champion on staff. However, environmental monitoring systems still do not have enough evidence to justify the semantic description of these many data sources. The compatibility issues can only be resolved with a tailored semantic middleware solution. Detailed herein is the design of a cross-domain middleware system capable of semantic integration and inference generation from a variety of data sources. Improved environmental monitoring systems are possible thanks to semantic technology's application to the prediction and forecasting of complicated environmental phenomena.

A middleware solution for integrating and exploring IoT and HPC capabilities

SummaryEven with the considerable advances in the development of middleware solutions, there is still a substantial gap in Internet of Things (IoT) and high‐performance computing (HPC) integration. It is not possible to expose services such as processing, storage, sensing, security, context awareness, and actuating in a unified manner with the existing middleware solutions. The consequence is the utilization of several solutions with their particularities, thus requiring different skills. Besides that, the users have to solve the integration and all heterogeneity issues. To reduce the gap between IoT and HPC technologies, we present the JavaCá&Lá (JCL), a middleware used to help the implementation of distributed user‐applications classified as IoT‐HPC. This ubiquity is possible because JCL incorporates (1) a single application programming interface to program different device categories; (2) the support for different programming models; (3) the interoperability of sensing, processing, storage, and actuating services; (4) the integration with MQTT technology; and (5) security, context awareness, and actions services introduced through JCL application programming interface. Experimental evaluations demonstrated that JCL scales when doing the IoT‐HPC services. Additionally, we identify that customized JCL deployments become an alternative when Java‐Android and vice‐versa code conversion is necessary. The MQTT brokers usually are faster than JCL HashMap sensing storage, but they do not perform distributed, so they cannot handle a huge amount of sensing data. Finally, a short example for monitoring moving objects exemplifies JCL facilities for IoT‐HPC development.

An approach for the secure management of hybrid cloud–edge environments

The Cloud-of-Things (CoT) paradigm is a challenging approach to manage IoT applications exploiting Cloud resources and services. In order to avoid latency in Cloud–IoT communications, the management of time-sensitive services has to be moved to the edge of the CoT. To this aim, a secure Cloud-to-Edge environment for seamless management of IoT applications is necessary. The realization of a performing and secure Cloud-to-Edge middleware solution is a very strategic goal for future business CoT services. Thus, it needs to be deeply investigated, as highlighted by the Cloud Security Alliance (CSA). A valuable approach to develop an efficient Cloud-to-Edge system is based on an instant-message communication solution. In current Cloud environments, a Message Oriented Middleware (MOM) based on an Instant Message Protocol (IMP) provides good performance, but overlook security requirements. In this paper, we aim at overcoming such a gap following the CSA guidelines. In particular, we discuss the involved issues for improving such a kind of Cloud-to-Edge system in order to achieve data confidentiality, integrity, authenticity and non-repudiation. Moreover, we analyze a real case of study considering a MOM architectural model. Experimental results performed on a real testbed show how the introduced secure capabilities do not affect the overall performances of the whole middleware.

Performance evaluation of IoT middleware

Connected objects in a billion scale are expected in the Internet of Things (IoT). These objects (“things”) are interacting autonomously, with minimal human intervention and connected to the Internet. Most of these objects are constrained in terms of resources, meaning that their intelligence is delegated to a smarter player, a software, identified as middleware. It is present in most IoT scenarios because it solves interoperability problems, allowing previously incompatible devices to communicate, while also integrates and makes decisions based on collected data. This paper presents a performance evaluation study of open-source middleware solutions, including a proprietary solution developed at Inatel for the Inatel Smart Campus. Performance metrics, both qualitative and quantitative to evaluate middleware solutions objectively are also proposed. The results are analyzed and it is concluded that the proposed metrics are well adjusted for this type of platforms and can play a key role when choosing the best middleware solution to deploy in a given IoT solution. Sitewhere is the middleware platform that obtained better performance in the study.

Middleware for internet of things: an evaluation in a small-scale IoT environment

The internet of things (IoT) envisages an ultralarge-scale network of things, which will offer services to a large number of applications in numerous domains and environments. A middleware can ease application development by providing the necessary functional components for service registration, discovery and composition. Recently, there have been a large number of proposals for IoT middleware solutions, and a few recent studies have surveyed and qualitatively evaluated these IoT middleware proposals against a variety of functional features. This paper is an extension of these studies with an evaluation of four representative middlewares in a small-scale scenario to provide a more in-depth perspective of the state of the art with reference to the scale and heterogeneity of dynamic IoT environments. The results show a number of issues. Service registration, discovery and composition components still require human intervention. With such a large number of available services, these components need to be automated to enable fast deployment and adaptation of IoT applications. The scalability evaluation of new proposals should follow a holistic approach, as opposed to considering only individual components. Finally, support for user’s non-functional requirements is limited to best-effort QoS.

