From Data to Actionable Knowledge: Big Data Challenges in the Web of Things [Guest Editors' Introduction

Traditional Complex Event systems (CEP) did not consider the computation requirements of continuous dynamic behavior such as differential equations. In addition, the event composition rules were predefined before the CEP engine began working. The rule defining task is error-prone and cumbersome. In this paper, therefore, a hybrid complex event service is proposed, which deals with not only discrete events but also continuous behavior computation based on IoT (Internet of Things) resource models. In order to satisfy the real-time constraints of processing IoT events, a divide-and-conquer principle is adopted, where we give a combination theorem such that different events can be processed on different IoT resources and then these processed results can be combined to derive complex events. Based on the formal IoT resources and event knowledge, we define interest goals to direct event composition without enumerating event relation to define event composition rules. We finally present event composition algorithms and evaluation to show our idea.

The Internet of Things (IoT) is a system that connects all physical devices to the web through switches, allowing them to exchange data. Web application development is advancing at a steady pace, and it is being used by a broad range of people in a variety of different fields and situations. To save human effort and make things easier, IoT often allows remote access to the existing system, which has been put up by different calculating institutions. Programed control of any gadget to get to the framework without human mediation is a unique IoT characteristic termed IoT. IoT, or the Internet of Things, refers to 'things' as a mixture of equipment components, programming information, and provided services. This device collects data from various devices from previous technological advances and exchanges it with other connected devices. IoT innovation can be portrayed as 'Web of Things', wherein this innovation is constructed dependent on the idea that all the ideal gadgets can be associated inside a particular system for sharing information and data with no manual intercession. The gadgets utilized for this can be isolated contingent to their capacity to send, get, and assemble information in the given system. IoT is obvious because of its remarkable properties that are, secure in nature, can be utilized on savvy gadgets, the capacity to interface with a system helps for the quicker network, etc. Thus IoT is a specialty innovation where heaps of work are going on and where the associations are attempting to computerize human exertion so the possibility of mistake will be negligible or zero. IoT will make things significantly simpler for people and associations with their machines to machine collaboration and network.

The Internet of Things (IoT) has become a paradigm shifter, connecting an enormous number of smart devices and facilitating seamless data exchange for a diverse array of applications. The availability and effective use of the IoT ecosystem's resources are key factors in determining how its practical applications will develop as they mature. The IoT resources and their practical application across several areas are thoroughly explored in this paper. The paper begins by classifying and describing the various sensor types, their applications in various fields, and IoT resources, highlighting their contributions to real-time data collection, processing, and transmission. It then goes on to demonstrate a wide range of real-world uses for these resources, such as smart cities, education, agriculture, business, healthcare, environment monitoring, transportation, and industrial automation. However, utilizing IoT resources effectively is not without difficulties. Critical difficulties such as resource allocation, scalability, security, interoperability, and privacy concerns are identified and discussed in the paper. Furthermore, the paper also highlights future directions and emerging trends in IoT resource management, including edge computing, cloud computing, human machine integration, and compatibility with other systems. These developments aim to increase the dependability of IoT applications in diverse settings and optimize resource allocation. This paper's conclusion highlights the crucial role that IoT resources play in advancing real-world applications across a variety of areas. Researchers, practitioners, policymakers, and other stakeholders may collaborate together to effectively leverage the full potential of IoT resources to build intelligent, effective ecosystems that meet the needs of contemporary society by solving difficulties and utilizing developing trends.

Chapter 13 - WoX: Model-Driven Development of Web of Things Applications

The concept of the Internet of Things (IoT) has fundamentally redefined the connectivity landscape by integrating physical devices with the Internet for data exchange. The Web of Things (WoT) takes this integration a step further by embedding IoT devices within the web, thus facilitating their interoperability. However, the inherent complexity of WoT architecture requires a layer of abstraction to simplify development and integration. Patterns and reference architectures (RAs) provide such an abstraction, modeling solutions for recurrent problems within this domain. In this paper, we aim to develop an RA for the WoT ecosystem. We use architectural patterns to build the RA of the WoT. Here, we present the WoT gateway pattern, which provides a clear and adaptable framework for integrating diverse IoT devices, ensuring seamless communication and functionality within the broader web ecosystem. The purpose of this pattern is twofold: to ensure the interoperability of WoT implementations and to serve as a foundational guide for developers navigating the multifaceted challenges of WoT system design. The pattern also paves the way for building an RA for IoT environments. KEYWORDS Architectural patterns, Internet of Things, reference architecture, web development, web science, WoT

Interacting with the Web of Things

Internet of things (IoT) has been researched in recently years. The Savant as a midware provides the data collecting and pre-processing for the IoT applications. Data grid can aggregate the resources in the IoT. Using data grid to build the Savant enables the Savant manage large scale data and optimizes the efficiency of the resources in IoT. In this paper, the data in the IoT is classified, and a data grid based Savant is designed. In addition, the key issue of data replication strategy is analyzed, and a advanced cascading strategy is proposed according to the features of the Savant. After the simulation to the strategy, In the simulation of the data replication strategy, the performance of the advanced cascading is lower than that of the cascading by 3.6%. However, the bandwidth consumption and the storage occupation are brought down by 12.5% and 25.9%.

