13194172
ActorNet: an actor platform for wireless sensor networks
We present actorNet, a mobile agent platform for wireless sensor networks (WSNs). WSNs are well-suited to multiagent systems: agent autonomy reduces the need for communication, saving precious energy. Mobile agents are also an intuitive technique for remotely reprogramming sensors deployed in the field. However, implementing agent programs directly on a WSN is complicated by the many limitations of sensor nodes, including limited memory, slow processors, low bandwidth and finite energy. ActorNet eases development by providing an abstract environment for lightweight concurrent object-oriented mobile code on WSNs. As such, it enables a wide range of new dynamic applications, including fully customizable queries and aggregation functions, in-network interactive debugging and high-level concurrent programming on the inherently parallel sensor network platform. Moreover, actorNet cleanly integrates all of these features into a fine-tuned, multi-threaded embedded Scheme interpreter that supports compact, maintainable programs---a significant advantage over primitive stack-based virtual machines.
2254400
iLTLchecker: a probabilistic model checker for multiple DTMCs
iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a tool to estimate a Markov transition matrix, and iLTLChecker, a tool to model check iLTL properties of DTMCs. These tools work together to verify iLTL properties of DTMCs.
61822837
Resilient Localization for Sensor Networks in Outdoor Environments
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is often impractical due to time requirements, economic constraints or inherent limitations of deployment scenarios. We have developed a service for reliably localizing wireless sensor networks in environments conducive to ranging errors by using a custom hardware-software solution for acoustic ranging and a family of self-localization algorithms. The ranging solution improves on previous work, extending the practical measurement range threefold (20-30m) while maintaining a distance-invariant median measurement error of about 1% of maximum range (33cm). The localization scheme is based on least squares scaling with soft constraints. Evaluation using ranging results obtained from sensor network field experiments shows that the localization scheme is resilient against large-magnitude ranging errors and sparse range measurements, both of which are common in large-scale outdoor sensor network deployments
5100963
Scalable Modeling and Performance Evaluation of Wireless Sensor Networks
A notable features of many proposed Wireless Sensor Networks (WSNs) deployments is their scale: hundreds to thousands of nodes linked together. In such systems, modeling the state of the entire system as a cross-product of the states of individual nodes results in the well-known state explosion problem. Instead, we represent the system state by the probability distribution on the state of each node. In other words, the system state represents the probability that a randomly picked node is in a certain state. Although such statistical abstraction of the global state loses some information, it is nevertheless useful in determining many performance metrics of systems that exhibit Markov behavior. We have previously developed a method for specifying the performance metrics of such systems in a probabilistic temporal logic called iLTL and for evaluating the behavior through a novel method for model checking iLTL properties. In this paper, we describe a method for estimating the probabilities in a Discrete Time Markov Chain (DTMC) model of a large-scale system. We also provide a statistical test so that we can reject estimated DTMCs if the actual system does not have Markov behavior. We describe results of experiments applying our method toWSNs in an experimental test-bed, as well as using simulations. The results of our experiments suggest that our model estimation and model checking method provides a systematic, precise and easy way of evaluating performance metrics of some large-scale WSNs.
21969752
The design and implementation of automata-based testing environment for Java multi-thread programs
Deterministic execution testing has been considered a promising method for concurrent program testing because of its reproducibility. However, since deterministic execution requires that a synchronization sequence to be replayed is feasible and valid, it is not directly applicable to a situation in which synchronization sequences, being valid but infeasible, are taken into account. To resolve this problem, we proposed automata-based testing in previous work, where a concurrent program is executed according to one sequence accepted by the automaton recognizing all sequences semantically equivalent to a given sequence. In this paper, we present the automata-based testing environment for Java multi-thread programs, and design and implement key components-automata generator, program transformer and replay controller. Algorithms for generating the equivalence automaton of a given sequence are presented and a program transformation method is suggested in order to guide a program to be executed according to the sequence accepted by the automaton. The replay controller is also redesigned and implemented to adopt the automaton. By illustrating automata-based testing procedures with the gas station example, we show how the proposed approach works in Java multi-threaded programs.
8907079
An empirical study on software error detection: voting, instrumentation and Fagan inspection
The paper presents the results of an experiment that compared error detection capability of voting, instrumentation, and Fagan inspection methods. Several experiments have measured effectiveness of various error detection methods. However, most experiments have used different programs; consequently, the results are generally incompatible and do not allow one to make objective comparison on the cost-effectiveness of various approaches. Software cannot be developed using an unlimited amount of resources, and practitioners need empirical and objective data on the cost-effectiveness of various error detection methods to decide which methods to use during software development. Results of this experiment is significant because these methods have been applied to the same program. Furthermore, the participant's educational and industrial experience are comparable to that of the previous experiments. We confirmed the previous finding that detecting errors in reliable programs is difficult; none of the three methods detected more than half of all the known errors in the programs. Of the three methods employed, participants detected more errors by using Fagan inspection method than they did by voting or instrumentation. When the average number of hours needed to detect an error was compared, Fagan inspection method was shown to be more cost-effective than instrumentation method.
10182888
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure optimization in artificial neural networks. There were many nonlinear feature extraction methods using neural networks but they still have the same difficulties arisen from the fixed network topology. In this paper, we propose a novel combination of genetic algorithm and feedforward neural networks for nonlinear feature extraction. The genetic algorithm evolves the feature space by utilizing characteristics of hidden neurons. It improved remarkably the performance of neural networks on a number of real world regression and classification problems.
13416160
Bandwidth tracing arbitration algorithm for mixed-clock SoC with dynamic priority adaptation
As the processing capabilities and operating frequency of embedded system are growing, so is the needed data bandwidth to fully utilize the processing capability. The ability to transfer huge amount of data between the embedded core and external devices is required for efficient system operation. In this paper, the data communication architecture for the mixed-clock system is proposed. The dynamic priority adaptation algorithm for bus arbitration is proposed for bandwidth guarantee. The communication architecture that incorporates the proposed arbitration algorithm adapts the priority of communication components dynamically based on the information from FIFO. The experiments show that the measured bandwidth of each component traces the required bandwidth well compared to the other arbitration algorithms.
40100233
Complexity Measures for Concurrent Programs Based on Information-Theoretic Metrics
Abstract We present a model and information-theoretic measures (entropy) which provide the complexity of concurrent programs. The information content, risk ratio and the amount of intertasking activity contained in a concurrent program are measured in terms of the information in the corresponding graph representation.