Conference Paper

Resource discovery in Internet of Things: Current trends and future standardization aspects

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... Today's IoT and IIoT technologies can be grouped into Society, Industry and Environment domains [25]. Refer to idea of [26], every searching techniques in any IoT areas, such as event-based search, location-based search, time-related search, content-based search, spatiotemporal search, context-based search, real-time search, and user-interactive search, are varied and not similar to each other. ...
... In table 2 below, we have listed only the related knowledge-based learning methods and compared their key advantages and disadvantages as a reference for potential researchers. [25] and equally likely to be chosen. 4 Blackboard Resource Discovery Mechanisms [25] If no suggested node is identified, the artificial intelligence procedure using queries is forwarded spontaneously. ...
... [25] and equally likely to be chosen. 4 Blackboard Resource Discovery Mechanisms [25] If no suggested node is identified, the artificial intelligence procedure using queries is forwarded spontaneously. ...
Article
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This paper discusses several issues supporting a knowledge-based methodology for discovery of high-volume IoT resources in the simulator NS-3 environment. We found the concept was developed in previous researches, especially based on widely accepted concepts of Q-Learning discovery model. The model is validated using samples from emulations of tested data in the NS-3 simulator. Proper simulation in NS-3 based on the different modules such as checkpoint and restore was used to model and analyse the data. The main feasibility checkpointing concept of simulations in the NS-3 processes were using Distributed Multi-Threaded Checkpointing (DMTCP) to run on a single machine and Message Passing Interface (MPI) under distributed machine to speed up the NS-3 model initialization and execution. As the chosen model to be implemented in this analysis, the Q-learning algorithm proposal offers a possible solution for addressing evolving IoT environments and configurations. Q-learning is one of the successful techniques available for the exploration of IoT nodes, but context-based problems have already been established and simplified as issues of dedicated server management, IoT object data acquisition issues, and unique application requirements. The findings empirically support the validation of the Q-Learning model improvement for high-volume IoT resource discovery cases. The study will contribute to the new model development by providing new insights on the conceptualization and validation of knowledge-based methodology based on widely accepted techniques and approaches.
... Resource Discovery "refers to crawling, finding, and allowing IoT resources to be found/discovered automatically or manually" [11]. An IoT resource can be an object/device, data, or service [6][12] [13][11] [14]. Resource Discovery is an essential step in any IoT system to work properly [15]. ...
... The diverse nature of IoT device capabilities, properties and communication technologies adds to the complexity of effective realization of IoT platforms. The traditional web based discovery service is not suitable for IoT because of the different requirements of IoT [13]. Many techniques are used to discover the resources. ...
... Moreover, IoT devices are not similar, so the discovery must respect the device diversity, location (local or remote) and nature and limitation (e.g. sleep/idle mode to save the device battery power) [12] [13]. In IoT, device heterogeneity is considered the main challenge in all operations including discovery, and more research is yet required in dynamic heterogeneous resource discovery [6]. ...
Article
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Internet of Things (IoT) is widely implemented in applications that require immediate interaction and fast response. Resource discovery is an essential step in any IoT system where the resource can be an object/device/thing/sensor, data, or service. Several resource discovery techniques were proposed in literature to discover various types of resources. This paper surveys existing IoT resource discovery techniques and classifies them with respect to discovery approach. In particular, the paper focuses on discovery techniques for object/thing/device and service. A set of properties are suggested to be used as evaluation parameters for discovery techniques, and these properties are mapped against discovery technique classes.
... It maximizes the utilization of these sensors since it enables IoT platforms to automatically detect the capabilities of connected IoT devices upon their registration. It is one of the fundamental requirements of any IoT platform which minimizes, or ideally eliminates the need for external human intervention for configuration and maintenance of deployed objects [3]. ...
... Authors in [1] propose the usage of Constrained Application Protocol (CoAP) together with Domain Name System Resource Discovery protocol (DNS-SD). However, CoAP has several specification issues [3]. It does not specify how a thing should join the CoAP server first time and announce itself, there is no specification on how a remote client can look up into the resource directory and query for the resource of interest, and a centralized approach using resource discovery and CoAP suffers from scalability issues and denial of service (DoS) attacks. ...
... Architecture for resource discovery can have the following layers [3]: proxy layer, discovery layer, service enablement layer and application layer. Proxy layer enables discovery of physical things regardless of communication technologies and protocols used by the things. ...
Chapter
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Internet of Things (IoT) systems are becoming omnipresent, with miscellaneous solutions in diverse domains. To release the full potential of the IoT, it is needed to have dynamic user-centric systems where services can be executed according to user demands. A growing number of devices that is being deployed need to be capable to be discovered easily by the IoT platforms, and offer their services automatically, without human intervention. Due to the complexity of IoT systems, automatic discovery and management of services offered by IoT devices is rarely aligned with user demands. In this paper we propose an agent-based approach which enables the discovery and management of IoT services. Furthermore, it enables the control of devices according to user-defined rules or direct commands.