Cloud of Things (CoT) consists of heterogeneous Cloud and Internet of Things (IoT) resources. CoT increasingly requires adaptive run-time management due to the CoT dynamism, environmental uncertainties and unpredictable changes in IoT resources. Adapting to these changes benefits particularly trading of CoT resources where the adaptability of traded resources and applications remains a challenge. Run-time changes in CoT trading environments can impact vital aspects including resource allocation, resource utilisation and application performance. This paper adopts monitoring, analysis, planning and execution (MAPE) model from autonomic computing to support adaptations when trading CoT resources. This is achieved by applying the MAPE model to systematically capture and identify changes in CoT environment. Based on the identified adaptations, an adaptive model is proposed to react to these changes.

Web of Things (WoT) extends the Internet of Things (IoT) paradigm to facilitate communications among smart things/devices and Web-based applications. In other words, WoT systems generally provide a Web interface for the monitoring and controlling of smart devices over the Web, for example, in applications, such as home automation, intelligent transportation system, smart healthcare, smart cities, and smart agriculture. However, this results in the generation of significant volume of data (i.e., big data) and, hence, the importance of big data analytics. There are also associated security and privacy implications. Therefore, in this article, we present a signature-based authentication and key agreement scheme for the WoT environment and prove its security. We also evaluate the performance of SCS-WoT and compare it against four other competing schemes. The findings show that SCS-WoT achieves better performance in terms of communication cost, computational cost, and security and functionality.

The Internet of Things (IoT) is being applied for stovepipe solutions, since it presents a semantic description limited to a specific domain. IoT needs to be pushed towards a more open, interoperable and collaborative IoT. The first step has been the Web of Things (WoT). WoT evolves the IoT with a common stack based on web services. But, even when a homogeneous access is reached through web protocols, a common understanding is not yet acquired. For this purpose, the Semantic Web of Things (SWoT) is proposed for the integration of the semantic web on the WoT. This work analyses the SWoT, presenting its different levels to offer an IoT convergence. Specifically, we analyse the trends for capillary networks and for cellular networks with standards such as IPSO, ZigBee, OMA, and the oneM2M initiative. This work also analyses the impact of the semantic-annotations/metadata in the performance of the resources.

Internet of Things (IoT) is considered very widely spread in these days application and technology, which means a huge amount of data will need to be exchanged between devices and applications domains., For example, a weather application needs to communicate with a traffic application. Data between both applications need to be interpreted and to be interoperable in both applications. These applications are based on domain-specific, which means there is no domain interoperability. As a result, some developers and users took the web approach to find an easy solution that can be offered from the web itself, which leads to the Web of Things (WoT). But as with most recommendations in the web community, if data interoperability is needed as part of your implementation, you need to use Semantic Web as an approach that leads to a combined approach called Semantic Web of Things (SWoT). However, not every developer and user are having experience with Semantic Web standards such as RDF, Turtle, RDF/XML, SPARQL, OWL, etc. This paper proposes WOTJD for WoT using JavaScript Object Notation Linked Data (JSON-LD). WOTJD helps IoT users to overcome the main challenges of data interoperability in WOT by helping in (1) Design and integrate WOT applications, (2) IoT data parsing and annotation, and (3) Linking domains with each other (by using domain knowledge expertise), A case study of solving interoperability between smart cars and weather domain through a mobile application is presented, and performance evaluation has been performed, Experimental results show how fast is WOTJD framework against the sensor data size.

