Service Discovery System Research Articles

Research and Application of the Internet of Things Service Platform Based on Semantic Network

In order to study the Internet of Things service platform based on semantic Network, a service-oriented clustering labeling method is proposed, firstly, a semantic Web service similarity computing method is proposed to solve the shortcomings of the existing methods. This method describes the designed semantic Web service annotation clustering algorithm based on AP algorithm. The distance matrix and related parameters of the algorithm are calculated and assigned according to the results of similarity calculation. The correctness of preference parameter selection will be compared and verified in the service discovery system. The greater the value of damping coefficient, the more iterations, and the slower the convergence rate. However, when the value of damping coefficient is 0.7, the number of iterations is moderate and the convergence rate is the best, which proves that this method has a better effect on service function matching.

Trustable service discovery for highly dynamic decentralized workflows

The quantity and capabilities of smart devices and sensors deployed as part of the Internet of Things (IoT) and accessible via remote microservices is set to rise dramatically as the provision of interactive data streaming increases. This introduces opportunities to rapidly construct new applications by interconnecting these microservices in different workflow configurations. The challenge is to discover the required microservices, including those from trusted partners and the wider community, whilst being able to operate robustly under diverse networking conditions. This paper outlines a workflow approach that provides decentralized discovery and orchestration of verifiably trustable services in support of multi-party operations. The approach is based on adoption of patterns from self-sovereign identity research, notably Verifiable Credentials, to share information amongst peers based on attestations of service descriptions and prior service usage in a privacy preserving and secure manner. This provides a dynamic, trust-based framework for ratifying and evaluating the qualities of different services. Collating these new service descriptions and integrating with existing decentralized workflow research based on vector symbolic architecture (VSA) provides an enhanced semantic search space for efficient and trusted service discovery that is necessary to support a diverse range of emerging edge-computing environments. An architecture for a dynamic decentralized service discovery system, is designed, and described through application to a scenario which uses trusted peers’ reported experiences of an anomaly detection service to determine service selection.

Handfan: A flexible peer-to-peer service discovery system for internet of things applications

The Internet of Things (IoT) can be defined as an extensive network of interconnected devices that enables any physical object to be part of the worldwide network. The opportunity of everything being interconnected to the internet leads to many other challenges, such as many devices, the exponentially generated data, and the limited resources capacity of such devices (in terms of storage capacity, processing, energy, and accessibility). Decentralized systems and more particularly Peer-to-Peer (P2P) systems can meet the requirements of IoT applications. Peer-to-Peer DHT-Based approaches enable an effective search within a logarithmic cost. However, two issues need to be addressed to suit efficiently resource-constrained IoT systems. The first technical gap is that DHT-Based approaches do not handle network scalability and resources allocation, so they assume both nodes and keys must be in the same space, therefore, they are exclusively determined by the output of the hashing function. The second gap is that service discovery in such approaches is independent of the node’s resources capacity, which makes it ineffective and unsuitable for resource-constrained IoT systems. To cope with such limitations, our approach fundamentally addresses the previous technical gaps in existing DHT-based approaches by the following: Firstly, it deals with the first issue by adopting a novel mapping mechanism for both keys and identifiers based on geometric angles, the same mechanism is applied for nodes auto-configuration. Secondly, it introduces a customized routing mechanism that factors in nodes' processing capacity. We consider the number of hops, routing table size, configuration overhead, and load distribution as performance metrics. The proposed protocol's implementation and simulation with multiple experimentations confirm our approach's out-performance and effectiveness against competing IoT application approaches.

A New Approach Customizable Distributed Network Service Discovery System

Computer systems and applications on the internet provide services to outsiders and, at the same time, the vulnerabilities may be exploited by attackers and leak some sensitive private information. To collect and monitor the service information provided by the network environment such as IoT (Internet of Things), vehicular networks, cloud computing, and cloud storage, it is particularly important that a system can provide faster service discovery for discovering and identifying specific network services. The current service discovery systems mainly use port scanning technology, including Nmap, Zmap, and Masscan. However, these technologies hard code the service features and only support common services so that cannot cope with real‐time updates and changing network services. To solve the above problems, this paper proposed a customizable distributed network service discovery system based on stateless scanning technology of Masscan and proposed a customizable interactive pattern set syntax. The system used random destination address technologies to scan for Ipv4 address allocation and used a distributed deployment scheme. Experimental results show that the system has high scanning speed and has high adaptability to new services and special services.

