Yellow Tree: A Distributed Main-memory Spatial Index Structure for Moving Objects

Mobile devices equipped with wireless technologies to communicate and positioning systems to locate objects of interest are common place today, providing the impetus to develop location-aware applications. At the heart of location-aware applications are moving objects or objects that continuously change location over time, such as cars in transportation networks or pedestrians or postal packages. Location-aware applications tend to support the tracking of very large numbers of such moving objects as well as many users that are interested in finding out about the locations of other moving objects. Such location-aware applications rely on support from database management systems to model, store, and query moving object data. The management of moving object data exposes the limitations of traditional (spatial) database management systems as well as their index structures designed to keep track of objects\u27 locations. Spatial index structures that have been designed for geographic objects in the past primarily assume data are foremost of static nature (e.g., land parcels, road networks, or airport locations), thus requiring a limited amount of index structure updates and reorganization over a period of time. While handling moving objects however, there is an incumbent need for continuous reorganization of spatial index structures to remain up to date with constantly and rapidly changing object locations. This research addresses some of the key issues surrounding the efficient database management of moving objects whose location update rate to the database system varies from 1 to 30 minutes. Furthermore, we address the design of a highly scaleable and efficient spatial index structure to support location tracking and querying of large amounts of moving objects. We explore the possible architectural and the data structure level changes that are required to handle large numbers of moving objects. We focus specifically on the index structures that are needed to process spatial range queries and object-based queries on constantly changing moving object data. We argue for the case of main memory spatial index structures that dynamically adapt to continuously changing moving object data and concurrently answer spatial range queries efficiently. A proof-of concept implementation called the yellow tree, which is a distributed main-memory index structure, and a simulated environment to generate moving objects is demonstrated. Using experiments conducted on simulated moving object data, we conclude that a distributed main-memory based spatial index structure is required to handle dynamic location updates and efficiently answer spatial range queries on moving objects. Future work on enhancing the query processing performance of yellow tree is also discussed

Variables and parameters as references and containers

Most designers of object-based languages adopt a reference model of variables without explicit justification, despite its wide ranging consequences. This paper argues that the traditional container model of variables is more efficient than the reference model, nearly as flexible, and more appropriate to parallel and distributed systems. The topics addressed are object lifetime and its implications for storage management, dynamic typing and its implications for object representation, aliasing and its implications for interference between operations, parameter passing and its implications for communication, and sharing and its implications for contention. We present our experience with the container model in a prototype parallel language. Neither model is always better than the other, and the choice of model should not be left to default.Computing Reviews Categories and Subject Descriptors: D.3.2 [Programming Lan­guages]: Language Classifications — concurrent, distributed and parallel languages; object-oriented languages; D.3.3 [Programming Languages]: Language Constructs and Features — concurrent programming structures; data types and structures; dynamic storage management; procedures, func­tions, and subroutinesKeywords: object-based programming languages, reference variables, container variables, reference parameters, container parameters, variable lifetime, object lifetime, dynamic typing, static typing, dynamic allocation, static allocation, garbage collection, variable aliasing, parameter passing, communication, sharing, contention, parallelism, concurrency, distribution, Matroshka, Natash

Pattern Reification as the Basis for Description-Driven Systems

One of the main factors driving object-oriented software development for information systems is the requirement for systems to be tolerant to change. To address this issue in designing systems, this paper proposes a pattern-based, object-oriented, description-driven system (DDS) architecture as an extension to the standard UML four-layer meta-model. A DDS architecture is proposed in which aspects of both static and dynamic systems behavior can be captured via descriptive models and meta-models. The proposed architecture embodies four main elements - firstly, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, secondly the identification of four data modeling relationships that can be made explicit such that they can be modified dynamically, thirdly the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourthly the encoding of the structural properties of the five design patterns by means of one fundamental pattern, the Graph pattern. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of description-driven data objects to handle system evolution.Comment: 20 pages, 10 figure