... Considerando as características da computação em névoa, tais como a mobilidade, a alta distribuição geográfica, e também a heterogeneidade, o processo de descoberta de recursosé considerado um grande desafio e fundamental para o ambiente [Datta et al. 2015]. No artigo [Masip et al. 2020] o problema de descoberta de recursos na computação em névoaé declarado como uma forma de projetar uma solução para encontrar recursos pertencentes a componentes dispostos a se juntar ao ambiente. ...
... Visão geral da proposta para descoberta de recursos.Para a comunicação com os dispositivos também foi necessário utilizar um protocolo de comunicação. Atualmente na literaturaé possível encontrar propostas que utilizam diversos tipos de protocolos, entre os quais o Message Queuing Telemetry Transport (MQTT)[Khalil et al. 2020], o Constrained Application Protocol (CoAP)[Datta et al. 2015], e o Open Communication Foundation (OCF)[Jin and Kim 2018]. Para a nossa proposta, no entanto, foi escolhido o protocolo Named Data Networking (NDN), queé conduzido pelos consumidores de dados, por meio da troca de pacotes de Interesse e Dados[Zhang et al. 2014], conforme apresentado na Figura 2. Atrelado ao algoritmo de descoberta, o protocolo NDN será fundamental para obter as informações e a descrição dos fog nodes. ...
Conference Paper
A Computação em Névoa é um paradigma que permite o provisionamento de recursos e serviços computacionais na borda da rede, mais próximos dos dispositivos finais e usuários, com menor latência, complementando a Computação em Nuvem. A heterogeneidade, a alta distribuição geográfica e o grande número de dispositivos são desafios para realizar a descoberta de recursos otimizada neste ambiente. Este artigo apresenta uma proposta para o processo de descoberta de recursos em computação em névoa.
... Devices must be able to handle new or leaving devices themselves in a decentralized manner. Datta et al. (Datta et al., 2015) categorize related work in the area of discovery into the following areas: distributed and peer-to-peer discovery services, centralized architectures, CoAP-based service discovery, semantic-based discovery, search engines for resource directory, and utilization of ONS and DNS. ...
... (Datta et al., 2015) (Fredj et al., 2014) (Bermudez-Edo et al., 2016) (Shelby et al., 2014) (Shelby et al., 2013) (Cirani et al., 2014) (Del Gaudio et al., 2020) FR 2 Interoperability (Akyildiz et al., 2002) (Shelby et al., 2014) (Hunkeler et al., 2008) (Meng et al., 2016) FR 3 Portability and Software Provisioning (Binz et al., 2012) (Franco da Silva et al., 2016) (Franco da Silva et al., 2017) Meyer et al., 2013) (Andrews et al., 2003) (White, 2004) (Seeger et al., 2018b) (Seeger et al., 2018a) (DelGaudio and Hirmer, 2019) Mahfouz et al., 2009) (Wang et al., 2013) (Witrisal et al., 2016) ...
... The number of devices connected together as the Internet of Things (IoT) are growing and expected to reach 50 billion by 2020 [1], and therefore the demand of a fast and efficient method to find an object (i.e. a device) in IoT is increasing [2]. The traditional search model is based on host centric scheme which address the question of how one host can reach another one. ...
... The resource discovery [2] is a mechanism to return the address of a resource based on the information provided during the lookup operation. The resource address could be its URI, other metadata and further links about the resource. ...
... Nevertheless, the rapid technological development and deployment of IoT devices [2] have led to the emergence of new use cases at the edge of the network where the use of the cloud infrastructure is not the most suitable solution, as for example, delay-sensitive applications that need to operate with a lower latency than the one offered by cloud, such as critical urban infrastructure or eHealth monitor devices. In these cases, the cloud's centralized nature and the conceptual distance between the cloud datacenter and the user/ device requesting the service [3] prevent cloud to meet the low-delay requirement. ...
... The result (2) shows that the probability of collision is 0.00076, that is, 0.076%: ...
Article
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Fog-to-Cloud (F2C) is a novel paradigm aiming at extending the cloud computing capabilities to the edge of the network through the hierarchical and coordinated management of both, centralized cloud datacenters and distributed fog resources. It will allow all kind of devices that are capable to connect to the F2C network to share its idle resources and access both, service provider and third parties resources to expand its own capabilities. However, despite the numerous advantages offered by the F2C model, such as the possibility of offloading delay-sensitive tasks to a nearby device and using the cloud infrastructure in the execution of resource-intensive tasks, the list of open challenges that need to be addressed in order to have a deployable F2C system is pretty long. In this paper we focus on the resource identification challenge, proposing an identity management system (IDMS) solution that starts assigning identifiers (IDs) to the devices in the F2C network in a decentralized fashion using hashes and afterwards, manages the usage of those IDs applying a fragmentation technique. The obtained results during the validation phase show that our proposal not only meets the desired IDMS characteristics, but also that the fragmentation strategy is aligned with the constrained nature of the devices in the lowest tier of the network hierarchy.
