6484880
Spatio-temporal aggregation using sketches
Several spatio-temporal applications require the retrieval of summarized information about moving objects that lie in a query region during a query interval (e.g., the number of mobile users covered by a cell, traffic volume in a district, etc.). Existing solutions have the distinct counting problem: if an object remains in the query region for several timestamps during the query interval, it will be counted multiple times in the result. We solve this problem by integrating spatio-temporal indexes with sketches, traditionally used for approximate query processing. The proposed techniques can also be applied to reduce the space requirements of conventional spatio-temporal data and to mine spatio-temporal association rules.
3455572
On Trip Planning Queries in Spatial Databases
In this paper we discuss a new type of query in Spatial Databas es, called the Trip Planning Query (TPQ). Given a set of points of interestP in space, where each point belongs to a specific category, a star ting pointS and a destinationE, TPQ retrieves thebesttrip that starts at S, passes through at least one point from each category, and ends at E. For example, a driver traveling from Boston to Providence might want to stop to a gas station, a ban k and a post office on his way, and the goal is to provide him with the best possibl e route (in terms of distance, traffic, road conditions, etc.). The difficulty of this query lies in the existence of multiple choices per category. In this paper, w study fast approximation algorithms for TPQ in a metric space. We provide a numb er of approximation algorithms with approximation ratios that depend o either the number of categories, the maximum number of points per category or b oth. Therefore, for different instances of the problem, we can choose the alg orithm with the best approximation ratio, since they all run in polynomial time. Furthermore, we use some of the proposed algorithms to derive efficient heuristi cs for large datasets stored in external memory. Finally, we give an experimental ev luation of the proposed algorithms using both synthetic and real datasets .
3002704
Approximate aggregation techniques for sensor databases
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidth-intensive when combined with the fault-tolerant, multipath routing methods often used in these environments. For example, duplicate-sensitive aggregates such as SUM cannot be computed exactly using substantially less bandwidth than explicit enumeration. To avoid this expense, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicate-insensitive sketches for approximating COUNT to handle SUM, 2) we present and analyze methods for using sketches to produce accurate results with low communication and computation overhead, and 3) we present an extensive experimental validation of our methods.
2945748
Time Series Compressibility and Privacy
In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty about individual values by perturbing them. More specifically, if the perturbation does not have the same compressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty. Thus, by making the perturbation "similar" to the original data, we can both preserve the structure of the data better, while simultaneously making breaches harder. However, as data become more compressible, a fraction of the uncertainty can be removed if true values are leaked, revealing how they were perturbed. We formalize these notions, study the above trade-offs on real data and develop practical schemes which strike a good balance and can also be extended for on-the-fly data hiding in a streaming environment.
16124997
GameOD: an internet based game-on-demand framework
Multiplayer online 3D games are becoming very popular in recent years. However, existing games require the complete game content to be installed prior to game playing. Since the content is usually large in size, it may be difficult to run these games on a PDA or other handheld devices. It also pushes game companies to distribute their games as CDROMs/DVDROMs rather than online downloading. On the other hand, due to network latency, players may perceive discrepant status of some dynamic game objects. In this paper, we present a game-on-demand (GameOD) framework to distribute game content progressively in an on-demand manner. It allows critical contents to be available at the players' machines in a timely fashion. We present a simple distributed synchronization method to allow concurrent players to synchronize their perceived game status. Finally, we show some performance results of the proposed framework.
8615414
Collaborative distributed virtual sculpting
A lot of effort is now being put into developing collaborative distributed virtual environments. However very few projects address collaborative virtual sculpting in which the shapes of the target objects are likely changing continuously. Some major issues including user interaction, data transmission, concurrent object editing by multiple clients and rendering of deforming objects must be addressed in a real-time context. We propose a framework for collaborative virtual sculpting in a distributed virtual environment. The system is based on a hybrid model which merges the client-server and the peer-to-peer architectures to allow fast data replication. To support real-time deformation and rendering of deformable objects, we model each of these objects using NURBS surfaces and render them using the real-time deformable NURBS rendering method that we have developed. We present a data structure for the transmission of these deformable objects. We also introduce the idea of editing region and the corresponding locking mechanism for simultaneous editing of the same object by multiple clients. Toward the end of the paper we show some performance results of the prototype system.
11226444
Locality-conscious workload assignment for array-based computations in MPSOC architectures
While the past research discussed several advantages of multiprocessor-system-on-a-chip (MPSOC) architectures from both area utilization and design verification perspectives over complex single core based systems, compilation issues for these architectures have relatively received less attention. Programming MPSOCs can be challenging as several potentially conflicting issues such as data locality, parallelism and load balance across processors should be considered simultaneously. Most of the compilation techniques discussed in the literature for parallel architectures (not necessarily for MPSOCs) are loop based, i.e., they consider each loop nest in isolation. However, one key problem associated with such loop based techniques is that they fail to capture the interactions between the different loop nests in the application. This paper takes a more global approach to the problem and proposes a compiler-driven data locality optimization strategy in the context of embedded MPSOCs. An important characteristic of the proposed approach is that, in deciding the workloads of the processors (i.e., in parallelizing the application) it considers all the loop nests in the application simultaneously. The authors' experimental evaluation with eight embedded applications showed that the global scheme brings significant power/performance benefits over the conventional loop based scheme.
11065544
Profile-driven energy reduction in network-on-chips
Reducing energy consumption of a Network-on-Chip (NoC) is a critical design goal, especially for power-constrained embedded systems.In response, prior research has proposed several circuit/architectural level mechanisms to reduce NoC power consumption. This paper considers the problem from a different perspective and demonstrates that compiler analysis can be very helpful for enhancing the effectiveness of a hardware-based link power management mechanism by increasing the duration of communication links' idle periods. The proposed profile-based approach achieves its goal by maximizing the communication link reuse through compiler-directed, static message re-routing. That is, it clusters the required data communications into a small set of communication links at any given time, which increases the idle periods for the remaining communication links in the network. This helps hardware shut down more communication links and their corresponding buffers to reduce leakage power. The current experimental evaluation, with twelve data-intensive embedded applications, shows that the proposed profile-driven compiler approach reduces leakage energy by more than 35% (on average) as compared to a pure hardware-based link power management scheme.
2365659
A Trajectory-Preserving Synchronization Method for Collaborative Visualization
In the past decade, a lot of research work has been conducted to support collaborative visualization among remote users over the networks, allowing them to visualize and manipulate shared data for problem solving. There are many applications of collaborative visualization, such as oceanography, meteorology and medical science. To facilitate user interaction, a critical system requirement for collaborative visualization is to ensure that remote users would perceive a synchronized view of the shared data. Failing this requirement, the user's ability in performing the desirable collaborative tasks would be affected. In this paper, we propose a synchronization method to support collaborative visualization. It considers how interaction with dynamic objects is perceived by application participants under the existence of network latency, and remedies the motion trajectory of the dynamic objects. It also handles the false positive and false negative collision detection problems. The new method is particularly well designed for handling content changes due to unpredictable user interventions or object collisions. We demonstrate the effectiveness of our method through a number of experiments