2862791
A data delivery strategy in ubiquitous computing systems
Browsing Web pages through wireless devices will become more and more popular in the near future. However, accessing a large chunk of Web data incurs a great amount of access latency while a mobile user migrates across cells. This paper investigates this problem and proposes an effective way of delivering such data to a mobile user in a ubiquitous computing system. Our data delivery (/spl Dscr//sup 2/) strategy is based on the dynamic programming skill needed to pre-assign the user-requested data on the possible cells to be visited in order to reduce the access latency. We first design an encoding method for the cells and then derive the properties of the encoding scheme. These properties are then used in our algorithm to deliver the data. Finally, experiments are conducted to demonstrate the feasibility and efficiency of the proposed method.
31179959
Improving location management for mobile users with frequently visited locations
Abstract In wireless computing environment, users’ mobility brings new challenges to traditional computing systems. The explosive growth of demand in communication bandwidth requires new schemes to effectively and efficiently locate users. The Basic HLR/VLR locating scheme does not exploit the fact that many mobile users’ (such as commuters’) moving patterns are likely to be known. In this paper, we propose one locating scheme, the frequently visited locations first (FVLF) scheme, to efficiently locate a mobile user. The FVLF scheme is proposed to prestore the RAs that a mobile user frequently visits according to the probabilities of the RAs that the mobile user may appear. When the system receives a call, these prestored RAs are examined first to locate the callee. This scheme can avoid the high cost of querying the callee’s HLR. The cost model of the proposed scheme is derived and the optimal number of prestored RAs is also found. Our evaluation shows that benefit does exist in various conditions by using this scheme.
9024709
Time-Constrained Service on Air
Data broadcasting is an efficient and highly scalable technique for delivering data to mobile clients in wireless environments. In this paper, we study the problem of scheduling broadcast data that are with an expected time within which the client is expecting to receive the data item. We analyze the problem and derive the minimum number of broadcast channels required for such a task. Also, we discuss the problems when the number of available channels is not enough. We propose novel solutions for both of the cases and the performance study indicates that our method is much better than the previous ones and performs very close to optimal
9253270
Query Optimization in Multidatabase Systems Considering Schema Conflicts
In a multidatabase system, the participating databases are autonomous. The schemas of these databases may be different in various ways, while the same information is represented. A global query issued against the global database needs to be translated to a proper form before it can be executed in a local database. Since data requested by a query (or a part of a query) is sometimes available in multiple sites, the site (database) that processes the query with the least cost is the desired query processing site. The authors study the effect of differences in schemas on the cost of query processing in a multidatabase environment. They first classify schema conflicts to different types. For each type of conflict, they show how much more or less complex a translated query can become in comparison with the originally user-issued global query. Based on this observation, they propose an analytical method that considers the conflicts between local databases and finds the database(s) that renders the least execution cost in processing a global query. This research introduces a new level of query optimization (termed the schema-level optimization) in multidatabase environments. The results provide a new dimension of enhancement for the capability of a query optimizer in multidatabase systems.
9335901
Performance upgrade for large object bases using disk arrays
The authors propose the use of multiple disks to increase the bandwidth of disk I/O so as to alleviate the I/O bottleneck problem existed in OODB applications. However, a major difficulty in using multiple disks for the support of OODBs is that an object may reference or be referenced by other objects through associations. This requires that the search of objects be sequential through the association links, which is sometimes referred to as the navigational search of objects in an object base. This restriction limits the concurrency in object retrieval and invalidates the use of multiple disks. Techniques such as clustering/indexing of objects do not help to resolve this problem. By using a two-phase query processing strategy previously proposed by them, objects of interest can be accessed in parallel from multiple disk. The aim of the paper is to design a probability-based evaluation model to estimate the performance of using multiple disks and to compare it with a single disk system. The result shows that the scheme is viable and a significant improvement is achieved while multiple disks are used.