Systematic performance evaluation using component-in-the-loop approach

Timeliness and throughput critical applications require a framework offering predictable temporal characteristics. The best practice for estimating a prediction of the system dynamics relies on benchmarking. Each novel middleware solution needs such an evaluation as part of the development process to assure an appropriate throughput in the future use. General purpose blockchain frameworks are viable replacements for many current systems in several sectors by providing a fully distributed, secure, and non-repudiable ledger as a service. Blockchain technologies target domains with a large number of interactions, thus demanding strict performance guarantees. Engineering for performance targets in a trustworthy manner requires performance models. However, performance characteristics of blockchain systems are highly unexplored due to the novelty of the technology. This paper proposes a general-purpose, systematic methodology for the performance analysis of complex systems, aided by a component-in-the-loop approach. The Linux foundation-hosted hyperledger fabric serves as a case study for the presented methodology.

An intelligent agent system for managing heterogeneous sensors in dispersed and disparate wireless sensor network

Wireless sensor networks (WSNs) employ middleware solutions to coordinate their sensors and provide web services for managing data. Adding/configuring a new or existing sensor requires modification to the middleware and web service. To integrate hundreds of sensors with different capabilities, a system needs to support all the encodings, models and services for registering, tasking and querying sensors. We present an intelligent agent, which provides automatic semantic-based registration/configuration in a large-scale sensor observation system. The agent can react to any changes internally/externally made (i.e., adding a new sensor or sending a task request to sensors/support systems). The agent makes a 'smart' decision on which system function to use by integrating a semantic representation of sensor network data including middleware and web service specifications and applying logical rules to the knowledge-base. The agent's operation is demonstrated using two real-world systems represented in RDF using a domain ontology that extends the W3C SSN-XG ontology.

Sensor discovery in ambient IoT ecosystems

Heterogeneity represents a singular barrier to the cross-domain adoption of sensor networks, limiting the take-up of Ambient Intelligence. Historically, the preferred approach has been to adopt a middleware solution to mitigate the problems associated with heterogeneity. Normally, the sensor discovery process is tightly coupled to the middleware platform, resulting in a unique implementation for each platform. Such an approach is unsustainable given the speed of developments in sensing technologies and the increased deployment of networks of sensors and Internet-of-Things (IoT) devices. An alternative approach is to decouple the sensor discovery process from the middleware and to regard it a discrete service that could be harnessed by different middleware platforms and external IoT services. This paper presents the design and implementation of a generic discovery service framework—POrtable Discovery Services (PODS). PODS utilises existing middleware abstractions to support heterogeneity in so far as such abstractions relate to the discovery process. An evaluation of the framework is presented using an exemplar middleware platform.

A Middleware Solution for Wireless IoT Applications in Sparse Smart Cities.

The spread of off-the-shelf mobile devices equipped with multiple wireless interfaces together with sophisticated sensors is paving the way to novel wireless Internet of Things (IoT) environments, characterized by multi-hop infrastructure-less wireless networks where devices carried by users act as sensors/actuators as well as network nodes. In particular, the paper presents Real Ad-hoc Multi-hop Peer-to peer-Wireless IoT Application (RAMP-WIA), a novel solution that facilitates the development, deployment, and management of applications in sparse Smart City environments, characterized by users willing to collaborate by allowing new applications to be deployed on their smartphones to remotely monitor and control fixed/mobile devices. RAMP-WIA allows users to dynamically configure single-hop wireless links, to manage opportunistically multi-hop packet dispatching considering that the network topology (together with the availability of sensors and actuators) may abruptly change, to actuate reliably sensor nodes specifically considering that only part of them could be actually reachable in a timely manner, and to upgrade dynamically the nodes through over-the-air distribution of new software components. The paper also reports the performance of RAMP-WIA on simple but realistic cases of small-scale deployment scenarios with off-the-shelf Android smartphones and Raspberry Pi devices; these results show not only the feasibility and soundness of the proposed approach, but also the efficiency of the middleware implemented when deployed on real testbeds.