... 3) Real-time search engine: In [26] search engine Dyser is proposed that have the ability of scalability of Things and also support rapidly change contents or in another word real-time search engine using two approaches, A) Proactive which called Push approach in which sensor update the index itself and query response by the search engine. B) In Pull approach when a query is initiated then request sends to the sensor for required data. ...
... Implementation of this research is using Java and PHP technologies. Sensor Gateways are implanted using SOAP [26] and Java technologies for fetching the information. Gateways also generate automatically pages for testing purposes using REST www.ijacsa.thesai.org ...
Article
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Internet of Things (IoT) referred to interconnected the world of things like physical devices, cars, sensors, home appliances, actuators and machines embedded with software at any time, any location. The increasing number of IoT devices facing challenges which are registration, integration, describing sensor, interoperability, semantics, security, discovery and searching. The current systems are suitable for limited number of devices. Our ecosystem change day by day which means we have billions and trillions of devices connecting to the Internet in future. One major challenge in current system is searching of suitable Smart Things from a millions or even billions number of devices in IoT. For the purpose of searching and indexing, some discovery methods and techniques are discussed and compared. Those techniques and methods are studied and find out the limitations and issued of the current system. Another challenge to searching the Smart Things is a variety of description models for describing the Smart Things. In this piece of work, a novel search engine is proposed to search the Smart Things with variety of description models. A web interface is implemented in this research with HTML, JSON and XML formats. The description models of Smart Things SensorML, SensorThings API and W3C JSON-LD are implemented in the current proposed system. © 2018 International Journal of Advanced Computer Science and Applications.
... In [24], a new framework for SD in IoT was proposed which is based on three layers: (1) Proxy layer aiming at discovering physical things regardless of the protocols and communication technologies being used, (2) Discovery Layer, which consists of a database where resource parameters can be stored. ...
Article
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A critical requirement in Mobile Ad Hoc Networks (MANETs) is its ability to automatically discover existing services as well as their locations. Several solutions have been proposed in various communication domains which could be classified into two categories: (1) directory based, and (2) directory-less. The former is efficient but suffers from the amount of control messages being exchanged to maintain all directories in an agile environment. However, the latter approach attempts to reduce the amount of control messages to update directories, by simply sending broadcast messages to discover services; which is also a non-desirable approach in MANETs. This research work builds on top of our prior work (Nazeeruddin et al. in IFIP/IEEE international conference on management of multimedia networks and services, Springer, Berlin, 2006)) where we introduced a new efficient protocol for service discovery in MANETs (MSLD); a lightweight, robust, scalable, and flexible protocol which supports node heterogeneity and dynamically adapts to network changes while not flooding the network with extra protocol messages—a major challenge in today’s network environments, such as Internet of Things (IoT). Extensive simulations study was conducted on MSLD to: (1) initially evaluate its performance in terms of latency, service availability, and overhead messages, then (2) compare its performance to Dir-Based, Dir-less, and PDP protocols under various network conditions. For most performance metrics, simulation results show that MSLD outperforms Dir-Based, Dir-less, and PDP by either matching or achieving high service availability, low service discovery latency, and considerably less communication overhead.
... This approach takes into consideration context awareness and QoS along with trust factor while delivering services to consumers. Authors in [21] have proposed a search engine based discovery framework that makes use of a central directory to store and index resources or services. ...
Article
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As automobile sector is witnessing a paradigm shift from Internal Combustion Engine (ICE) based vehicles to smart electric vehicles, a new concept of connected vehicles has emerged that is able to provide a number of services to its users. Internet of Vehicles has now transformed to an indispensable platform of information exchange among vehicles, city infrastructure, drivers and other connected entities. Due to highly dynamic nature of Internet of Vehicles, there is need of a dynamic service discovery infrastructure that can cater to Internet of Vehicle specific challenges. This paper is a step ahead in that direction to provide a distributed service discovery protocol that facilitates service discovery and service selection for Internet of Vehicles environment. We have proposed a clustering based service discovery approach that makes use of neighbor awareness to find neighboring vehicles. Proposed protocol has been validated by running extensive simulations and results show the improvement in terms of query success rate, transmission rate and transmission cost by a considerable margin.
... The resources can be registered in different parts of the network distributed among many nodes (Figure 1a) or in a centralised trusted entity (Figure 1b). The resource discovery [9] is a mechanism to return the access address of a resource based on the information provided during the lookup operation. The resource access address can be its IP and port addresses, its URI or other metadata and further links about the resource. ...
