Catálogo de publicaciones - libros

RFID systems should be designed to process a large number of RFID data in real time. Therefore, there have been much research and company studies regarding RFID data processing. One of methods is CEP (Complex Event Processing), which can provide a method to process RFID data efficiently. However, previous work is just focused on raw RFID data processing, such as data filtering, the elimination of duplicated data, and the aggregation of data. Also, it creates primitive events based on just one physical or logical reader. Therefore, processing overhead for complex events may increase. And it cannot provide business level events. Therefore, we propose a method that can reduce processing overhead and create business level events by using CEP. Proposed method provides two primitive events that are defined by using the relationship of two readers. Thus, when any pattern of events is matched for a specific complex event, business level events can be generated and execution time can be reduced comparing with other mechanisms without those events. And, execution time can be reduced by about 57% as compared to others.

Recently, there is lots research for tangible objects which enables to support users everyday’s life. However, due to the high price of sensors , end-users hesitate to attach such devices to physical objects. Even worth, batteries of embedded devices should despoil the living environment. Therefore, the low-price system to detect users’ phisical objects without battery is needed. We will propose a novel hardware platform using cheap RFID tags which can attach on any everyday physical objects. We have designed and implemented two size of RFID systems which have flexible multiple area antennas to support manage users’ physical objects. This paper describes details of Smart-Furoshiki system and its applications.

In context-aware computing, the context aggregation is an important function of the context management. In an infrastructure-based smart space, a centralized context management system need not concern about its resource consumption for context aggregation. However, in a personal smart space which consists of only resource-constrained mobile devices, not only global resource consumption of the personal smart space but also that of the device which plays a role of a context manager (coordinator) must be minimized. In this paper, we propose a task decomposition scheme in which heavy context aggregation tasks to be imposed on a centralized coordinating device are decomposed and distributed to all the participating mobile devices (clients) in a mobile smart space. By decomposing and distributing the heavy aggregation operations the processing overhead upon the coordinating device can be minimized while providing equivalent context aggregation capability for applications, but maintaining the total amount of processing of all devices not to be significantly increased.

The architecture named the GALIS is a cluster-based distributed computing system architecture which has been devised to efficiently handle a large volume of LBS application data. In this paper, we propose a distributed k-NN query processing scheme for moving objects on multiple computing nodes, each of which keeps records relevant to a different geographical zone. We also propose a hybrid k-NN scheme, which utilizes range queries instead of k-NN queries for the neighboring overlapped nodes, thus resulting in 30% reduction of query processing cost. Through some experiments, we show the efficiency of hybrid k-NN scheme over naïve k-NN scheme.

In a pervasive environment, context aware services are necessary to enable collaborate and communicate with others in order to provide proper service to users. Each service can be designed with individual context information which represents different perspective over the context. This paper proposes an advanced context management model with context alignment among heterogeneous context aware services. This model enable the interaction between context information producer devices and context information consumer devices and as well as their insertion in an open environment. And this paper show how this model can be used in context aware middleware.

Community computing is a new computing environment where ubiquitous services are provided by cooperation between existing smart object. In these days, it is studied by many researchers but works on community computing are still at an early phase. To design and describe cooperation effectively, in this paper, we propose the community situation based cooperation model. In addition, we introduce conflict resolution scheme for community computing. Consequently, we propose the community computing model supporting the community situation based cooperation and conflicts resolution. Case studies are also tried to examine the proposed community computing model.

When developing strategies for future research directions it may be a wise decision to reflect on the development in the respective area during the last few years. As to future applications of embedded systems, we consider a concise solution for interconnecting embedded systems to be one of their core requirements. In particular, we focus on the development of dependable communication.

Our paper recapitulates progress in research and development of dependable time-triggered communication protocols as done by the Institute for Computer Engineering at the Vienna University of Technology and by TTTech Computertechnik AG over the last five years. We provide an overview of the current situation and discuss the ongoing research and development directions.

We consider the problem of scheduling distributable real-time threads in networked embedded systems that operate under run-time uncertainties including those on thread execution times, thread arrivals, and node failure occurrences. We present a distributed scheduling algorithm called CUA. We show that CUA satisfies thread time constraints in the presence of crash failures, is early-deciding, has an efficient message complexity of () (where is the number of crashes that actually occur and is the number of nodes), and is time-optimal with a time lower bound of ( +  + ) (where is the message delay upper bound, is the failure detection bound, and is the maximum number of threads). In crash-free runs, the algorithm constructs schedules within ( + ), and yields optimal total utility if nodes are also not overloaded. The algorithm is also “best-effort” in that a high importance thread that may arrive at any time has a very high likelihood for feasible completion (in contrast to classical admission control algorithms which favor feasible completion of admitted threads over admitting new ones, irrespective of thread importance).

Signal voting of redundant sensor values and communication channels is of central importance in today’s X-by-wire systems. The required degree of sensor redundancy, the type of redundancy, and finally the voting strategy must be designed to meet the system’s dependability requirements. These design decisions depend on an analysis of the probabilities and effects of all underlying fault scenarios. Given a probabilistic fault model and a communication model, the voting step can be formally stated as a maximum-likelihood estimation of the correct input signal. With an example of an X-by-wire system we show how GTEFT can be used to derive the failure probabilities of different fault scenarios for various systems architectures and different voting strategies. Thus the capability of GTEFT to support system development and system assessment is demonstrated.

Some high integrity software systems require the rigorous validation of safety properties. Assessing whether software architectures are able to meet these requirements is of great interest: to avoid the risk that the implementation does not fulfill requirements due to a bad design, and, to reduce the development cost of safety critical parts of the system. Safety analyses like FMECA and FTA are two methods used during preliminary safety assessments. We have implemented tools to automatically generate safety analyses from the models of the architecture: a UML profile for safety, modeling languages to express safety analyses, and a model transformation chain. Safety analysts can use these tools to annotate the models, analyze the architecture, and recommend system engineers mitigation means to apply for improving the architecture.