Information theoretic‐based detection and removal of slander and/or false‐praise attacks for robust trust management with Dempster‐Shafer combination of linguistic fuzzy terms

SummaryCritical systems are progressively abandoning the traditional isolated and closed architectures, and adopting more federated solutions, in order to deal with orchestrated decision making within large‐scale infrastructures. Such an increasing connectivity and the possibility of dynamically integrate constituents in a seamless manner by means of a decoupling middleware solution are causing the flouring of novel and previously unseen security threats, such as internal attacks conducted by camouflaged and/or compromised federated systems. Trust management is the most efficient way for dealing with such attacks, so that each constituent computes a trust degree of the other interacting ones based on the direct experiences and of collected reputation scores. An adversary may negatively affect the overall process with false reputations, which must not be considered when estimating a trust degree. Our work combines a multi‐criteria linguistic fuzzy term formulation of the trust degree with the concept of entropy for measuring the divergence of certain scores from the other ones and to avoid to consider them during reputation aggregation. A set of experiments have been conducted in order to measure the quality and effectiveness of the presented approach.

MIDDLEWARE OF MULTI CLOUD COMPUTING SYSTEM : AN ANALYSIS AND REVIEW

Heterogeneity of service is main characteristic of Multi Cloud Computing Systems. Portability and interoperability are the main obstacles to provide heterogeneous services to users. Hence few middleware solutions are provided to support design, development and implementation of services in multi cloud computing systems. This paper proposes an overview of middleware of multi cloud computing Systems, an in depth analysis of various middleware of multi cloud computing system and ontology for accessing heterogeneous services in multi cloud computing.

An Optimized, Data Distribution Service-Based Solution for Reliable Data Exchange Among Autonomous Underwater Vehicles.

Major challenges are presented when managing a large number of heterogeneous vehicles that have to communicate underwater in order to complete a global mission in a cooperative manner. In this kind of application domain, sending data through the environment presents issues that surpass the ones found in other overwater, distributed, cyber-physical systems (i.e., low bandwidth, unreliable transport medium, data representation and hardware high heterogeneity). This manuscript presents a Publish/Subscribe-based semantic middleware solution for unreliable scenarios and vehicle interoperability across cooperative and heterogeneous autonomous vehicles. The middleware relies on different iterations of the Data Distribution Service (DDS) software standard and their combined work between autonomous maritime vehicles and a control entity. It also uses several components with different functionalities deemed as mandatory for a semantic middleware architecture oriented to maritime operations (device and service registration, context awareness, access to the application layer) where other technologies are also interweaved with middleware (wireless communications, acoustic networks). Implementation details and test results, both in a laboratory and a deployment scenario, have been provided as a way to assess the quality of the system and its satisfactory performance.

A resource-oriented middleware in a prototype cyber-physical manufacturing system

The interconnection among heterogeneous sensors and data acquisition equipment in cyber-physical systems have profound significance in achieving adaptability, flexibility, and transparency. Various middlewares have been developed in cyber-physical systems to collect, aggregate, correlate, and translate system monitoring data. Existing middleware solutions are normally highly customized, which face several challenges due to the highly dynamic and harsh production environments. The data generated by sensors can only be shared by specific applications, which prevents the reusability of sensors. Moreover, the lack of uniform access to sensors causes high cost and low efficiency in application development. To address these issues, a resource-oriented middleware architecture called ROMiddleware was proposed, and three key enabling technologies including heterogeneous sensor modeling and grouping, open application programming interfaces development, and token-based access right control mechanism have been developed. Under the guidance of the key enabling technologies, a prototype of ROMiddleware was implemented and its performance was evaluated. Finally, two applications were developed to stress the significance of ROMiddleware. The results show that ROMiddleware can meet the requirements of data acquisition in cyber-physical systems.

Automatic run-time versioning for BPEL processes

We describe a middleware solution for automatic run-time process versioning in Business Process Execution Language (BPEL) and then analyse its impact in terms of scalability and performance. Business processes change in response to business needs, but the deployment of new versions to a BPEL engine must ensure that running instances are not disrupted and can conclude following their original workflows. Our solution is implemented as a standalone component that manages versioning transparently to the process editor, the orchestration engine, the web services used by the process, and the end-user. We have tested it for almost 1 year in the production environment of a telecommunications company, without significant overhead in terms of process invocation time.

