29616158
Improved decremental algorithms for maintaining transitive closure and all-pairs shortest paths
This paper presents improved algorithms for the following problem: given an unweighted directed graph G(V,E) and a sequence of on-line shortest-path/reachability queries interspersed with edge-deletions, develop a data-structure that can answer each query in optimal time, and can be updated efficiently after each edge-deletion. The central idea underlying our algorithms is a scheme for implicitly storing all-pairs reachability/shortest-path information, and an efficient way to maintain this information. Our algorithms are randomized and have one-sided inverse polynomial error for query.
13425332
A generalization of the 0-1 principle for sorting
The traditional zero-one principle for sorting networks states that "if a network with n input lines sorts all 2n binary sequences into nondecreasing order, then it will sort any arbitrary sequence of n numbers into nondecreasing order". We generalize this to the situation when a network sorts almost all binary sequences and relate it to the behavior of the sorting network on arbitrary inputs. We also present an application to mesh sorting.
32334601
Finding an Approximate Median with High Probability in Constant Parallel Time
Given n elements from a totally ordered set we outline a method for choosing an element whose rank is γn for some 0 0.
10562059
Improved decremental algorithms for maintaining transitive closure and all-pairs shortest paths
We present improved algorithms for maintaining transitive closure and all-pairs shortest paths/distances in a digraph under deletion of edges.(MATH) For the problem of transitive closure, the previous best known algorithms, for achieving O(1) query time, require O(\min(m, \frac{n^3}{m}))$ amortized update time, implying an upper bound of O(n^{\frac{3}{2}})$ on update time per edge-deletion. We present an algorithm that achieves $O(1)$ query time and O(n \log^2n + \frac{n^2}{\sqrt{m}}{\sqrt{\log n}})$ update time per edge-deletion, thus improving the upper bound to O(n^{\frac{4}{3}}\sqrt[3]{\log n})$.(MATH) For the problem of maintaining all-pairs shortest distances in unweighted digraph under deletion of edges, we present an algorithm that requires O(\frac{n^3}{m} \log^2 n)$ amortized update time and answers a distance query in O(1) time. This improves the previous best known update bound by a factor of log n. For maintaining all-pairs shortest paths, we present an algorithm that achieves O(\min(n^{\frac{3}{2}} \sqrt{\log n}, \frac{n^3}{m} \log ^2n))$ amortized update time and reports a shortest path in optimal time (proportional to the length of the path). For the latter problem we improve the worst amortized update time bound by a factor of O(\sqrt{\frac{n}{\log n}})$.(MATH) We also present the first decremental algorithm for maintaining all-pairs (1+ε) approximate shortest paths/distances, for any ε > 0, that achieves a sub-quadratic update time of O(n log2n + \frac{n^2}{\sqrt{\epsilon m}}\sqrt{\log n})$ and optimal query time.Our algorithms are randomized and have one-sided error for query (with probability O(1/nc) for any constant c).
9302549
Planar Graph Blocking for External Searching

AbstractWe present a new scheme for storing a planar graph in external memory so that any online path can be traversed in an I-O efficient way. Our storage scheme significantly improves the previous results for planar graphs with bounded face size. We also prove an upper bound on I-O efficiency of any storage scheme for well-shaped triangulated meshes. For these meshes, our storage scheme achieves optimal performance.

1068367
An Efficient Output-Size Sensitive Parallel Algorithm for Hidden-Surface Removal for Terrains
Abstract. We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log 4 n) steps on the CREW PRAM model with a work bound of O((n+k) \polylog ( n)) where n and k are the input and output sizes, respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data structures is somewhat novel in the context of parallel algorithms.
12702435
Robustness of reputation-based trust: boolean case
We consider the problem of user agents selecting processor agents to processor tasks. We assume that processor agents are drawn from two populations: high and low-performing processors with different averages but similar variance in performance. For selecting a processor, a user agent queries other user agents for their high/low rating of different processors. We assume that a known percentage of "liar" users, who give inverse estimates of processors. We develop a trust mechanism that determines the number of users to query given a target guarantee threshold likelihood of choosing high-performance processors in the face of such "noisy" reputation mechanisms. We evaluate the robustness of this reputation-based trusting mechanism over varying environmental parameters like percentage of liars, performance difference and variances for high and low-performing agents, learning rates, etc.
6087385
Effect of joining decisions on peer clusters
Super-peer networks have been proposed to address the issue of search latency and scalability in traditional peer-to-peer (P2P) networks. In a super-peer network, instead of having a fully distributed systems of peer nodes with similar or comparable capabilities, some nodes that possess considerable computing power and resources are designated as super-peers. Each super-peer acts as a server for multiple client peers under it. This hierarchical structure of a super-peer network improves the performance of a super-peer network over traditional P2P networks by handling most search queries between the few super-peer nodes, thereby reducing overall network traffic and improving search latency. In this paper, we address the problem of mutual selection by super-peers and client peers. In particular, we evaluate alternative decision functions used by super-peers to allow new client peers to join the cluster of clients under it. We experiment with peers with known resources and demands. By formally representing and reasoning with capability and query distributions, we develop peer-selection functions that either promote concentration or diversification of capabilities within a cluster. We evaluate the effectiveness of these different selection functions for different environments where peer capabilities are aligned or are independent of their queries. We offer insight and analysis on the effects on inter and intra-peer bandwidth consumption which will allow a super-peer to adopt appropriate peer-selection functions given their expectations about the environment.
1281859
Unsupervised Surrogate Agents and Search Bias Change in Flexible Distributed Scheduling
Computational infrastructures for cooperative work should contain embedded agents for handling many routine tasks (Galegher, Kraut, Egldo 1990), but as the number of agents increases and the agents become geographically and/or conceptually dispersed, supervision of the agents will become increasingly problematic. We argue that agents should be provided with deep domain knowledge that allows them to make justifiable decisions, rather than shallow models of users to mimic. In this paper, we use the application domain of distributed meeting scheduling to investigate how agents embodying deeper domain knowledge can choose among alternative strategies for searching their calendars in order to create flexible schedules within reasonable cost.
16333487
Playback restart in interactive streaming video applications
Low latency is crucial in networked multimedia applications such as on-demand streaming audio and video. In this paper we consider the problem of restarting or resuming playback following an interactive operation such as fast forward, rewind, or indexed jump in stored on-demand video. We present two approaches to restart playback after an interactive operation, and develop algorithms to compute the latencies incurred in restarting playback. Using long MPEG-1 traces, with an optimal smoothing technique to transmit data for regular playback, we demonstrate that the latencies incurred under our approaches are very small. We next examine the latencies incurred when restarting playback in a video server under two policies for sharing its bandwidth: (a) one in which only regular playback bandwidth is available to restart playback and (b) one in which additional free server bandwidth (if any) is accessible. We find playback restart latencies to be similarly low under both policies, suggesting that the simpler approach (a) is sufficient.
656475
Evaluating concurrent reinforcement learners
Assumptions underlying the convergence proofs of reinforcement learning (RL) algorithms like Q-learning are violated when multiple interacting agents adapt their strategies online as a result of learning. Empirical investigations in several domains, however, have produced encouraging results. We evaluate the convergence behavior of concurrent reinforcement learning agents using game matrices as studied by Claus and Boutilier (1998). Variants of simple RL algorithms are evaluated for convergence under increasing number of agents per group, scale up of game matrix size, delayed feedback and game matrix characteristics. Our results show surprising departures from that observed by Claus and Boutilier, particular for larger problem sizes.