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RPL (Routing Protocol for Low-power and lossy networks) is a special? routing protocol designed for optimizing 6LoWPAN (IPv6 over Lower power Wireless Personal Area Network) operations. RPL suffers from resource constraints on battery, processor, memory and bandwidth, which make RPL more vulnerable to several threats than normal routing protocol. It is necessary to design a lightweight method to protect...
Routing Protocol for Low-Power and Lossy Networks (RPL) is the Internet Engineering Task Force (IETF) standard for IPv6 routing in Low-power and Lossy Networks (LLNs). By using the Objective Function (OF) and a collection of routing metrics, it can build a Destination Oriented Directed Acyclic Graph (DODAG). There are two kinds of OFs specified by the IETF, Objective Function Zero (OF0) and Minimum...
Location-based services are widely used in the Internet services. The method of location cloaking is used to effectively protect the user's location privacy. The current cloaking algorithm does not take into account the regional characteristics, such as population density, popularity level and so on, based on which an attacker can often infer user's exact location from their cloaking area. In this...
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...
This paper proposes the CaPeR which is the context-awareness based architecture for personalized recommendation. The CaPeR provides the personalized recommender engine and the peer-to-peer context management framework. With a hybrid approach, the personalized recommender engine combines those contexts into the decisions on recommendations to get more comprehensive recommendation effectiveness. Owing...
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 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...
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 user's personal...
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.
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...
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