Jian Ye

PCSM: A Context Sharing Model in Peer-to-Peer Ubiquitous Computing Environment

This paper proposes the peer-to-peer context sharing model (PCSM) which is a ubiquitous computing oriented peer-to-peer context sharing model. Owing to the distribution and limit of resources of the mobile ubiquitous network, the PCSM model constructs a context management framework based on the mechanism of registration-query. Through designing the broadcast messages for available terminals discovery and unicast messages for remote registration, the model implements remote registration of Context Database Agents, and builds up an architecture for sharing and fusing of contexts in a peer-to-peer ubiquitous computing environment to satisfy the requirements of sentient computing applications. In contrast with some current context management systems, the PCSM model partly solves the inherent problem of high cost for communication and storage redundancy through the mechanism of optimization. Besides, the PCSM model enables computing nodes to share contexts, on which the decisions depend. Based on the PCSM model, a prototype of instant messenger with ubiquitous computing ability is provided in the end.

A Service Discovery Framework for Ubiquitous Computing

This paper presents a novel service discovery framework for ubiquitous computing called Ubiquitous Computing Service Discovery Framework (UCSDF). UCSDF offers a more flexible and scalable architecture which can combine the local services with remote services. That characteristic makes UCSDF different from many other service discovery frameworks and more adaptive to ubiquitous computing environments.

A User-centric Service Framework for Pervasive Computing

In pervasive computing environments, users can interact with a wide range of services, but which do not include legacy application services such as interactive desktop applications. How to use legacy service as a kind of transparent service mechanism in a pervasive computing environment is an important problem to solve during the transition from personal computing to pervasive computing. This paper presents a user-centric service framework that coordinates application services over network and heterogeneous networked devices nearby users to form a users virtual computing environment. It also provides legacy support without modification to existing softwares based on virtual desktop and virtual device

A Fuzzy Petri Net Model towards Context-Awareness Based Personalized Recommendation

In a personalized recommender system of a ubiquitous computing environment, the decision on recommendation depends on some uncertain factors. Fuzzy system has an ability of solving the reasoning uncertainty, and gets widely used in the context awareness based personalized recommender system. In this paper, we present a fuzzy reasoning model based on the Fuzzy Petri Net. The model considers the requirements of task fulfillment, users preferences and QoS of the system. With difference from those existing recommender systems, we focus on the formalized modeling of fuzzy reasoning of the personalized recommendation. Through formalization of fuzzy reasoning, we propose an approach to construct a rule-based reasoning system. The feasibility of the proposed approach is validated by an example of the personalized recommender engine.

A User-Centric Pervasive Computing Services Model for Medical and Health-care

The hospital and the health-care center of a community, as persons life-care and health-care settings, need to provide more and better services for patients or residents. Establishing Electronic Medical Record (EMR) system is the necessity in hospital, and providing pervasive services is the further trend. Based on the EMR database, this paper presents a user-centric pervasive computing service model (PCSM) that coordinates application services over network and heterogeneous platforms nearby users to form a service environment for medical and health-care. It also provides doctors with legacy information service support without modification to exiting information system based on the PCSM.

Ubiquitous Computing-Oriented Distributed Fuzzy Reasoning Petri Net Modeling and Simulation

In a ubiquitous computing environment, contexts are initially got and stored on those nodes scattered over the environment. However, the traditional reasoning about contexts applied a centralized approach which aggravated the load of reasoning server and cost for communication of context. As an important approach for context reasoning, the rule-based reasoning can be easily decomposed of independent propositions. Therefore, the rule-based context reasoning can be decomposed and distributed over those nodes of the ubiquitous environment to decrease the computing load of reasoning server. In this paper, we propose a distributed fuzzy reasoning Petri net model (dFRPN) towards the decomposition of distributed fuzzy reasoning. dFRPN model is able to formalize the distribution of fuzzy reasoning over every node of the whole environment. dFRPN model is characterized as a hierarchical structure to make a description of reasoning on nodes more clear. Considering the limited capabilities of some mobile nodes such as PDA and smart phone, we add the special migrating transition to define the load detection and corresponding actions. At the end of the paper, the feasibility of dFRPN model is validated through a case of context-awareness based personalized recommendation system.

A Hierarchical Service Discovery Framework for Ubiquitous Computing

This paper presents a novel service discovery framework for ubiquitous computing called hierarchical ubiquitous computing service discovery framework (HUCSDF). HUCSDF offers a more flexible and scalable architecture which can combine the local services with remote services. Based on the novel architecture, HUCSDF possesses some useful characteristics such as supporting migration of users personal computing environment, group collaboration, interoperation with other kind of services and integration of context-aware information. These characteristics make HUCSDF different from many other service discovery frameworks and more adaptive to ubiquitous computing environments.

A feedback Adaptive fuzzy Petri net model for context reasoning

As an improved model of fuzzy Petri net, adaptive Petri net (AFPN) has got the learning ability from neural network. But AFPN still depends on offline training data, while actual environment is so complex, vague and changeful that AFPN seems slightly inadequate. This paper proposes an approach based on fuzzy logic and feedback theory to improve AFPN. The approach introduces feedback mechanisms into AFPN to enhance the adaptive ability in dynamic environment. In addition, the approach embeds fuzzy logic theory into the representation of context information. Thus, the uncertain context information management is more conformable with persons sense. The approach is also able to learn the parameters of membership function by using the back propagation algorithm of neural network. At the end of the paper, an experiment is designed to demonstrate that the approach is feasible and effective in fuzzy reasoning.

DFre: A Distributed Fuzzy Reasoning Engine for Personalization Recommendation

In a pervasive computing environment, the personalized recommender system incorporates contexts into recommendation and becomes a multiple dimensional decision expert system. In this paper, we present DFre, a distributed fuzzy reasoning engine for personalization recommendation. With difference from those existing rule-based systems, the DFre puts an emphasis on the distribution of the recommendation in the pervasive computing environment. With the distributed data management framework, the DFre has an ability of getting those distributed primitive data and fuzzy rules, which makes the distributed reasoning become true. Finally, the feasibility of DFre in the user-centric recommender system is validated through the Flowing Desktop which is an example of the personalized recommender engine.

Distributed Reasoning Modeling and Algorithm Design towards a Pervasive Computing Environment

Considering the fuzzy reasoning can be distributed over every node of a pervasive computing environment, we propose a fuzzy reasoning Petri net model with load detection (LD-FRPN) towards the decomposition of distributed fuzzy reasoning in this paper. The LD-FRPN model applies a hierarchical structure to make a description of reasoning on nodes more clear. We divide transitions of LD-FRPN into three classes to describe the reasoning, migrating and integrating of contexts respectively. With these transitions, the distributed reasoning of the pervasive computing environment will be specified.