11619174
Provable algorithms for parallel sweep scheduling on unstructured meshes
We present provably efficient parallel algorithms for sweep scheduling on unstructured meshes. Sweep scheduling is a commonly used technique in radiation transport problems, and involves inverting an operator by iteratively sweeping across a mesh. Each sweep involves solving the operator locally at each cell. However, each direction induces a partial order in which this computation can proceed. On a distributed computing system, the goal is to schedule the computation, so that the length of the schedule is minimized. Several heuristics have been proposed for this problem; but none of the heuristics have worst case performance guarantees. We present a simple, almost linear time randomized algorithm which (provably) gives a schedule of length at most O(log/sup 2/n) times the optimal schedule for instances with n cells, when the communication cost is not considered, and a slight variant, which coupled with a much more careful analysis, gives a schedule of (expected) length O(logmlogloglogm) times the optimal schedule for m processors. These are the first such provable guarantees for this problem. We also design a priority based list schedule using these ideas, with the same theoretical guarantee, but much better performance in practice. We complement our theoretical results with extensive empirical analysis. The results show that (i) our algorithm performs very well and has significantly better performance guarantee in practice and (ii) the algorithm compares favorably with other natural and efficient parallel algorithms proposed in the literature [S. Pautz, (2002), S. Plimpton et al., (2001)].
47278894
Equilibria in Topology Control Games for Ad Hoc Networks
We study topology control problems in ad hoc networks where network nodes get to choose their power levels in order to ensure desired connectivity properties. Unlike most other work on this topic, we assume that the network nodes are owned by different entities, whose only goal is to maximize their own utility that they get out of the network without considering the overall performance of the network. Game theory is the appropriate tool to study such selfish nodes: we define several topology control games in which the nodes need to choose power levels in order to connect to other nodes in the network to reach their communication partners while at the same time minimizing their costs. We study Nash equilibria and show that—among the games we define—these can only be guaranteed to exist if each network node is required to be connected to all other nodes (we call this the Strong Connectivity Game). For a variation called Connectivity Game, where each node is only required to be connected (possibly via intermediate nodes) to a given set of nodes, we show that Nash equilibria do not necessarily exist. We further study how to find Nash equilibria with incentive-compatible algorithms and compare the cost of Nash equilibria to the cost of a social optimum, which is a radius assignment that minimizes the total cost in a network where nodes cooperate. We also study variations of the games; one where nodes not only have to be connected, but k-connected, and one that we call the Reachability Game, where nodes have to reach as many other nodes as possible, while keeping costs low. We extend our study of the Strong Connectivity Game and the Connectivity Game to wireless networks with directional antennas and wireline networks, where nodes need to choose neighbors to which they will pay a link. Our work is a first step towards game-theoretic analyses of topology control in wireless and wireline networks.
5797236
Strong edge coloring for channel assignment in wireless radio networks
We give efficient sequential and distributed approximation algorithms for strong edge coloring graphs modeling wireless networks. Strong edge coloring is equivalent to computing a conflict-free assignment of channels or frequencies to pairwise links between transceivers in the network
5622554
Equilibria in topology control games for ad hoc networks
We study topology control problems in ad hoc networks, where network nodes get to choose their power levels in order to ensure desired connectivity properties. Unlike most other work on this topic, we assume that the network nodes are owned by different entities, whose only goal is to maximize their own utility that they get out of the network without considering the overall performance of the network. Game theory is the appropriate tool to study such selfish nodes: we define several topology control games in which the nodes need to choose power levels in order to connect to other nodes in the network to reach their communication partners while at the same time minimizing their costs. We study Nash equilibria and show that -- among the games we define -- these can only be guaranteed to exist if all network nodes are required to be connected to all other nodes (we call this the Strong Connectivity Game). We give asymptotically tight bounds for the worst case quality of a Nash equilibrium in the Strong Connectivity Game and we improve these bounds for randomly distributed nodes. We then study the computational complexity of finding Nash equilibria and show that a polynomial-time algorithm finds Nash equilibria whose costs are at most a factor 2 off the minimum cost possible; for a variation called Connectivity Game, where each node is only required to be connected (possibly via intermediate nodes) to a given set of nodes, we show that answering the question, if a Nash equilibrium exists, is NP-hard, if the network graph satisfies the triangle inequality. For a second game called Reachability Game, where each node tries to reach as many other nodes as possible, while minimizing its radius, we show that 1+o(1)-approximate Nash equilibria exist for randomly distributed nodes. Our work is a first step towards game-theoretic analyses of ad hoc networks.