An ontology-based cloud infrastructure service discovery and selection system

In recent years, due to global economic downfall, many of the organisations have resorted to downsizing their Information Technology (IT) expenses by adopting innovative computing models like cloud computing, which allows business houses to reduce their fixed IT costs by promising a greener, scalable, cost-effective alternative to utilise the IT resources. A growing number of pay-per-use cloud services are now available on the web in the form of Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). With the increase in the number of services, there has also been an increase in demand and adoption of cloud services making cloud service identification and discovery a challenging task. This is due to varied service, descriptions, non-standardised naming conventions, heterogeneity in type and features of cloud services. Thus, selecting an appropriate cloud service according to consumer requirements is a daunting task, especially for applications that use a composition of different cloud services. In this paper, we have designed an ontology-based cloud infrastructure service discovery and selection system that defines functional and non-functional concepts, attributes and relations of infrastructure services. We have shown how the system enables one to discover appropriate services optimally as requested by consumers.

An ontology-based cloud infrastructure service discovery and selection system

In recent years, due to global economic downfall, many of the organisations have resorted to downsizing their Information Technology (IT) expenses by adopting innovative computing models like cloud computing, which allows business houses to reduce their fixed IT costs by promising a greener, scalable, cost-effective alternative to utilise the IT resources. A growing number of pay-per-use cloud services are now available on the web in the form of Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). With the increase in the number of services, there has also been an increase in demand and adoption of cloud services making cloud service identification and discovery a challenging task. This is due to varied service, descriptions, non-standardised naming conventions, heterogeneity in type and features of cloud services. Thus, selecting an appropriate cloud service according to consumer requirements is a daunting task, especially for applications that use a composition of different cloud services. In this paper, we have designed an ontology-based cloud infrastructure service discovery and selection system that defines functional and non-functional concepts, attributes and relations of infrastructure services. We have shown how the system enables one to discover appropriate services optimally as requested by consumers.

Study on the Design of Service Discovery System Based on IoT Device Extended Information

Study on the Design of Service Discovery System Based on IoT Device Extended Information

Numerical Similarity Algorithms for Cloud Service Discovery and Selection System

Numerical Similarity Algorithms for Cloud Service Discovery and Selection System

A study on web services discovery system based on the internetof things user information

IoT is a technology that provides service and shares information through connecting real objects through wireless and wired networks. Various services and information divided through IoT based environment device cooperation not only increases the quality of life in individuals but also has become an important issue in the development of various industrial fields. IoT service development appropriate for applicable industries and personal requirements is required. This study suggests a system that can provide a web service list appropriate for the user when selecting service by using a concept of applying and collecting various forms of information created in IoT environment while using web service. The suggested method applies user IoT information with traditional web service search to include the advantages of the existing search methods and services that the user needs. Thus, user friendly service selection that can increase the efficiency of service use is created compared with the traditional provider centered service provision environment. The study defines usable service properties and derives IoT service components. Based on this, we suggest an IoT information based web service search system and algorithm. Diverse user information models collected and created through IoT collector are provided with user requirements during service selection and based on user IoT information, useful service for individual user environment can be discovered and provided. The suggested method utilizes information models created through IoT device elements to suggest a system model that can be utilized for various requirements and rapidly changing services.

A Decentralized Trustworthy Context and QoS-Aware Service Discovery Framework for the Internet of Things

The Internet of Things envisions a multitude of heterogeneous objects and interactions with physical environments. It has provided a promising opportunity to build powerful services and applications by leveraging the growing ubiquity of smart objects connected to the Internet. In this environment, it is challenging to locate desirable services due to the considerable diversity, large scale, dynamic behavior, and geographical distribution of the services provided by physical objects. In this paper, we propose a decentralized semantics-based service discovery framework, which can effectively locate trustworthy services based on requester’s quality of service demands and changing context requirements. The proposed service discovery system is built upon fully distributed peer-to-peer architectures and includes two discovery approaches which are scalable, robust, and trust assured. Moreover, an efficient trust propagation mechanism is proposed, which seamlessly integrates with the proposed service discovery system without adding additional infrastructure overhead. Comprehensive simulation studies have demonstrated the effectiveness of the proposed framework.

Introducing our Publications and Editorial Board

Joanna Ball is Head of Library Content Delivery and Digital Strategy at the University of Sussex, where she provides strategic direction for the teams who acquire, license and deliver the Library’s print and digital resources. She is also responsible for technical innovation and the development of library systems, including the library services platform, discovery system and institutional repository. Additionally, she has driven the development of a research data management (RDM) policy and solution for the University.

