Ihn-Han Bae

An ontology-based approach to ADL recognition in smart homes

This paper presents a method for recognition of Activities of Daily Living (ADL) in smart homes. Recognition of activities of daily living and tracking them can provide unprecedented opportunities for health monitoring and assisted living applications, especially for elderly people and people with memory deficits. This paper presents Recognizing Activities of Daily Living (RADL) by discovering and monitoring patterns of ADLs in sensor equipped smart homes. The RADL is composed of two components: smart home management monitoring and ADL pattern monitoring. This paper studies the ontology base and the reasoning that are the main parts of ADL pattern monitoring. The ontology for RADL is designed and the prototype system of RADL is implemented using Protege and Jess tools. Also, the ontology for RADL is verified by OntoCheck in automatic mode and evaluated by a metric-based approach in manual mode.

A Misbehavior-Based Reputation Management System for VANETs

Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose a misbehavior-based reputation management system (MBRMS) which is composed of three components: misbehavior detection, event rebroadcast and global eviction algorithms, to detect and filter false data in vehicular ad-hoc networks (VANETs). The performance of MBRMS is evaluated through simulation. From the results of the simulation, we confirm that the proposed MBRMS identifies and evicts properly bad nodes by outlier detection method and misbehaving node risk value.

An Adaptive Location Service on The Basis of Diamond Quorum for MANETs

Mobile ad-hoc network (MANET) is a network of mobile nodes that do not have a fixed infrastructure. Recent research in this field addresses ways of solving existing problems in a MANET by using the node location information. However, maintaining the location information of the nodes is one of the essential challenges in mobile ad-hoc networks because the location of a node changes frequently. In this paper, we propose an adaptive location service on the basis of diamond quorum system (DQS) considering the gravity of locality that is managing the location information for all nodes efficiently in a MANET. In a proposed scheme, the mobility database storing the location information of a mobile node can be selected adoptively from the DQS by considering the gravity of locality. The performance of a proposed scheme is to be evaluated by an analytical model, and compared with that of existing uniform quorum system (UQS) based mobility management scheme.

A Tolerant Context-Aware Driver Assistance System for VANETs-Based Smart Cars

Current driver assistance systems merely use a minimum amount of information. By using additional information of the environment hazardous situations can be detected earlier, more reliably and with a higher accuracy. This situational information has a significant impact not only on hazard detection, but also on other modules such as the human-machine-interface or knowledge distribution between vehicles over vehicular ad-hoc networks. In this paper, we design TOCADAS (TOlerant Context-Aware Driver Assistance System) in order to help prevent accidents and reduce the number of traffic fatalities. The proposed TOCADAS is aware of uncertain situational information, recognizes current context situation and provides drivers with the most effective driver assistance services for the current context situation using pattern similarity degrees.

Design and Evaluation of a Fuzzy Cooperative Caching Scheme for MANETs

Caching of frequently accessed data in multi-hop ad hoc environment is a technique that can improve data access performance and availability. Cooperative caching, which allows sharing and coordination of cached data among several clients, can further enhance the potential of caching techniques. In this paper, we propose a fuzzy cooperative caching scheme in mobile ad hoc networks. The cache management of the proposed caching scheme not only uses adaptively CacheData or CachePath based on data similarity and data utility, but also uses the replacement manager based on data profit. Also, the proposed caching scheme uses a prefetch manager. When the TTL of the cached data expires, the prefetch manager evaluates the popularity index of the data. If the popularity index is larger than a threshold, the data is prefetched. Otherwise, its space is released. The performance of the proposed scheme is evaluated analytically and is compared to that of other cooperative caching schemes.

A Fuzzy Logic-Based Location Management Method for Mobile Networks

State-of-the-art wireless communication networks allow dynamic relocation of mobile terminals. A location management mechanism is required to keep track of a mobile terminal for delivering incoming calls. In this paper, we propose a fuzzy logic-based location management method to reduce paging cost. In the proposed method, the location update uses an area-based method that uses direction-based method together with movement-based method, and the location search uses a fuzzy logic-based selective paging method based on the mobility information of mobile terminals. A partial candidate paging area is selected by fuzzy control rules, and then the fuzzy logic-based selective paging method pages only cells within the partial candidate paging area. The performance of the proposed fuzzy logic-based location management method is evaluated by an analytical model and by a simulation, and is compared with that of basic velocity paging (BVP) method.

Design and Evaluation of a Hybrid Intelligent Broadcast Algorithm for Alert Message Dissemination in VANETs

Vehicular ad hoc network is an emerging new technology and a promising platform for the intelligent transportation system. The most important application of VANET is disseminating emergency messages to warn drivers in case of dangerous events. The core technique relies on the design of a broadcast scheme. In this paper, we propose a hybrid intelligent broadcast algorithm for alert message dissemination in VANETs that is called Hi-CAST. To deliver alert message effectively, the proposed Hi-CAST algorithm uses delay and probabilistic broadcast protocols together with token protocol. The performance of the Hi-CAST is evaluated through simulation and compared with that of other alert message dissemination algorithms.

FHLS: Fuzzy Hierarchical Location Service for Mobile Ad Hoc Networks

Location services are used in mobile ad hoc and hybrid networks either to locate the geographic position of a given node in the network or for locating a data item. One of the main usages of position location services is in location based routing algorithms. In particular, geographic routing protocols can route messages more efficiently to their destinations based on the destination nodes geographic position, which is provided by a location service. In this paper, we propose an adaptive location service on the basis of fuzzy logic called FHLS (fuzzy hierarchical location service) for mobile ad hoc networks. The FHLS uses the adaptive location update scheme using the fuzzy logic on the basis of the mobility and the call preference of mobile nodes. The performance of the FHLS is to be evaluated by using a simulation, and compared with that of existing HLS scheme.

A Weighted-Dissimilarity-Based Anomaly Detection Method for Mobile Wireless Networks

Mobile wireless networks continue to be plagued by theft of identity and intrusion. Both problems can be addressed in two different ways, either by misuse detection or anomaly-based detection. In this paper, we propose a weighted-dissimilarity-based anomaly detection method that can effectively identify abnormal behavior such as mobility patterns of mobile wireless networks. In the proposed algorithm, a normal profile is constructed from normal mobility patterns of mobile nodes in mobile wireless networks. From the constructed normal profile, the dissimilarity is computed by a weighted dissimilarity measure. If the computed dissimilarity value is greater than the dissimilarity threshold that is a system parameter, an alert message is occurred. The performance of the proposed method is evaluated through a simulation. From the result of the simulation, we know that the proposed method is superior to the performance of anomaly detection methods using other dissimilarity measures.

An Ontology-Based ADL Recognition Method for Smart Homes

This paper presents a method for recognition of Activities of Daily Living (ADLs) in smart homes. Recognition of activities of daily living and tracking them can provide unprecedented opportunities for health monitoring and assisted living applications, especially for elderly and people with memory deficits. We present ARoM (ADL Recognition Method) that discovers and monitors patterns of ADLs in sensor equipped smart homes. The ARoM is consists of two components: smart home management monitoring and ADL pattern monitoring. This paper studies on the ontology base and the reasoning that are main parts of ADL pattern monitoring. The ontology base supports the semantic discovery for location, device, environments domains in smart homes. The reasoning system discovers the activity for a person and the appropriate service for a present situation. On detection of significant changes of context, the reasoning is triggered. We design the ontology model for ARoM and implement the prototype system of ARoM by using Protege and Jess tools.