Article
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The resources in the Internet of Things (IoT) network are distributed among different parts of the network. Considering huge number of IoT resources, the task of discovering them is challenging. While registering them in a centralized server such as a cloud data center is one possible solution, but due to billions of IoT resources and their limited computation power, the centralized approach leads to some efficiency and security issues. In this paper we proposed a location aware and decentralized multi layer model of resource discovery (LaMRD) in IoT. It allows a resource to be registered publicly or privately, and to be discovered in a decentralized scheme in the IoT network. LaMRD is based on structured peer-to-peer (p2p) scheme and follows the general system trend of fog computing. Our proposed model utilizes Distributed Hash Table (DHT) technology to create a p2p scheme of communication among fog nodes. The resources are registered in LaMRD based on their locations which results in a low added overhead in the registration and discovery processes. LaMRD generates a single overlay and it can be generated without specific organizing entity or location based devices. LaMRD guarantees some important security properties and it showed a lower latency comparing to the cloud based and decentralized resource discovery.
... The resources can be registered in different parts of the network distributed among many nodes or in a centralised trusted entity. The resource discovery [14] is a mechanism to return the address data of a resource based on the information provided during the lookup operation. The resource address data can be its IP and port, its URI or other metadata and further links about the resource. ...
Conference Paper
The Internet of Things (IoT) consists of billions of resources distributed among different geographical locations. In centralized resource discovery, the resources are registered in a centralized third party server, and the clients can discover any resource by querying the centralized entity. In the decentralized resource discovery the task of resource registration and discovery is distributed among many nodes in the system. Replacing a centralized entity with a distributed set of nodes requires that a system fulfils some security and performance requirements. In this paper, the centralized and decentralized resource discovery models are discussed. In addition, the properties of decentralised resource discovery are studied and some of the fundamental and most important requirements for such models are discussed. Each of the fundamental requirements in decentralized resource discovery are analysed and the possible approaches and their feasibility in IoT network are studied.
... Resources Discovery is, consequently, one of the major challenges in an environment like IoT, where objects are supposed to communicate, interact and exchange services autonomously. The term resource could mean physical objects and/or associated metadata or the services provided by the objects (Datta et al. (2015)). Several approaches have been proposed to ensure resource discovery in the literature. ...
Thesis
The Internet of Things (IoT) is a paradigm that has made everyday objects intelligent by giving them the ability to connect to the Internet, communicate and interact. The integration of the social component in the IoT has given rise to the Social Internet of Things (SIoT), which has overcome various issues such as interoperability, navigability and resource/service discovery. In this type of environment, participants compete to offer a variety of attractive services. Some of them resort to malicious behavior to propagate poor quality services. They launch so-called Trust-Attacks (TA) and break the basic functionality of the system. Several works in the literature have addressed this problem and have proposed different trust-models. Most of them have attempted to adapt and reapply trust models designed for traditional social networks or peer-to-peer networks. Despite the similarities between these types of networks, SIoT ones have specific particularities. In SIoT, there are different types of entities that collaborate: humans, devices, and services. Devices can have very limited computing and storage capacities, and their number can be as high as a few million. The resulting network is complex and highly dynamic, and the impact of Trust-Attacks can be more compromising. In this work, we propose a Multidimensional, Dynamic, Resources-efficient and Scalable trust-model that is specifically designed for SIoT environments. We, first, propose features to describe the behavior of the three types of nodes involved in SIoT networks and to quantify the degree of trust according to the three resulting Trust-Dimensions. We propose, secondly, an aggregation method based on Supervised Machine-Learning and Deep Learning that allows, on the one hand, to aggregate the proposed features to obtain a trust score allowing to rank the nodes, but also to detect the different types of Trust-Attacks and to counter them. We then propose a hybrid propagation method that allows spreading trust values in the network, while overcoming the drawbacks of centralized and distributed methods. The proposed method ensures scalability and dynamism on the one hand, and minimizes resource consumption (computing and storage), on the other. Experiments applied to synthetic data have enabled us to validate the resilience and performance of the proposed model.
... Resource Discovery in IoT [T8] -They Developed a new framework shown in figure-3 based on a searching system, which provides the capacity of discovering resources efficiently and automatically. This framework includes a search engine, which offers the ability to finding an IoT object in local or remote range through RESTful web service [10] An adaptive meta-heuristic search [T9] -This study claims a mechanism that can organize those IoT sensors with similar context information in the form of Sensor Semantic Overlay Networks (SSONs) and group them into a cluster. This system is inspired by ant clustering algorithm and designed to perform search in the large amount number of shared data that dynamically generated by millions of IoT devices all the time [11]. ...
