Research On Key Technologies And System Of Service Delivery For IoT

With the rapid development of Internet of Things technology, a huge business value network is formed. This resuts would encourage multiple service providers to develop services for IoT. Multiple services providers will require the development of a suitable, scalable service delivery platform, which enables the fast and cost-effective creation of new IoT services. However, the network capacity of IoT has some characteristics of errpor-prone, unreliable, limited energy, and constrained resources, so how to deliver services over IoT becomes a big challenge in service computing. The research topic discussed in this paper is about IoT-based service delivery, which includes the service delivery framework model, IoT capabilities abstract framework and related algorithms, distributed service description and dynamic combination based on life cycle model and its algorithm, and trustful service exposure and negoziation mechanism and its algorithm for multiple service providers. Research results and innovation points are summarized as below:1) Based on TMF SDF, SensorLogic SDP, and L. Atzori IoT middleware, a IoT-based service delivery framework model is proposed for chaos of the IoT service environment, service development of "chimney", and lack of sustainability. The first, IoT-based service delivery environment is divided into service providers, service consumers, and IoT infrastructure providers by referring to TMF SDF. Then, the model realizes IoT resource share using dynamic coordination and abstraction technology. Lastly, complex service is quickly created by service dynamic composition. Compared with TMF SDF, SensorLogic SDP, and L.Atzori IoT middleware, the model effectively solves problem of IoT services stability, service dynamic composition, and trustful service exposure.2) Refered to EU FP7SENSEI, G. Fortina object abstraction and dynamic coordination, this paper proposes a novel IoT capabilities abstraction framework with dynamic collaboration, self-organization and fault tolerance, and its related algorithm. For errpor-prone, unreliable, limited energy, and constrained resources of node communication. This framework firstly abstracts Smart Object in the Internet of things (CHN node) into PRA agent for the unstructured data real-time and complexit. This has intelligence formalization, self-management ability, and autonomic computing ability for each PRA agent. Then, a RCT-based coordinate algorithm is proposed for each PRA limited computing power. Lastly, a TFA and Load-based self-envalution algorithm is proposed for each PRA internal structure dynamic variable. Compared with EU FP7SENSEI, G. Fortina object abstraction and dynamic coordination, the model and some algorithm not only maintain IoT services stability, and reliability, but also support the service dynamic composition.3) According to the E.G. da Silva dynamic service composition, and S.C.Geyik robust dynamic sensor service composition, this paper proposes a life cycle-based distributed service description and dynamic composition model and its algorithm for a large heterogeneity, unstructured data-driver service, and decentralization service compostion of atomic sensor service. Each PRA is abstracted into semantic service by metadata in sensor service description, which enhances robustness of service. According to service life-cycle, the dynamic sensor service composition is divided into four phases:service planning, discovery, selection and execution. In the planning phase, it has proposed generation algorithm of dynamic service composition for PlanningDomain, UserRequirement and Workflow. In the discovery phase, it proposes based on Input/Output semantic matching service discovery algorithm. In the selection phase, it has proposed based on Fuzzy Logic and PSO service selection algorithm. In the execution phase, dynamic service composition script is deployed on service broker, which service composition metadata is dynamically mapped on IoT network capabilities. Compared with E.G. da Silva dynamic service composition, and S.C.Geyik robust dynamic sensor service composition, the model and some algorithm effectively solves problem of unstructured data-driver service dynamic composition.4) Referencing S. Alam service exposure of IoT services and T. Finin service exposure on SDP, This paper proposes the trustful service exposure and negotiation mechanism for multiple service providers. The mechanism firstly assignes virtual ID card to each service provider by trust-based access control. Then, the mutual trust is established by the direct or indirect trust reasoning, and the trustful service exposure mechnism is established by the trustful service level agreement negotiation. Finally through comprehensive SLA evaluator, service capabilities are assigned to service provider. Compared with S. Alam service exposure of IoT services and T. Finin service exposure on SDP, service delivery capabilities is exposed for multiple service providers by the trustful service exposure and negotiation mechanism.