Flexible and timely on-line integration of medical services using iLand middleware

Modern medical systems are intensive in the use of distribution technology in medical services. Communication among professionals and patients is enabled to exchange patient information, and for on-line monitoring of health conditions. A miriad of specialized middleware solutions that have appeared in this domain, typically focus on providing more and more patient-data processing services over basic communication backbones (e.g., from pure socket communication to more sophisticated interaction models). Paradigms such as service oriented architectures and decoupled communication middleware support the development of emerging medical systems based on the composition of existing (posibly remote) services into a new application. This adjusts to the phylosophy of systems of systems (SoS) development. In a cyber-physical medical domain, service based applications require support for this composition in a way that a new application is created (or simply modified) in a timely fashion. iLand middleware supports this phylosophy, enabling both off-line and run-time reconfiguration of distributed service based applications. It provides timely operation, controlled communication delays, and a decoupled interaction model for stateless services. iLand has been used in medical applications for remote patient monitoring and in surveillance domains for remote real-time video transmission. This paper presents the systems that iLand has enabled in the medical domain, mainly based on remote patient monitoring. These iLand-based systems have shown to be flexible and capable of undergoing timely service reconfigurations.

Distributed strategic learning and game theoretic formulation of network embedded coding

Nowadays, there is a growing demand of middleware solutions for reliable event notification over the Internet due to several key industrial projects aiming at integrating existing legacy systems and enhancing their functionalities. Reliable event notification is mainly realized by means of retransmissions, with the consequent worsening of the performance and traffic load. Traditionally, the opposite approach of spatial redundancy is not used due to the tunability, scalability and flexibility issues of its implementation schemes. In this paper, we propose a game theoretic formulation of Forward Error Correction (one of the mean schemes to introduce spatial redundancy), in order to resolve these mentioned issues. Moreover, we introduce distributed strategic learning for the optimal formulation of the payoff functions in the game, and for the effective adaptivity in response to the possible variations in the experienced loss patterns. We prove the quality of this solution by using a series of simulations run on OMNET++.

Development of Middleware Applied to Microgrids by Means of an Open Source Enterprise Service Bus

The success of the smart grid relies heavily on the integration of Distributed Energy Resources (DERs) and interoperability among the hardware elements that are present as part of either the smart grid itself or in a smaller size deployment, such as a microgrid. Therefore, establishing an accurate design for software architectures that guarantee interoperability and are able to abstract hardware heterogeneity in this application domain, along with a clearly defined procedure on how to implement and test a solution like this, becomes a desirable objective. This paper describes the requirements needed to design a secure, decentralized and semantic middleware architecture for microgrids and the procedures used to develop it, so that the mandatory software components that have to be encased by the solution, as well as the steps that should be followed to make it happen, become clear for any designer, software architect or programmer that has to tackle similar challenges. In order to demonstrate the usability of the ideas put forward here, two successful pilots where middleware solutions were created according to these principles have been described.

An Information-Centric Platform for Social- and Location-Aware IoT Applications in Smart Cities

Recent advances in Smart City infrastructures and the Internet of Things represent a significant opportunity to improve people’s quality of life. Corresponding research often focuses on Cloud-centric network architectures where sensor devices transfer collected data to the Cloud for processing. However, the formidable traffic generated by countless IoT devices and the need for low-latency services raise the need to move away from centralized architectures and bring the computation closer to the data sources. To this end, this paper discusses SPF, a middleware solution that supports IoT application development, deployment, and management. SPF runs IoT services on capable devices located at the network edge and proposes an information-centric programming model that takes advantage of decentralized computation resources located in the proximity of application users and data sources. SPF also adopts Value-of-Information based methods to prioritize the transmission of essential information.

A Middleware Architecture for RFID-enabled traceability of air baggage

1980 marked the start of a boom in radiofrequency identification (RFID) technology, initially associated with a growing need for traceability. In view of the technological progress and lower costs, RFID’s area of application became much broader and, today, multiple business sectors take advantage of this technology. However, in order to achieve the maximum benefits of RFID technology, the data collected should be delivered in the best conditions to the whole applications that have need of its exploitation. For that, a dedicated middleware solution is required to ensure the collection of RFID data and their integration in information systems. The issues and key points of this integration as the description of the RFID technology will be summarized in the present paper, with a new middleware architecture. We focus mainly on components and the design of our middleware MedRFID, solution developed in our Lab, and which integrates mobility and provides extensibility, scalability, abstraction, ease of deployment and compatibility with IATA standards and EPCglobal standards. Moreover, we have developed an application (FindLuggage) allowing a real time tracking of luggage in the airport, based on the proposed middleware MedRFID.