An Integrated and Layered Architecture for Location-Aware Computing

This paper gives an overall introduction to the basic concept of LAC(location-aware computing) and its development status, puts forward an integrated location-aware computing architecture which is useful for designing the reasonable logical model of LBS(location-based service). Finally, a brief introduction is conducted on a LAC experimental prototype, which acts as a mobile urban tourism assistant.

Pervasive Computing Location-aware Model Based on Ontology

In order to integrate heterogeneous location-aware systems into pervasive computing environment,a novel pervasive computing location-aware model based on ontology is presented.A location-aware model ontology(LMO)is constructed.The location-aware model has the capabilities of sharing knowledge,reasoning and adjusting the usage policies of services dynamically through a unified semantic location manner.At last,the work process of our proposed location-aware model is explained by an application scenario.

A User Proprietary Obfuscate System for Positions Sharing in Location-Aware Social Networks

A user’s trajectory can be maliciously monitored by adversaries when they share the positions in location-aware social networking applications which require users to update their own locations continuously. An adversary infers user’s locations from the trajectories, and gleans user’s private information through them via location-aware social networking applications and public available geographic data. In this paper, we propose a user proprietary obfuscate system to suit situations for position sharing and location privacy preserving in location-aware social network. Users transform the public available geographic data into personal obfuscate region maps with pre-defined profile to prevent the location leaking in stationary status. Our obfuscation with size restricted regions method tunes user’s transformed locations fitting into natural movement and prevents unreasonable snapshot locations been recorded in the trajectory.

An IoT-Aware System for Managing Patients’ Waiting Time Using Bluetooth Low-Energy Technology

It is a common observation that whenever patients arrives at the front desk of a hospital,outpatient clinic,or other health-associated centers,they have to first queue up in a line and wait to fill in their registration form to get admitted.The long waiting time without any status updates is the most common complaint,concerning health officials.In this paper,UrNext,a location-aware mobile-based solution using Bluetooth low-energy(BLE)technology is presented to solve the problem.Recently,a technology-oriented method,the Internet of Things(IoT),has been gaining popularity in helping to solve some of the healthcare sector’s problems.The implementation of this solution could be illustrated through a simple example of when a patient arrives at a clinic for a consultation.Instead of having to wait in long lines,that patient will be greeted automatically,receive a push notification of an admittance along with an estimated waiting time for a consultation session.This will not only provide the patients with a sense of freedom but would also reduce the uncertainty levels that are generally observed,thus saving both time and money.This work aims to improve the clinics’quality of services,organize queues and minimize waiting times,leading to patients’comfort while reducing the burden on nurses and receptionists.The results demonstrate that the presented system is successful in its performance and helps achieves a plea-sant and conducive clinic visitation process with higher productivity.

QoS prediction algorithm used in location-aware hybrid Web service

Quality-of-Service （QoS） describes the non-functional characteristics of Web services. As such, the QoS is a critical parameter in service selection, composition and fault tolerance, and must be accurately determined by some type of QoS prediction method. However, with the dramatic increase in the number of Web services, the prediction failure caused by data sparseness has become a critical challenge. A new ＇hybrid user-location-aware prediction based on weighted Adamic-Adar （WAA）＇ （HUWAA） was proposed. The implicit neighbor search was optimized by incorporating location factors. Meanwhile, the ability of the improved algorithms to solve the data sparsity problem was validated in experiments on public real world datasets. The new algorithm outperforms the existing of item-based pearson correlation coefficient （IPCC）, user-based pearson correlation coefficient （UPCC） and Web service recommender system （WSRec） algorithms.

A location-aware GIServices quality prediction model via collaborative filtering

The quality of GIServices(QoGIS)is an important consideration for services sharing and interoperation.However,QoGIS is a complex concept and difficult to be evaluated reasonably.Most of the current studies have focused on static and non-scalable evaluation methods but have ignored location sensitivity subsequently resulting in the inaccurate QoGIS values.For intensive geodata and computation,GIServices are more sensitive to the location factor than general services.This paper proposes a location-aware GIServices quality prediction model via collaborative filtering(LAGCF).The model uses a mixed CF method based on time zone feature from the perspectives of both user and GIServices.Time zone is taken as the location factor and mapped into the prediction process.A time zone-adjusted Pearson correlation coefficient algorithm was designed to measure the similarity between the GIServices and the target,helping to identify highly similar GIServices.By adopting a coefficient of confidence in the final generation phase,the value of the QoGIS most similar to the target services will play a dominant role in the comprehensive result.Two series of experiments on large-scale QoGIS data were implemented to verify the effectivity of LAGCF.The results showed that LAGCF can improve the accuracy of QoGIS prediction significantly.

Broadcast-Based Spatial Queries

Indexing techniques have been developed for wireless data broadcast environments, in order to conserve the scarce power resources of the mobile clients. However, the use of interleaved index segments in a broadcast cycle increases the average access latency for the clients. In this paper, the broadcast-based spatial query processing methods （BBS） are presented for the location-based services. In the BBS, broadcasted data objects are sorted sequentially based on their locations, and the server broadcasts the location dependent data along with an index segment. Then, a sequential prefetehing and caching scheme is designed to reduce the query response time. The performance of this scheme is investigated in relation to various environmental variables, such as the distributions of the data objects, the average speed of the clients and the size of the service area.

Context-aware location discovery exchange in a ubiquitous environment

It becomes challenging in order to represent, discover and exchange location information in a ubiquitous environment due to dynamic movement and interaction between mobile nodes inside. In this paper, a new method is presented in order to make location information context-aware so that organizing the format of location information and maintaining the communication between direct connected nodes in a ubiquitous environment is enabled. The structure of a contextual location information repository and a context information communication protocol is manipulated to implement the proposed features. According to the simulation results in network simulator version2 （NS2）, the new method has depicted good discovery success ~nd consumed efficient service discovery bandwidth. Other network traffic, i.e. transmission control protocol, （TCP） has been simulated in the scenarios but the new location-aware method has shown its robustness with continuous context discovery process.