Myungseok Kang

Performance Analysis of Location Estimation Algorithm in ZigBee Networks Using Received Signal Strength

This paper presents a maximum likelihood estimator (MLE) for the ZigBee networks. We propose a deployment of cluster-tree topology in the ZigBee networks and derive the MLE under the log-normal models for the Received Signal Strength (RSS) measurements. The ZiLA algorithm is also proposed to apply the MLE to ZigBee networks. To validate the RSS measurement model, we have conducted exhaustive experiments. Testbed experiments are also conducted to validate the effectiveness of ZiLA algorithm.

ZigBee Based Location Estimation in Home Networking Environments

This paper presents a Maximum Likelihood Location Estimation (MLLE) algorithm for the home network environments. We propose a deployment of cluster-tree topology in the ZigBee networks and derive the MLE under the log-normal models for the Received Signal Strength (RSS) measurements. Experiments are also conducted to validate the effectiveness of the proposed algorithm.

FTOG-Based Management and Recovery Services

This paper presents a Fault-Tolerant Object Group (FTOG) model that provides the group management service and the fault-tolerance service for consistency maintenance and state transparency. Through Intelligent Home Network Simulator, we verify that FTOG model supports both of reliability and the stability of the distributed system.

A context-aware service model using a multi-level prediction algorithm in smart home environments

Smart home is emerging as the future digital home environments that provide various ubiquitous home services like u-Life, u-Health, etc. It is composed of some home appliances and sensors which are connected through wired/wireless network. Ubiquitous home services become aware of users context with the information gathered from sensors and make home appliances adapt to the current home situation for maximizing user convenience. In these context-aware home environments, it is the one of significant research topics to predict user behaviors in order to proactively control the home environment. In this paper, we propose Multi-Level prediction algorithm for context-aware services in ubiquitous home environment. The algorithm has two phases, prediction and execution. In the first prediction phase, the next location of user is predicted using tree algorithm with information on users, time, location, devices. In the second execution phase, our table matching method decides home appliances to run according to the prediction, devices location, and user requirement. Since usually home appliances operate together rather than separately, our approach introduces the concept of mode service, so that it is possible to control multiple devices as well as a single one. We also devised some scenarios for the conceptual verification and validated our algorithm through simulations.

A design of RFTOG model for distributed real-time applications

In this paper, we design the Real-Time Fault-Tolerant Object Group (RFTOG) model that supports the grouping of distributed objects that are required for distributed application. The proposed model basically provides two services. One is the group management service, which supports both consistency maintenance and transparency of the replicated objects with a variety of replication mechanisms. It also provides the load balancing of distributed applications. The other is real-time service in an object group. When the clients request the service to the service object selected through the load balance, this service guarantees the service execution within deadline for the clients’ requests. We develop the Naval Air Defense System (NADS) simulator for verifying the effectiveness of the services proposed by the RFTOG model.

Intelligent service reasoning model using data mining

This paper proposes an Intelligent Service Reasoning (ISR) model using data mining in smart home environments. This model creates a service tree used for service reasoning on the basis of the C4.5 algorithm, one of decision tree algorithms, and determines the services that will be provided to users through a quantitative weight estimation algorithm that uses a quantitative characteristic rule and a quantitative discrimination rule. The effectiveness in the performance of the developed model is validated through a smart home-network simulation.

Construction of an Agent-based Fault-Tolerant Object Group Model

We propose an agent-based fault-tolerant object group (AFTOG) model for achieving effective object management and reliable fault recovery. We define five kinds of agents as internal processing agent, registration agent, state handling agent, user interface agent, and service agent. The roles of the agents in the proposed model are not only to reduce the remote interactions between distributed objects but also to guarantee more effective service execution. Through the simulations, it is validated that the proposed model decreases the interactions of the object components and supports effective fault recovery, while providing more stable and reliable services.

Design and Implementation of a Real-Time Fault-Tolerant Object Group Model

In this paper, we design the Real-Time Fault-Tolerant Object Group (RFTOG) model that provide distributed transparency to heterogeneous and guarantee the service execution within deadline. The RFTOG provides the object management service and real-time service. Also, based on RFTOG model, we verify the services of the proposed model by implementing Naval Air Defense System (NADS) simulator as distributed real-time simulation environment.

A Time-Redundant Recovery Scheme of TMR failures Using Retry and Rollback Techniques

This paper proposes an integrated recovery approach applying retry and rollback techniques to recover the TMR failure. Combining the time redundancy techniques with W system is apparently effective to recover the TMR failure(or masked error) primarily caused by transient faults. These policies need fewer reconfigurations at the cost of extra time required for the time redundant schemes. The optimal numbers of retry and rollback to minimize the mean execution time of tasks are derived for the proposed method through computing the likelihoods of all possible states of the failed system. The effectiveness of the proposed method is validated through examining certain numerical examples and simulations conducted with a variety of parameters governing environmental characteristics.

Construction of a Fault-Tolerant Object Group Framework and Its Execution Analysis Using Home-Network Simulations

We propose a Fault-Tolerant Object Group framework that provides group management and fault-tolerance services for consistency maintenance and state transparency as well. Through a virtual home-network simulation, we validate that the FTOG framework supports both of the reliability and the stability of the distributed home-network systems.