... Paper [25] presents a search engine based resource discovery framework which is made up of three layers, namely proxy, discovery and service enablement layer. The proxy layer discovers the objects regardless of their technologies. ...
Article
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Efficient resource management is a challenging task in distributed systems, such as the Internet of Things, fog, edge, and cloud computing. In this work, we present a broad overview of the Internet of Things ecosystem and of the challenges related to managing its resources. We also investigate the need for efficient resource management and the guidelines given/suggested by Standard Development Organizations. Additionally, this paper contains a comprehensive survey of the individual phases of resource management processes, focusing on resource modeling, resource discovery, resource estimation, and resource allocation approaches based on performance parameters or metrics, as well as on architecture types. This paper presents also the architecture of a generic resource management enabler. Furthermore, we present open issues concerning resource management, pointing out the directions of future research related to the Internet of Things.
... Some authors like [41] have claimed that the performance of IoT and Big Data applications and IoT devices with each other as well as with information systems. Accepting a Service Oriented Architecture (SOA) approach naturally helps integrate devices with enterprise systems. ...
Article
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Software-Defined Internet of Things (SDIoT) is defined as merging heterogeneous objects in a form of interaction among physical and virtual entities. Large scale of data centers, heterogeneity issues and their interconnections have made the resource management a hard problem specially when there are different actors in cloud system with different needs. Resource management is a vital requirement to achieve robust networks specially with facing continuously increasing amount of heterogeneous resources and devices to the network. The goal of this paper is reviews to address IoT resource management issues in cloud computing services. We discuss the bottlenecks of cloud networks for IoT services such as mobility. We review Fog computing in IoT services to solve some of these issues. It provides a comprehensive literature review of around one hundred studies on resource management in Peer to Peer Cloud Networks and IoT. It is very important to find a robust design to efficiently manage and provision requests and available resources. We also reviewed different search methodologies to help clients find proper resources to answer their needs.
... Very similar to our approach is the research area of discovery in the IoT. Datta et al. (Datta et al., 2015) categorize related work in the area of discovery into the following areas: distributed and peerto-peer discovery services, centralized architectures, CoAP-based service discovery, semantic-based discovery, search engines for resource directory, and utilization of ONS and DNS. ...
... A hierarchical resource discovery scheme is proposed in [14], where resources are found by traversing the hierarchy of gateways presenting IoT devices. In large-scale distributed IoT applications, search engines and layered resource discovery frameworks, as in [15], [16], provide discovery services with structured document and linked open data. In [17], both centralized and distributed service discovery solutions utilize network routers as CoRE RD peers that also perform discovery load balancing. ...
Preprint
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Mist computing leverages Internet of Things applications to the IoT devices at the edges of the networks. The dynamic characteristics of the IoT environment and resource limitations make the orchestration of the mist platform difficult. In this paper, we present a hybrid resource discovery solution for mist, with IETF CoRE Resource Directories deployed to the edge devices as containerized microservices, facilitating their on-demand deployment. Each directory at an edge devices manages a mist network, enabling bottom-up low latency resource queries at one-hop distance from mist and top-down queries from cloud and edge. Moreover, the directories form a horizontal discovery infrastructure across the edge deployment, connecting resources in disparate mist networks. A real-world prototype discovery infrastructure is implemented, with low resource edge devices hosting the directories and low-power embedded devices as the resource servers and clients. The prototype is evaluated with latency and power consumption measurements, where the results show that discovery latency is as low as half a millisecond with a low power consumption.
... An alternative approach is adopted in the management frameworks that rely on IoT gateways to directly handle the interactions between applications and IoT resources, providing efficient services for resource discovery and access. In cloud-centric IoT systems, such IoT gateways are typically deployed in the cloud infrastructure (Datta et al., 2015). For instance, the DNS-SD protocol uses a central repository to facilitate service discovery for IoT applications (Cheshire and Krochmal, 2013). ...
Article
Edge/fog computing is an emerging paradigm that exploits computing and management at the edge of the network to improve QoS of traditional cloud-centric IoT applications. In large-scale IoT deployments, multiple applications are expected to access the same constrained resource (e.g., a sensor) with heterogeneous QoS requirements. However, IoT applications may be unable to adapt their access patterns to cope with bandwidth limitations. To address this issue, we propose a fog-based IoT broker that determines suitable notification rates to access IoT resources while maximising applications' QoS and avoiding network congestion. We first formalise the rate selection as an optimisation problem, and then we propose a practical algorithm that leverages transmission reliability to dynamically select notification periods. We developed a CoAP-based prototype and validated our proposal through simulations and experiments in a real IoT testbed. Our broker provides higher QoS satisfaction, throughput and energy efficiency compared to a conventional CoAP proxy.