Analytical study of a service discovery system based on an LTE-A D2D implementation

This work adapts the paradigm of Cloud Computing over the framework of Device-to-Device (D2D) proximity-based communications in order to offer proximity services to LTE network subscribers, and offload major traffic from the core network. Our proposed work introduces a platform in which mobile devices can offer network services to other nearby devices, and thus act as service end points, or mobile cloudlets. Devices seeking particular services can discover these providers and communicate with them directly, but with the help of the LTE network whose role is limited to assisting in the service provider discovery process. D2D can introduce several positive aspects within any community, through (1) helping tourism by making it seamless to obtain needed services; (2) improving social ties among the society members; and (3) helping the economy through creating a more conducive environment for thriving personal-level businesses. From an implementation point of view, our solution is in line with the 3GPP standards, utilizes the 3GPP-proposed network elements designated for offering proximity based services, and introduces no changes to the rest of the LTE system. Our experimental results proved the effectiveness of our system in helping mobile users discover needed services offered by nearby providers, and therefore communicate directly in a peer-to-peer fashion.

Semantic web service discovery system for road traffic information services

We describe a multi-agent platform for a traveller information system, allowing travellers to find the road traffic information web service (WSs) that best fits their requirements. After studying existing proposals for discovery of semantic WS, we implemented a hybrid matching algorithm, which is described in detail here. Semantic WS profiles are annotated semantically as an OWL-S and also the traveller request is represented as a OWL-S profile. The algorithm assigns different weights and measures to each advertisedWS profile parameter, depending on their relevance, type and nature. To do this we have extended Paolucci’s Algorithm and adapted it to our scenario. We have added new similarity measures, in particular, the use of the ‘sibling’ relationship, to improve the recall, allowing relevant services to be discovered by the users yet not retrieved by other algorithms. Although we have increased the similarity concept relations, we have improved the run-time using a pre-process filter step that reduces the set of potentially useful WS. This improves the scalability of the semantic matching algorithm.

Ontology-based Cloud Services Representation

The advancement of cloud computing has enabled service providers to provide diversity of cloud services to users with different attributes at a range of costs. Finding the suitable service from the increasing numbers of cloud services that satisfy the user requirements such as performance, cost and security has become a big challenge. The variety on services description none uniformed naming conventions and the heterogeneous types and features of cloud services led to make the cloud service discovery a hard problem. Therefore, an intelligent service discovery system is necessary for searching and retrieving appropriate services accurately and quickly. Many studies have been conducted to discover the cloud services using different techniques, such as ontology model and agents technology. The existing ontology for cloud services does not cover the cloud concepts and it is intended to be used for specific tasks only. This study represents the cloud concepts in a comprehensive way that can be used for cloud services discovery or cloud computing management.

Combination of self-organization mechanisms to enhance service discovery in open systems

Decentralized systems have emerged as an alternative to centralized approaches for dealing with dynamic requirements in new business models. These systems should provide mechanisms that contribute to flexibility and facilitate adaptation to changes in the environment. In this paper, we present two self-organization mechanisms for a decentralized service discovery system in order to improve its performance. These mechanisms are based on local actions of agents that only consider local information about queries they forward during the discovery process. The self-organization actions are chosen by each agent individually when the agent considers them to be appropriate. The actions are: remaining in the system, leaving the system, cloning, and changing structural relations with other agents. We have evaluated each self-organization mechanism separately but also the combination of the two as the environmental conditions in the service demand change. The results show that the proposed self-organization mechanisms considerably improve the performance of the service discovery system.

An ontology update mechanism in IaaS service discovery system

Purpose – Hybrid cloud computing is considered a viable and cost-effective approach to satisfy the inability of a private cloud to meet the user requirements. The information status of the selected public cloud service may change at runtime which should be reflected at the broker server database. This research illustrates a mechanism to assist the IaaS discovery system to assess the status change of the selected public cloud service and to update the broker server database. The paper aims to discuss these issues. Design/methodology/approach – A prototype was developed with the broker server as the main component in the service discovery system containing the status information of the selected public cloud service. The merge-ontology and patch-update methods were proposed, the processing cost details of each were measured, and the methods were evaluated. Findings – Experimental results showed that in the merge update, the merging process incurred much longer time than its required communication, contributing to long overall time. Relatively, the patch update method incurred much less time than its counterpart. Research limitations/implications – The proposed mechanism is experimental with some ideal assumptions, and so further work in real conditions is needed for its improvement. Originality/value – This research is believed to be the first proposal to investigate ontology merge/patch methods to support ontology update in the broker server database of a hybrid cloud and will serve as a reference to researchers in the field.