14506171
Optimal constrained graph exploration
We address the problem of exploring an unknown graph <i>G</i> = (<i>V</i>, <i>E</i>) from a given start node <i>s</i> with either a tethered robot or a robot with a fuel tank of limited capacity, the former being a tighter constraint. In both variations of the problem, the robot can only move along the edges of the graph, i.e, it cannot jump between non-adjacent vertices. In the tethered robot case, if the tether (rope) has length <i>l</i>, then the robot must remain within distance <i>l</i> from the start node <i>s</i>. In the second variation, a fuel tank of limited capacity forces the robot to return to <i>s</i> after traversing <i>C</i> edges. The efficiency of algorithms for both variations of the problem is measured by the number of edges traversed during the exploration. We present an algorithm for a tethered robot which explores the graph in <i>&Ogr;</i>(¦<i>E</i>¦) edge traversals. The problem of exploration using a robot with a limited fuel tank capacity can be solved with a simple reduction from the tethered robot case and also yields a <i>&Ogr;</i>(¦<i>E</i>¦) algorithm. This improves on the previous best known bound of <i>&Ogr;</i>(¦<i>E</i>¦ + ¦<i>V</i>¦log <sup>2</sup>¦<i>V</i>¦) in [4]. Since the lower bound for the graph exploration problems is ¦<i>E</i>¦, our algorithm is optimal, thus answering the open problem of Awerbuch, Betke, Rivest, and Singh [3].
1842716
Dynamic control of 3-D rolling contacts in two-arm manipulation
When two or more arms are used to manipulate a large object, it is necessary to maintain and control contacts between the object and effector(s) on one or more arms. The dynamic control of two arms manipulating a large object with rolling contacts is addressed. In the framework presented, the motion of the object as well as the loci of the contact points on the surface of the effectors and on the object can be directly controlled. The velocity and acceleration equations for three-dimensional rolling contacts are derived in order to obtain a dynamical model of the system. A nonlinear feedback algorithm that decouples and linearizes the system is used to demonstrate the control of rolling motion along each arm and the adaption of grasps to varying loads.<<ETX>>
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.
4677633
A Strategic Modeling Technique for Change Management in Organizations Undergoing BPR
Modern day organizations seek to rationalize, innovate, and adapt to changing environments, and circumstances as part of Business Process Reengineering (BPR) efforts. Irrespective of the process reengineering program selected, and the technique used to model, BPR brings with it the issues of organizational, and process changes, which involves managing organizational changes (also called “change management”). Change management is non-trivial, as organizational changes are difficult to accomplish. Though some attempt has been made to model change management in enterprise information systems using conventional conceptual modeling techniques, they have just addressed “what” a change process is like, and they don’t address “why” the process is the way it is. Our approach is novel in the sense that it presents an actor-dependency-based 5-phased technique for analyzing, and modeling early-phase requirements of change management that provides the motivations, intents, and rationales behind activities.
42935672
Performance Measurement of Main Memory Database Recovery Algorithms Based on Update-in-Place and Shadow Approaches
The authors present a performance study of two main memory database recovery algorithms, one using a shadow approach and the other update-in-place. The results show that in main memory databases, shadow approach performs better than update-in-place. The authors introduce minor improvements to the shadow scheme and show that the modified algorithm does show further performance improvement. >
2804750
A Timeout-Based Mobile Transaction Commitment Protocol
We investigate transaction commit in Mobile Database Systems (MDS) and develop a commitment protocol based on "timeout" approach. Timeout approach is universally used to reach a decision as a last option in all message oriented systems. With this approach we have minimized the use of wireless message cost in commiting transactions.