... To provide value-added services to end users through IoT platforms, these devices must be discovered by resources in the cloud and by other devices. Services for resource discovery in the IoT are generally proposed using RESTful web services [28]. ...
Article
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In this paper, we describe the design and the management of an agent-based system that supports distributed brainstorming activities. The support system is a highly coordinated IoT application composed of many locally installed interface devices, multimedia communication functions, and cloud functions that process application logic and store meeting data. The system is designed to support a variety of brainstorming sessions, so its functionalities must be modifiable and enable the system to be adapted to different environments and user requirements without any loss of performance. System accessibility should be also ensured from any location for any user. These constraints require a flexible and usable support system. We further discuss the aspects of flexibility and usability that are important in a support system for distributed brainstorming, from which we propose a conceptual schema for flexible and usable support systems. To realize this schema, we present a resource-oriented architecture that can modify the brainstorming support system’s structure and functions. Flexibility is achieved thanks to an agent-based system that manages resources and operates on them according to users’ requests. We also describe the system architecture, which is organized around a set of channels dedicated to different services proposed to the users. We present in detail a video channel that ensures user awareness during synchronized activities. We then conduct several experiments verifying the usability of important channels in the architecture and present the results of these experiments. Finally, we discuss experimental scenarios that show how the system owes its adaptability to management based on an agent organization that supports distributed brainstorming and other activities.
... An alternative approach is adopted in the management frameworks that rely on IoT gateways to directly handle the interactions between applications and IoT resources, providing efficient services for resource discovery and access. In cloud-centric IoT systems, such IoT gateways are typically deployed in the cloud infrastructure (Datta et al., 2015). For instance, the DNS-SD protocol uses a central repository to facilitate service discovery for IoT applications (Cheshire and Krochmal, 2013). ...
Article
Edge/fog computing is an emerging paradigm that exploits computing and management at the edge of the network to improve QoS of traditional cloud-centric IoT applications. In large-scale IoT deployments, multiple applications are expected to access the same constrained resource (e.g., a sensor) with heterogeneous QoS requirements. However, IoT applications may be unable to adapt their access patterns to cope with bandwidth limitations. To address this issue, we propose a fog-based IoT broker that determines suitable notification rates to access IoT resources while maximising applications’ QoS and avoiding network congestion. We first formalise the rate selection as an optimisation problem, and then we propose a practical algorithm that leverages transmission reliability to dynamically select notification periods. We developed a CoAP-based prototype and validated our proposal through simulations and experiments in a real IoT testbed. Our broker provides higher QoS satisfaction, throughput and energy efficiency compared to a conventional CoAP proxy.
... Liu et al. [60] proposed a distributed resource discovery (DRD) architecture to discover resources in M2M applications and implement interoperability between heterogeneous devices and enable resources access to resource-constrained embedded devices from the Internet. Datta et al. [61] proposed a framework for automatic and efficient resource discovery in the IoT. But identity addressing of IoT based on search engine also faces some challenges, such as searching for things in the IoT that require tight binding to contextual information. ...
Article
With the development of the Internet of Things (IoT), the physical space we are living in is experiencing unprecedented digitalization and virtualization. It is an overwhelming trend to achieve the convergence between physical space and cyberspace, where the fundamental problem is to realize the accurate mapping between the two spaces. Therefore, identity modeling and identity addressing, which serve as the main bridge between physical space and cyberspace, are regarded as important research areas. This paper summarizes the related works regarding identity modeling and identity addressing in IoT, and makes a general comparison and analysis based on their respective features. Following that a flexible and low coupling framework, with strong independence between different modules is proposed, where both identity modeling and identity addressing are integrated. Meanwhile, we discuss and analyze the future development and challenges of identity modeling and addressing. It is proved that the identity modeling and identity addressing are extremely significant topics in the era of IoT.
... Work in [12] is a first attempt at applying Web oriented patterns (REST) to service discovery, so to enable integration of heterogeneous physical devices into digital information systems. Finally, authors of the paper [13] provide a thorough categorization of the current technology landscape for resource discovery in IoT and also proposes a discovery framework based on REST APIs. The API manages registration and indexing of resources, whose metadata are represented using CoRE Link Format. ...
... According to the rapidly increasing number of IoT devices, the naming IoT devices is important to efficiently manage these devices and its resources [38]. The schemes of dynamic naming services are proposed to be used for IoT devices. ...
