39362526
Main memory database recovery algorithms and their performance
In main memory systems recovery becomes more complex mainly due to the volatility of main memory and the elimination of the separation of data storage (disk) and data processing locations (main memory). In a disk based database system, it is the disk copy that represents the stable database restored after a system failure; but in MDBSs, the main memory copy of the database must be recovered. The paper discusses the recovery issues in MDBSs and presents a somewhat detailed performance study of two recovery algorithms, one using a shadow approach and the other update-in-place.<<ETX>>
45908534
KRISHNA - Concurrency Control Algorithms based on Dynamic Attributes
Three new concurrency control mechanisms that utilizes the dynamic attribute of concurrent transactions for resolving conflicts are presented. Our study shows that their performance is superior to all well-known two-phase concurrency control mechanisms. There are a large number of such algorithms but we report our findings since our approach has some unique features worth exploring.
368036
Data Organization Issues for Location-Dependent Queries in Mobile Computing
We consider queries which originate from a mobile unit and whose result depends on the location of the user who initiates the query. Example of such a query is How many people are living in the region I am currently in?" We execute such queries based on location-dependent data involved in their processing. We build concept hierarchies based on the location data. These hierarchies define mapping among different granularities of locations. One such hierarchy is to generate domain knowledge about the cities that belong to a state. The hierarchies are used as distributed directories to assist in finding the database or relation that contains the values of the location-dependent attribute in a particular location. We extend concept hierarchies to include spatial indexes on the location-dependent attributes. Finally, we discuss how to partition and replicate relations based on the location to process the queries efficiently. We briefly discuss the implementation issues.
14504228
Location dependent data and its management in mobile databases
In traditional ways of managing data, the relationship between the data and the geographical location of the organization it represents, is usually ignored. In wireless computing this property of "location transparency" is in fact often replaced by a "location dependency" property. Furthermore, the mode of issuing queries (the geographical location where the queries originate, the way they are issued, etc.) on such data determines the outcome. Location dependent data is data whose value depends on its location. The objective of the paper is to introduce this topic and spawn further related research.
18803353
Performance of Multiversion and Distributed Two-Phase Locking Concurrency Control Mechanisms in Distributed Databases
In this paper, we have presented a detailed simulation study of a distributed multiversion and a distributed two-phase locking concurrency control mechanism (CCM). Our experiment concentrated on measuring the effect of message overhead, read:write ratios, data partitioning, and partial replication on the performance of these mechanisms. The effect of these parameters has not been investigated in any previous work. We simultated a blind-write model for two reasons: (a) all other works studied the behavior of multiversion CCMs under read-before-write model and observed a similar result, and (b) the performance of any multiversion CCM has not been studied under a blind-write model. A blind-write model is not unrealistic, and intutively the multiversion should provide much better performance. We observed that multiversion outperforms wound-wait (WW) in both partitioned and partially replicated databases. Multi version (MV) handles read-only and write-only transactions efficiently, and after a certain write percentage the throughput improves with this percentage. The message overhead progressively becomes less significant as the MPL (multiprogramming level) increases, indicating that in a heavily loaded system the throughput is least sensitive to message cost. We found that in the partially replicated case, 50% write does not show the lowest performance, as observed in the partitioned case.
18344625
Concurrent operations on extendible hashing and its performance
Extendible hashing is a dynamic data structure which accommodates expansion and contraction of any stored data efficiently. In this article, an algorithm has been developed for managing concurrent operations on extendible hashing by achieving optimal memory utilization by supporting directly expansion and contraction, page split, and merge. The results of this study have been encouraging in the sense that it seems to provide a higher degree of concurrency compared to other algorithms on an extendible hash file.
7496057
Hybrid control of formations of robots
We describe a framework for controlling a group of nonholonomic mobile robots equipped with range sensors. The vehicles are required to follow a prescribed trajectory while maintaining a desired formation. By using the leader-following approach, we formulate the formation control problem as a hybrid (mode switching) control system. We then develop a decision module that allows the robots to automatically switch between continuous-state control laws to achieve a desired formation shape. The stability properties of the closed-loop hybrid system are studied using the Lyapunov theory. We do not use explicit communication between robots; instead we integrate optimal estimation techniques with nonlinear controllers. Simulation and experimental results verify the validity of our approach.
5480787
Parallel Formulations of Decision-Tree Classification Algorithms
Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets in reasonable amount of time. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. In this paper, we present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations. One is based on Synchronous Tree Construction Approach and the other is based on Partitioned Tree Construction Approach. We discuss the advantages and disadvantages of using these methods and propose a hybrid method that employs the good features of these methods. We also provide the analysis of the cost of computation and communication of the proposed hybrid method. Moreover, experimental results on an IBM SP-2 demonstrate excellent speedups and scalability.
30844152
Multiple cooperating mobile manipulators
The main goal of the paper is to present a framework and basic control algorithms for coordinating a small team of robots in tasks that involve grasping large objects and transporting them in a two-dimensional environment with obstacles. Each robot consists of a mobile platform and an arm. Some arms are passive while others are active. Our previous work (1998) addressed the manipulator design, the architecture, and the communication between robots. In this paper we address the control of the manipulators, the coordination between the platforms for a team of two or three cooperating robots, and the handling of flexible large objects.
38254367
Parallel formulations of decision-tree classification algorithms
Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing classification decision trees are desirable for dealing with large data sets in reasonable amount of time. Algorithms for building classification decision trees have a natural concurrency, but are difficult to parallelize due to the inherent dynamic nature of the computation. We present parallel formulations of classification decision tree learning algorithm based on induction. We describe two basic parallel formulations. One is based on Synchronous Tree Construction Approach and the other is based on Partitioned Tree Construction Approach. We discuss the advantages and disadvantages of using these methods and propose a hybrid method that employs the good features of these methods. Experimental results on an IBM SP-2 demonstrate excellent speedups and scalability.
40202530
Decentralized control of cooperating mobile manipulators
This paper addresses the design and control of autonomous mobile platforms manipulating and transporting a grasped object. Each platform is equipped with a manipulator arm. In order to hold an object in a stable grasp, the arms have to apply and maintain appropriate contact forces to ensure force closure. We describe an architecture and a real time control system that allow the coordinated control of multiple, heterogeneous, mobile manipulators. In this architecture, a lead robot plans, based on available sensory information, and follows a suitable trajectory. The other robots follow a desired formation with respect to the leader while maintaining a stable grasp. There are three main contributions in this paper. We present the real time control system and our approach to rapidly prototype the control code. We describe a novel, forklift-like arm and a control scheme that allows us to easily control the Cartesian stiffness or impedance. Finally, we describe the details of an experimental testbed and results that demonstrate the robustness of the control scheme.