41223157
Best Movement of Mobile Agent in Mobile Computing Systems
Retrieving data using mobile agents gains popularity due to the advance of mobile computing techniques. However, the transmission of wireless communication is still unreliable and bandwidth-limited. This paper investigates this issue and tries to find the most suitable location for a mobile agent in a vast network. We first propose a mechanism and operations for the support of this strategy. We then develop an analysis model to estimate the optimal location for a mobile agent.
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.
31930663
Minimization of resource consumption for multidatabase query optimization
Due to the autonomy of individual databases, a multidatabase system (MDBS) has no control over the task execution within each database system. This complicates the issue of query optimization in a MDBS. Past researchers tackled this problem mainly by regenerating the cost model of each participating database systems. However a completely autonomous participating database system does nor own the information (data) as well as the mechanism (software) for converting data of one database to another to resolve the data type conflict problems that can occur in any MDBS environment. In addition, unpredictable factors that can drastically deviate the accuracy of a regenerated cost model (in the past research) come into play at unknown time. This confines the processing of an intersite operation (such as a join over two relations of different databases) to the MDBS only. The participating database systems will not be able to share the workload of the MDBS under this circumstance. Hence, minimizing the consumption of system resources of the MDBS is an urgent problem. The authors propose three scheduling algorithms that are used in the MDBS to reduce the processing cost of a multidatabase query. A major difference between the strategies and the past methods is that ours do not require the knowledge of the cost models of the participating databases.
20308502
Object signatures for supporting efficient navigation in object-oriented databases
Most methods that have been proposed to improve query processing in object-oriented databases are designed for the aggregation hierarchy. Although the structure of the generalization hierarchy is similar to the aggregation hierarchy, techniques developed for the aggregation hierarchy cannot fully use the characteristics of the generalization hierarchy to improve performance. We devise a new object signature for the generalization hierarchy. The object signature consists of two parts: a reference signature and a structure signature. The former can be used to eliminate objects that do not match the nested predicates specified in the query, and the latter can be used to eliminate objects that do not belong to the target classes. We propose some processing methods using the object signatures for queries that involve generalization hierarchies. In addition, we define cost models of the object signature and then compare the performance of the traditional query processing method with the object signature method. The results show that using the object signatures can effectively reduce the number of disk accesses in a query.
18796888
Design and Performance Evaluation of Broadcast Algorithms for Time-Constrained Data Retrieval
We refer "time-constrained services" to those requests that have to be replied to within a certain client-expected time duration. If the answer cannot reach the client within this expected time, the value of the information may seriously degrade or even become useless. On-demand channels may not be able to handle all time-constrained services without degrading the performance. How to handle these services in broadcast channels becomes crucial to balance the load of wireless systems. In this paper, we study this problem and find the minimum number of broadcast channels required for such a task. Also, we propose solutions for this problem when the available channels are insufficient. Our performance result reveals that only a moderate number of channels is required to promote these time-constrained services
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.
8167367
Online QoS Optimization Using Service Classes 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 problems are fundamentally multi-dimensional optimization problems that require 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. In dynamic real-time systems, it is important to improve the performance by re-allocating the resources adapting to dynamic situations. However, the overhead of changing task parameters (i.e., algorithms and frequencies) for resource re-allocation is non-negligible in many applications. Thus, too frequent change of resource allocation may not be desirable. This paper proposes a method called service classes configuration to address the QoS problem with dynamic arrival and departure of tasks. The method avoids online usage of optimization procedures by offline designing templates (called service classes) of resource allocation, which will be adaptively used depending on online situations. The service classes are designed by best trading-off the accuracy of dynamic adaptation against the overhead of resource re-allocation. A simplified radar application is used as an illustrative example.
33337266
A genetic fuzzy agent using ontology model for meeting scheduling system
A Genetic Fuzzy Agent (GFA) using the ontology model for Meeting Scheduling System (MSS) is presented in this paper. The ontology model includes the Fuzzy Meeting Scheduling Ontology (FMSO) and the Fuzzy Personal Ontology (FPO) that can support to construct the knowledge base of the GFA. The FMSO is utilized to record and describe the meeting scheduling domain knowledge for the GFA. In addition, we implement a FMSO editor for generating the Web Ontology Language, OWL, that will be utilized by the GFA. Furthermore, the GFA will infer the suitable meeting time slots based on the ontology model. Moreover, it also adjusts the FMSO and FPO based on the results of the genetic learning mechanism for the next meeting. The experimental results show that our approach can effectively work for MSS.
33340433
An evolutionary approach to the job-shop scheduling problem
This paper focuses on the heuristic hybridization and the genetic search as a methodology to develop a computationally efficient heuristic for the job-shop scheduling problem (JSP). In order to adapt the JSP to a genetic algorithm (GA), the ASGPL (Active-Schedule Generation with a Priority-List) algorithm with a hopping scheme was proposed, and using a GA, an iterative schedule improvement procedure called EVIS (Evolutionary Intracell Scheduler) was designed. The genetic search in EVIS was parallelized with a model of subpopulations and migration. Without implementing any problem-tailored heuristic for the job-shop scheduling problem, EVIS was able to find optimal solutions to a number of different problem instances in reasonable computation time.<<ETX>>
8218476
A resource allocation model for QoS management
Quality of service (QoS) has been receiving wide attention in many research communities including networking, multimedia systems, real-time systems and distributed systems. In large distributed systems such as those used in defense systems, on-demand service and inter-networked systems, applications contending for system resources must satisfy timing, reliability and security constraints as well as application-specific quality requirements. Allocating sufficient resources to different applications in order to satisfy various requirements is a fundamental problem in these situations. A basic yet flexible model for performance-driven resource allocations can therefore be useful in making appropriate tradeoffs. We present an analytical model for QoS management in systems which must satisfy application needs along multiple dimensions such as timeliness, reliable delivery schemes, cryptographic security and data quality. We refer to this model as Q-RAM (QoS-based Resource Allocation Model). The model assumes a system with multiple concurrent applications, each of which can operate at different levels of quality based on the system resources available to it. The goal of the model is to be able to allocate resources to the various applications such that the overall system utility is maximized under the constraint that each application can meet its minimum needs. We identify resource profiles of applications which allow such decisions to be made efficiently and in real-time. We also identify application utility functions along different dimensions which are composable to form unique application requirement profiles. We use a video-conferencing system to illustrate the model.
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.