Article
Full-text available
With the rapid development of Internet of Things (IoT) technologies in various domains including smart homes, smart cities, smart factories and smart buildings where Internet-connected devices are deployed to provide IoT services based on heterogeneous frameworks and platforms. Many standard protocols, frameworks, libraries and specifications have been proposed for developing IoT applications. Therefore, providing a consistent scheme is important for supporting the interoperability in heterogeneous IoT devices to interact in the same domain and cross-domain. Moreover, supporting the device transparent access for clients to consume IoT service from the different environment that can provide user-friendly service scenarios although the user consumes services in different IoT networks. In this paper, we propose an improved Resource Directory (RD) based on a Domain Name System (DNS) Name Self-Registration (DNSNSR) for the device transparent access in heterogeneous IoT networks. For supporting proposed DNSNSR, an IoT RD is presented based on the Open Connectivity Foundation (OCF) standard specification to provide device registration and discovery service. Through the registration interface, the IoT RD configures the DNS names using Bind 9 to provide the DNS service in an IoT network based on the published device information. Using the discovery interface of RD and name resolution of DNS, the IoT Client gets devices information including (Identifier) ID and Internet Protocol (IP) to access IoT Devices without considering underlying protocols through the interworking proxy of proposed RD in heterogeneous IoT networks. Therefore, the proposed RD based on DNSNSR enables the IoT devices to be discovered by IoT clients in the various environment through the RD and DNS functions. Furthermore, using the OCF-direct and proxy-based access mechanism, the proposed RD based on DNSNSR supports IoT devices to be accessed by clients in various IoT environment.
... Although there has been significant research in the general area of security and privacy in edge and fog computing [45], [46], [47], [48], [49], [50], literature on access management for resource sharing is rather scarce. In order to improve the efficiency of resource lookup using centralized architectures, distributed and peer-to-peer networks, RESTful web APIs, etc., include approaches that employ centralized search engines [51], single [52] or k-hop [53] distributed hash tables, and other scalable look up solutions [54], [55], [56]. Although relevant, these are not applicable to an edge computing infrastructure without significant modifications. ...
... Good resource discovery mechanisms are essential for distributed systems to optimally utilize the available resources in the network [15], and improve the efficiency of the network [16]. Many such methods exist, and a thorough review is available in [17]. ...
... Resource discovery [4] is an important challenge in any distributed system such as distributed clouds [5], peer-to-peer networks [6], and grids [7]. It is essential to achieve pervasive behavior, in which it devices and services making up the Internet of Things perceive available resources and utilize them. ...
Conference Paper
Edge computing has been recently introduced as an intermediary between Internet of Things (loT) deployments and the cloud, providing data or control facilities to participating loT devices. This includes actively supporting loT resource discovery, something particularly pertinent when building large-scale, distributed and heterogeneous loT systems. Moreover, edge devices supporting resource discovery are required to meet the stringent requirements prevalent in loT systems including high availability, low-latency, and privacy. To this end, we present a resource discovery platform for loT resources situated at the edge of the network. Our approach aims at providing a seamless discovery process that is able to (i) extend the covered area by deploying additional edge nodes and (ii) assist in the development of new loT applications that target already available resources. Within our proposed platform, devices located in a certain proximity connect and form an edge-to-edge network that we call an edge neighborhood-our edge-to-edge metadata replication platform enables participating devices to discover available resources. Our solution is characterized by absence of centralization, as edge nodes exchange metadata about available resources within their scope in a peer-to-peer manner.
... A search engine-based resource discovery architecture is presented in [6]. The architecture consists of three layers: proxy, discovery, and service enablement. ...
... The web-based service discovery solutions are built with a high-performance computer to provide searching services, such as web searching engines on the Internet. However, traditional webbased searching solutions cannot provide the service in the same way for the IoT network because of the heterogeneity and constrained network requirements [29]. In the IoT network, the discovery service provider shall support resource discovery regardless of the communication protocols and technologies used by IoT clients [30]. ...
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... Based on the knowledge, the corresponding cyber object is generated by cyber-physical mapping model [22]. In the latter case, the corresponding cyber objects are searched and discovered according to the application requirements [23]. By computing and analyzing, the applications can manipulate the corresponding physical objects to act on physical space. ...
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... Resources may include information about available sensors and their types, available computing and storage resources, middlewares, and networking components available within the specific IoT ecosystem. Various resource discovery mechanisms in IoT include-distributed discovery services, centralized discovery, constrained application protocol-based discovery, semantic discovery, and others such as object name service and domain name service (Datta, Da Costa, & Bonnet, 2015). As resource discovery can be employed to optimize the energy consumption of -ND = node discovery; SD = service discovery; DD = data discovery; RD = resource discovery; ID = information discovery; IoT = Internet of Things. ...
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Chapter
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Chapter
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Chapter
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Internet of Things (IoT) was faced with some difficulties which contained mass data management, various standards of object identification, data fusion of multiple sources, business data management and information service providing. In China, some safety monitoring systems of agricultural product always adopt centralized system architecture in which the data is stored concentratively. These systems could not be connected with or accessed by each other. This paper proposed an information system of agriculture Internet of Things based on distributed architecture. A distributed information service system based on IoT-Information Service, Object Naming Service, Discovery Service is designed to provide public information service including of capturing, standardizing, managing and querying of massive business data of agriculture production. A coding scheme for agricultural product, business location and logistic unit is provided for data identification. A business event model of agriculture IoT is presented for business data management. The whole system realizes the tracking and tracing of agricultural products, and quality monitoring of agriculture production. The implementation of this information service system is introduced.