33610569
Compression-based broadcast strategies in wireless information systems
Data delivery is through broadcast in wireless information systems due to the asymmetric communication property. However, broadcasting data easily wastes large access time because the large amount of data pages needs to be broadcast. In this paper we propose three compression-based strategies considering access order to reduce access time. Then, the expected access time of three proposed strategies is also derived by using the probability model. Our analytic and experimental results show that the compression-based broadcast strategies can dramatically reduce the access time for mobile users (MU).
5320438
On quality of service optimization with discrete QoS options
We present a QoS management framework that enables us to quantitatively measure QoS, and to analytically plan and allocate resources. In this model, end users' quality preferences are considered when system resources are apportional across multiple applications such that the net utility that accrues to the end-users is maximized. We previously worked with continuous QoS dimensions, and assumed that the utility gained by improvements along a QoS dimension were always representable by concave functions. In this paper we relax both assumptions. One, we support discrete QoS operating points. Two, we make no assumptions about the concavity of the utility functions. Using these as the basis, we tackle the problem of maximizing system utility by allocating a single finite resource to satisfy the QoS requirements of multiple applications along multiple QoS dimensions. We present two near-optimal algorithms to solve this problem. The first yields an allocation within a known bounded distance from the optimal solution, and the second yields an allocation whose distance from the optimal solution can be explicitly controlled by the QoS manager, We compare the run-times of these near-optimal algorithms and their solution quality relative to the optimal allocation, which in turn is computed using dynamic programming. These detailed evaluations provide practical insight into which of these algorithms can be used online in real-time systems.
42435746
Efficiently supporting hard/soft deadline transactions in real-time database systems
As in other application areas, there is an increasing need for managing a large amount of data in the real-time area. This need gave birth to a system called a real-time database system (RTDBS) that provides database operations with timing constraints. One typical timing constraint in an RTDBS is temporal consistency that states that a transaction must read temporally valid data objects. This requires the data objects to be updated repeatedly. This paper proposes three novel schemes that aim to minimize the number of updates of data objects needed for guaranteeing the temporal consistency requirements of transactions with hard-deadlines. The three guarantee schemes differ from each other in the amount of updates and the implementation complexity. This paper also gives a framework for integrating transactions with soft-deadlines into the three guarantee schemes.
20686264
Finite-Horizon Scheduling of Radar Dwells with Online Template Construction
Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism that is inherent in schedulers that assume a task executes forever. We also develop the notion of modular schedule update which allows portions of a schedule to be altered without affecting the entire schedule, thereby simplifying the scheduler. Through extensive simulations, we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline.
15046188
Human Motion Synthesis by Motion Manifold Learning and Motion Primitive Segmentation
We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date are represented using a low dimensional representation by topology preserving network, which maps similar motion instances to the neighborhood points on the low dimensional motion manifold. Nonlinear manifold learning between a low dimensional manifold representation and high dimensional motion data provides a generative model to synthesize new motion sequence by controlling trajectory on the low dimensional motion manifold. We segment motion primitives by analyzing low dimensional representation of body poses through motion from motion captured data. Clustering techniques like k-means algorithms are used to find motion primitives after dimensionality reduction. Motion dynamics in training sequences can be described by transition characteristics of motion primitives. The transition matrix represents the temporal dynamics of the motion with Markovian assumption. We can generate new motion sequences by perturbing the temporal dynamics
40821829
Service class based online QoS management in surveillance radar systems
Many application level qualities are functions of available computation resources. Recent studies have handled the computation resource allocation problem to maximize the overall application quality. However such QoS problem is fundamentally a multi-dimensional optimization problem that requires extensive computation. Therefore, online usage of optimization procedures may significantly reduce the computation resource available for applications. This raises the question of how to best use the optimization procedures for dynamic real-time task sets. This paper proposes a method called service classes configuration to address the QoS problem with dynamic arrival and departure of tasks. A simplified radar application is used as an illustrative example.