An Efficient and Optimized Service Discovery Methodology for QoS Aware Service Oriented Business Intelligence

The current and future business processes would be service oriented. The required service is selected using discovery process. The discovery process uses in-memory parse tree construction or callback based document parsing. Existing service discovery systems stores both functional attributed and QoS attributed in tree data structures and they are time consuming, space consuming, requires frequent parse tree construction in various location, difficult to replicate and distribute parse tree and replicated parse trees are inconsistent. This paper proposes an efficient methodology to improve the performance of in memory parse tree discovery process over extended web service architecture. The system uses two parallel discovery algorithms, Synchronous and Asynchronous algorithms for service discovery, both algorithms uses the tree and indexed data structure for service discovery and the later also uses a bitmap table to verify functional requirements. The services are selected and ranked based on user request using Coefficient of Variance. The proposed algorithms are detailed in this paper. The experimental results are conducted on benchmark dataset are discussed. The proposed system ensures availability, consistency, effective space utilization, eases replication and distribution and improves response time for service discovery by 30%.

Research on Web Information Retrieval based on Vector Space Model

Existing methods and technologies for Web services discovery mainly consist of two models: service matching based on grammar and based on semantics. With keywords service matching method, we introduce text information retrieval technology with vectors and concept lattice theory. Then a web service discovery algorithm using eigenvectors is put forward. It orders the Web services by correlation among the services in Web service subset. The services which have bigger correlation will get anterior places. According to this algorithm a Web service discovery system based on eigenvectors is designed. We give description to key modules of the system. At last the improved algorithm is compared to methods based on full-text retrieval and pure similarity retrieval. The results show it has better performance in accuracy and response.

A Study on Knowledge Discovery of Relevant Web Services with Semantic and Syntactic approaches

Web mining is the application of data mining techniques to discover patterns from the Web. Web services defines set of standards like WSDL(Web Service Description Language), SOAP(Simple Object Access Protocol) and UDDI(Universal Description Discovery and Integration) to support service description, discovery and invocation in a uniform interchangeable format between heterogeneous applications. Due to huge number of Web services and short content of WSDL description, the identification of correct Web services becomes a time consuming process and retrieves a vast amount of irrelevant Web services. This emerges the need for the efficient Web service mining framework for Web service discovery. Discovery involves matching, assessment and selection. Various complex relationships may provide incompatibility in delivering and identifying efficient Web services. As a result the web service requester did not attain the exact useful services. A research has emerged to develop method to improve the accuracy of Web service discovery to match the best services. In the discovery of Web services there are two approaches are available namely Semantic based approach and Syntactic based approach. Semantic based approach gives high accuracy than Syntactic approach but it takes high processing time. Syntactic based approach has high flexibility. Thus, this paper presents a survey of semantic based and syntactic based approaches of Web service discovery system and it proposed a novel approach which has better accuracy and good flexibility than existing one. Finally, it compares the existing approaches in web service discovery.

MANET에서 서비스 발견 및 전달을 위한 오버레이 네트워크 기반의 T-Chord 링 시스템

MANET의 기반 연구 기술들의 결과를 토대로 현실 속에서 MANET을 활용하기 위한 응용으로써 다양한 서비스 발견 및 전달 기법들이 제안되고 있다. 본 논문에서는 MANET에서의 메시지 오버헤드의 최소화와 안정적인 서비스 발견 및 네트워크의 확장성을 보장하기 위한 T-Chord(Trustworthy-based Chord) 링 시스템을 제안한다. T-Chord 링 시스템은 모바일 환경에서 이동 노드들이 제공하는 서비스들을 효율적으로 관리하기 위해 P2P 오버레이 네트워크 기법을 이용한 서비스 발견 시스템으로, MANET에서 이동 노드들은 이동성을 갖으며 서비스 요청 노드, 서비스 제공 노드 그리고 서비스 전달 노드로써 동작하기 위해 이동 노드들의 Trustworthy 평가와 분산된 서비스 정보의 수집, P2P 오버레이 네트워크의 구성을 통한 O(Log N) 성능을 제공하는 Chord 알고리즘 모듈로 내부 시스템을 구성하였다. 시스템의 성능 평가는 NS2 시뮬레이터를 이용하여BR기존의 서비스 발견 기법들과 서비스 발견 메시지 오버헤드, 서비스 발견 및 전달의 효율성, 네트워크의 확장성 측면에서 성능을 비교 평가하고 분석함으로써 MANET에서 효과적인 서비스 발견 및 전달의 우수함을 입증하였다.