PurposeThe purpose of the study was to investigate factors promoting innovation and application of internet of things in academic and research information organizations.Design/methodology/approachQuantitative research design involved survey of selected academic and research information organizations in public and private chartered institutions. Information professionals, digital content managers, information systems and technologists that normally consume big data and technological resources were involved in the process of data collection using structured questionnaire and content analysis. Information organizations and information practitioners were selected from public and private academic and research institutions.FindingsInnovation of internet of things has increasingly transformed and changed academic and research information organizations as the source of knowledge in addition to expanding access to education, data, information and communication anywhere anytime through hyperconnectivity and networking. Internet of things technologies such as mobile of things, web of things, digital information systems and personal devices are widely applied by digital natives in academic and research information organizations. Mobilization platform and devices is the single biggest provider of data, information and knowledge in academic and research organizations. Modern trends in education and knowledge practices in academic institutions and information organizations depends upon internet of things, digital repositories, electronic books and journals, social media interfaces, multimedia applications, information portal hubs and interactive websites, although challenges regarding inadequate information communication technology infrastructure and social computing facilities still persist.Research limitations/implicationsInformation organizations in public and private chartered academic and research institutions were adopted in the study. Respondents handling and supporting information management, planning and decision-making provided the necessary data. Information professionals, digital content managers, information systems and technologists are proactively involved in data and information analytics.Practical implicationsAcademic and research information organizations are powerhouses that provide knowledge to support research, teaching and learning for sustainable development and the betterment of humanity and society. Innovation of internet of things and associated technologies provides practical aspects of attaining sustainable information development practices in the contemporary knowledge society. Internet of things technologies, principles of economies of scale and investment and customer needs entail that information organizations and practitioners should provide appropriate and smart systems and solutions.Social implicationsModern academic and research information organizations have the social corporate responsibility to offer technological innovations to heighten access to knowledge and learning in academic and research institutions. Economically, innovation and application of internet of things provide unlimited access to big data and information in organizations all the time anywhere anytime.Originality/valueData management is a growing phenomenon that information practitioners need to fully understand in the digital economies. Information professionals need to embrace and appreciate innovation and application of internet of things technologies whose role in sustainable development practices is critical in academic and research organizations.

In the vision of the Internet of Things (IoT), an increasing number of embedded devices of all sorts (e.g., sensors, mobile phones, cameras, smart meters, smart cars, traffic lights, smart home appliances, etc.) are now capable of communicating and sharing data over the Internet. Although the concept of using embedded systems to control devices, tools and appliances has been proposed for almost decades now, with every new generation, the ever-increasing capabilities of computation and communication pose new opportunities, but also new challenges. As IoT becomes an active research area, different methods from various points of view have been explored to promote the development and popularity of IoT. One trend is viewing IoT as Web of Things (WoT) where the open Web standards are supported for information sharing and device interoperation. By penetrating smart things into existing Web, the conventional web services are enriched with physical world services. This WoT vision enables a new way of narrowing the barrier between virtual and physical worlds.In this paper, we elaborate the architecture and some key enabling technologies of WoT. Some pioneer open platforms and prototypes are also illustrated. The most recent research results are carefully summarized. Furthermore, many systematic comparisons are made to provide the insight in the evolution and future of WoT. Finally, we point out some open challenging issues that shall be faced and tackled by research community.

The number of devices connected together in the Internet of Things (IoT) are growing and therefore the demand of an efficient and secure method for discovering the resources in IoT is increasing. In most of IoT schemes, the resources are discovered based on their properties (i.e. their location, types, etc.) and the clients are able to discover the resources that are registered in the network. This discovery ability can be restricted to a number of clients by encrypting the discoverable address. However, any client with the key can decrypt and access a private resource regardless of the attributes of the client. In this paper, a decentralized resource discovery model using Cipher Policy Attribute Based Encryption (CP-ABE) and Distributed Hash Table (DHT) is introduced that allows secure and private discovering of the resources in IoT network. We integrated the CP-ABE that allows clients only by users' inherent attributes, to discover the resources in the network. Our proposed model provides a higher level of security for resource discovery by allowing the resources during registration in addition to their properties to define the attributes of the clients that are able to discover those resources. The model we proposed uses multi-authority ABE, which as a public key encryption can fit the decentralized environment.

A vast amount of data (known as big data) may now be collected and stored from a variety of data sources, including event logs, the internet, smartphones, databases, sensors, cloud computing, and Internet of Things (IoT) devices. The term “big data security” refers to all the safeguards and instruments used to protect both the data and analytics processes against intrusions, theft, and other hostile actions that could endanger or adversely influence them. Beyond being a high-value and desirable target, protecting Big Data has particular difficulties. Big Data security does not fundamentally differ from conventional data security. Big Data security issues are caused by extraneous distinctions rather than fundamental ones. This study meticulously outlines the numerous security difficulties Large Data analytics now faces and encourages additional joint research for reducing both big data security challenges utilizing Ontology Web Language (OWL). Although we focus on the Security Challenges of Big Data in this essay, we will also briefly cover the broader Challenges of Big Data. The proposed classification of Big Data security based on ontology web language resulting from the protégé software has 32 classes and 45 subclasses.