Macroservers: An Execution Model for DRAM Processor-In-Memory Arrays

The emergence of semiconductor fabrication technology allowing a tight coupling between high-density DRAM and CMOS logic on the same chip has led to the important new class of Processor-In-Memory (PIM) architectures. Newer developments provide powerful parallel processing capabilities on the chip, exploiting the facility to load wide words in single memory accesses and supporting complex address manipulations in the memory. Furthermore, large arrays of PIMs can be arranged into a massively parallel architecture. In this report, we describe an object-based programming model based on the notion of a macroserver. Macroservers encapsulate a set of variables and methods; threads, spawned by the activation of methods, operate asynchronously on the variables' state space. Data distributions provide a mechanism for mapping large data structures across the memory region of a macroserver, while work distributions allow explicit control of bindings between threads and data. Both data and work distributuions are first-class objects of the model, supporting the dynamic management of data and threads in memory. This offers the flexibility required for fully exploiting the processing power and memory bandwidth of a PIM array, in particular for irregular and adaptive applications. Thread synchronization is based on atomic methods, condition variables, and futures. A special type of lightweight macroserver allows the formulation of flexible scheduling strategies for the access to resources, using a monitor-like mechanism

Benchmarking Memory Management Capabilities within ROOT-Sim

In parallel discrete event simulation techniques, the simulation model is partitioned into objects, concurrently executing events on different CPUs and/or multiple CPUCores. In such a context, run-time supports for logical time synchronization across the different simulation objects play a central role in determining the effectiveness of the specific parallel simulation environment. In this paper we present an experimental evaluation of the memory management capabilities offered by the ROme OpTimistic Simulator (ROOT-Sim). This is an open source parallel simulation environment transparently supporting optimistic synchronization via recoverability (based on incremental log/restore techniques) of any type of memory operation affecting the state of simulation objects, i.e., memory allocation, deallocation and update operations. The experimental study is based on a synthetic benchmark which mimics different read/write patterns inside the dynamic memory map associated with the state of simulation objects. This allows sensibility analysis of time and space effects due to the memory management subsystem while varying the type and the locality of the accesses associated with event processin

From Design to Production Control Through the Integration of Engineering Data Management and Workflow Management Systems

At a time when many companies are under pressure to reduce "times-to-market" the management of product information from the early stages of design through assembly to manufacture and production has become increasingly important. Similarly in the construction of high energy physics devices the collection of (often evolving) engineering data is central to the subsequent physics analysis. Traditionally in industry design engineers have employed Engineering Data Management Systems (also called Product Data Management Systems) to coordinate and control access to documented versions of product designs. However, these systems provide control only at the collaborative design level and are seldom used beyond design. Workflow management systems, on the other hand, are employed in industry to coordinate and support the more complex and repeatable work processes of the production environment. Commercial workflow products cannot support the highly dynamic activities found both in the design stages of product development and in rapidly evolving workflow definitions. The integration of Product Data Management with Workflow Management can provide support for product development from initial CAD/CAM collaborative design through to the support and optimisation of production workflow activities. This paper investigates this integration and proposes a philosophy for the support of product data throughout the full development and production lifecycle and demonstrates its usefulness in the construction of CMS detectors.Comment: 18 pages, 13 figure

Improving the scalability of parallel N-body applications with an event driven constraint based execution model

The scalability and efficiency of graph applications are significantly constrained by conventional systems and their supporting programming models. Technology trends like multicore, manycore, and heterogeneous system architectures are introducing further challenges and possibilities for emerging application domains such as graph applications. This paper explores the space of effective parallel execution of ephemeral graphs that are dynamically generated using the Barnes-Hut algorithm to exemplify dynamic workloads. The workloads are expressed using the semantics of an Exascale computing execution model called ParalleX. For comparison, results using conventional execution model semantics are also presented. We find improved load balancing during runtime and automatic parallelism discovery improving efficiency using the advanced semantics for Exascale computing.Comment: 11 figure

A Formal Framework for Concrete Reputation Systems

In a reputation-based trust-management system, agents maintain information about the past behaviour of other agents. This information is used to guide future trust-based decisions about interaction. However, while trust management is a component in security decision-making, many existing reputation-based trust-management systems provide no formal security-guarantees. In this extended abstract, we describe a mathematical framework for a class of simple reputation-based systems. In these systems, decisions about interaction are taken based on policies that are exact requirements on agents’ past histories. We present a basic declarative language, based on pure-past linear temporal logic, intended for writing simple policies. While the basic language is reasonably expressive (encoding e.g. Chinese Wall policies) we show how one can extend it with quantification and parameterized events. This allows us to encode other policies known from the literature, e.g., ‘one-out-of-k’. The problem of checking a history with respect to a policy is efficient for the basic language, and tractable for the quantified language when policies do not have too many variables