18 research outputs found
Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams
Emerging applications in Internet of Things (IoT) and Cyber-Physical Systems
(CPS) present novel challenges to Big Data platforms for performing online
analytics. Ubiquitous sensors from IoT deployments are able to generate data
streams at high velocity, that include information from a variety of domains,
and accumulate to large volumes on disk. Complex Event Processing (CEP) is
recognized as an important real-time computing paradigm for analyzing
continuous data streams. However, existing work on CEP is largely limited to
relational query processing, exposing two distinctive gaps for query
specification and execution: (1) infusing the relational query model with
higher level knowledge semantics, and (2) seamless query evaluation across
temporal spaces that span past, present and future events. These allow
accessible analytics over data streams having properties from different
disciplines, and help span the velocity (real-time) and volume (persistent)
dimensions. In this article, we introduce a Knowledge-infused CEP (X-CEP)
framework that provides domain-aware knowledge query constructs along with
temporal operators that allow end-to-end queries to span across real-time and
persistent streams. We translate this query model to efficient query execution
over online and offline data streams, proposing several optimizations to
mitigate the overheads introduced by evaluating semantic predicates and in
accessing high-volume historic data streams. The proposed X-CEP query model and
execution approaches are implemented in our prototype semantic CEP engine,
SCEPter. We validate our query model using domain-aware CEP queries from a
real-world Smart Power Grid application, and experimentally analyze the
benefits of our optimizations for executing these queries, using event streams
from a campus-microgrid IoT deployment.Comment: 34 pages, 16 figures, accepted in Future Generation Computer Systems,
October 27, 201
STUDY ON FATIGUE LIFE OF THIN-WALL STRUCTURE FASTENERS OF AIRCRAFT
A typical example of the damage failure of the thin-wall structure fasteners on aircraft was enumerated. The failure characteristics and its harmfulness of the thin-wall structure fasteners on aircraft were analyzed briefly. According to the fasteners loose and fall off failure problem of one sided connection structure of the leading edge of the wing on a certain aircraft,three improved design methods were put forward. And these fasteners with and without improved were experimental comparison verifyed by the tension-tension fatigue and the vibration endurance test methods. The impact vibrationn test device was developed to simulation or representation the failure mode and failure course of fasteners during vibration fatigue loading. A vibration fatigue test method on the thin-wall structure fasteners on aircraft was initially established. The results showed that there is essential difference on failure mode,damage mechanism,wreck destroy break appearance and pattern distributions of fatigue life of the thin-wall structure fasteners between the classical fatigue loading and the vibration fatigue loading. Based on the test results,the preferred and alternative improved design methods on the fasteners of one sided connection structure of the leading edge of the wing on a certain aircraft were provided
End-to-end Toolkit for Developing a Class of WSN Applications on Sun SPOT Nodes ∗
Over the past years of research in Wireless Sensor Networks (WSNs), both the hardware used to construct WSNs and the languages used to describe their functionality have evolved. The Sun Small Programmable Object Technology (Sun SPOT) nodes are the latest offering in the former domain, with a Java virtual machine running on the metal. On the programming side, macroprogramming frameworks such as the Abstract Task Graph (ATaG) have been developed that aim to greatly reduce the burden of the application developer for a wide range of WSN applications. In this work, we present an end-to-end solution for macroprogramming WSN applications on Sun SPOT nodes using ATaG- a data-driven programming paradigm. We will demonstrate all the stages starting from the specification of the application to its compilation and deployment on actual sensor nodes, thus showcasing the power of our toolchain. We believe that our research will enable wide adoption of WSNs among a range of end-users who will now have a concrete end-to-end toolkit to develop WSN applications.
An informatics approach to demand response optimization in smart grids.
Abstract Power utilities are increasingly rolling out "smart" grids with the ability to track consumer power usage in near real-time using smart meters that enable bidirectional communication. However, the true value of smart grids is unlocked only when the veritable explosion of data that will become available is ingested, processed, analyzed and translated into meaningful decisions. These include the ability to forecast electricity demand, respond to peak load events, and improve sustainable use of energy by consumers, and are made possible by energy informatics. Information and software system techniques for a smarter power grid include pattern mining and machine learning over complex events and integrated semantic information, distributed stream processing for low latency response, Cloud platforms for scalable operations and privacy policies to mitigate information leakage in an information rich environment. Such an informatics approach is being used in the DoE sponsored Los Angeles Smart Grid Demonstration Project, and the resulting software architecture will lead to an agile and adaptive Los Angeles Smart Grid