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This paper proposes a device and capability discovery protocol with integrated Universal Plug and Play (UPnP) and Object Naming Service (ONS). The protocol automatically establishes a list of available devices - sensors, actuators and electronic apparatus - in our home. Since each device is identified with a globally unique Electronic Product Code (EPC) in the protocol, the capability of discovered device can be obtained through ONS without implementing a complex capability description exchange protocol in the device. The up-to-dated list of all the available devices facilitates the compositions of smart home applications. This paper overviews the device and capability discovery protocol. Illustrative smart home applications in our campus enabled by the proposed protocol are also reported.
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In recent years, the Internet of Things (IoT) has become a hot research issue and is changing the way how people live and work. IoT has a lot of benefits and meanwhile, it also brings about great challenges to the search engine community. In this paper, we analyze the challenges in the IoT search engine technology and propose a """"Hybrid Search Engine Framework for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions"""" (""""IoT-SVK Search Engine"""" for short). The experimental results show that the IoT-SVK search engine has satisfactory performances in supporting multi-modal retrieval conditions, and provides a good solution for real-time retrieval of massive sensor sampling data in the Internet of Things.
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This paper analyzes the needs of service discovery for Internet of Things (IOT) systems, and raises a service matching algorithm based on ontology. The proposed algorithm combines the characteristics of semantic similarity and semantic relativity, which can better complete the business of the services discovery capabilities of IOT. In addition, the algorithm has good scalability, and it can be applied to different fields only need to replace the domain ontology.
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Internet of Things (IoT) enables a homogeneous and seamless machine to machine (M2M) between any Internet-enabled devices in the real world. IoT provides global communications, access to services and information for the development of Smart Cities, environmental monitoring, bus tracking and parking. For this purpose, IoT requires scalability, extensibility, and integration of emerging resources in order to reach a suitable ecosystem for data acquisition and interaction with the citizens. This work presents a way to interact with the IoT through a homogeneous and suitable mechanism for the global resource discovery of devices and sensors on different scenarios. For discovery purpose, a infrastructure called "digcovery" is defined for maximizing efficiency and sustainability of deployments offering the framework to allow users to register/include their own sensors into a common infrastructure, and access/discover the available resources through a mobile phone. This presents how to use the smartphone capabilities, in terms of identification, geo-location and context-awareness, to access and interact with the available resources that are surrounding us.
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This paper proposes a semantic enhanced service proxy framework for internet-of-things cloud. The framework exposes IoT cloud's smart objects as services by virtue of service orientation and virtualization. The framework uses an adapter oriented approach to address the issue of connectivity with different types of smart objects. We employ a query based service re-route mechanism to decouple service provider and service consumer. We propose micro-formats based service description template for associating smart object location with its service end-point. As a step toward enhancing smart objects service publication and discovery, we adopt a service advertisement approach within the IoT cloud perimeter that automates service publication and discovery process. Our proof-of-concept prototype implementation shows that the existing technology enablers are capable of realizing the service oriented IoT vision, which does not only plug smart objects into the internet but also link the information resided in smart objects into the fabric of the web.
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In ubiquitous-city, a middleware is essential since various kinds of unified services are required in many different applications and flexibility of service is required. It should dynamically discover and invoke services to exploit the flexibility and the power of the middleware and the service discovery is very important in the middleware. In this paper, we present a mechanism and elements of semantic service discovery which have been implemented and used in a u-city middleware which is the ever first research in the world. We evaluated the performance of the semantic service discovery in a u-city middleware and present the performance result in this paper. It is also the ever first research in the world.
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We present DiscoWoT, a semantic discovery service for Web-enabled smart things. The service is based on the application of multiple Discovery Strategies to a Web resource's representation, where arbitrary users can create and update strategies at runtime using DiscoWoT's RESTful interface. Its goal is to provide a future-proof mechanism for enabling both, human users and machines, to semantically discover functionality provided by Web-enabled devices. Ultimately, it aims to allow for the facilitated discovery, selection, and utilization of smart things. DiscoWoT incorporates a transparent mechanism for deferring resource discovery to external handlers and can thus interact with other services within discovery service federations. It may be accessed by arbitrary users for ad hoc discovery of functionality offered by Web resources or incorporated into infrastructures for Web-enabled smart things.
Constrained Application Protocol (CoAP). RFC 7252 (Proposed Standard)
  • Z Shelby
  • K Hartke
  • C Bormann