9657581
k-anycast game in selfish networks
Conventionally, the majority of network routing protocols assume that every network terminal or link forwards data for others without any deviation. However, this may not be true when the terminals or links are owned by individual selfish users, who always tries to maximize their own benefits instead of faithfully following a prescribed protocol. In this paper, we propose a new routing protocol, called k-anycast routing, that works well even if network links (or terminals or both) are selfish. In our protocol, the source node first finds a tree that spans k receivers out of a set of possible receivers and pay the relay links to compensate their costs. We prove that every relay link follows the routing protocol: it maximizes its profit when it declares its actual cost
16100691
Design multicast protocols for non-cooperative networks
Conventionally, most network protocols assume that the network entities that participate in the network activities will always behave as instructed. However, in practice, most network entities will try to maximize their own benefits instead of altruistically contribute to the network by following the prescribed protocols, which is known as selfish. Thus, new protocols should be designed for the non-cooperative network, which is composed of selfish entities. In this paper, we specifically show how to design strategyproof multicast protocols for non-cooperative networks such that these selfish entities will follow the protocols out of their own interests. By assuming that a group of receivers is willing to pay to receive the multicast service, we specifically give a general framework to decide whether it is possible, and how if possible to transform an existing multicast protocol to a strategyproof multicast protocol. We then show how the payments to those relay entities are shared fairly among all receivers so that it encourages collaboration among receivers. As a running example, we show how to design the strategyproof multicast protocol for the currently used core-based multicast structure. We also conduct extensive simulations to study the relations between payment and cost of the multicast structure.
41218825
Relaxed game chromatic number of graphs
This paper discusses a coloring game on graphs. Let k, d be non-negative integers and C a set of k colors. Two persons, Alice and Bob, alternately color the vertices of G with colors from C, with Alice having the first move. A color i is legal for an uncolored vertex x if by coloring x with color i, the subgraph of G induced by those vertices of color i has maximum degree at most d. Each move of Alice or Bob colors an uncolored vertex with a legal color. The game is over if either all vertices are colored, or no more vertices can be colored with a legal color. Alice's goal is to produce a legal coloring which colors all the vertices of G, and Bob's goal is to prevent this from happening. We shall prove that if G is a forest, then for k = 3, d ≥ 1, Alice has a winning strategy. If G is an outerplanar graph, then for k = 6 and d ≥ 1, Alice has a winning strategy.
14611333
TAR: temporal association rules on evolving numerical attributes
Data mining has been an area of increasing interest. The association rule discovery problem in particular has been widely studied. However, there are still some unresolved problems. For example, research on mining patterns in the evolution of numerical attributes is still lacking. This is both a challenging problem and one with significant practical applications in business, science, and medicine. In this paper we present a temporal association rule model for evolving numerical attributes. Metrics for qualifying a temporal association rule include the familiar measures of support and strength used in traditional association rule mining and a new metric called density. The density metric not only gives us a way to extract the rules that best represent the data, but also provides an effective mechanism to prune the search space. An efficient algorithm is devised for mining temporal association rules, which utilizes all three thresholds (especially the strength) to prune the search space drastically. Moreover, the resulting rules are represented in a concise manner via rule sets to reduce the output size. Experimental results on real and synthetic data sets demonstrate the efficiency of our algorithm.
385307
STING: A Statistical Information Grid Approach to Spatial Data Mining
Spatial data mining, i.e., discovery of interesting characteristics and patterns that may implicitly exist in spatial databases, is a challenging task due to the huge amounts of spatial data and to the new conceptual nature of the problems which must account for spatial distance. Clustering and region oriented queries are common problems in this domain. Several approaches have been presented in recent years, all of which require at least one scan of all individual objects (points). Consequently, the computational complexity is at least linearly proportional to the number of objects to answer each query. In this paper, we propose a hierarchical statistical information grid based approach for spatial data mining to reduce the cost further. The idea is to capture statistical information associated with spatial cells in such a manner that whole classes of queries and clustering problems can be answered without recourse to the individual objects. In theory, and confirmed by empirical studies, this approach outperforms the best previous method by at least an order of magnitude, especially when the data set is very large.
9332288
Choosability, Edge Choosability, and Total Choosability of Outerplane Graphs
Let ?l(G),?l? (G),?l?? (G), and ?(G) denote, respectively, the list chromatic number, the list chromatic index, the list total chromatic number, and the maximum degree of a non-trivial connected outerplane graph G. We prove the following results. (1) 2 ??l(G) ? 3 and?l (G) = 2 if and only if G is bipartite with at most one cycle. (2)?(G) ??l?(G) ??(G) + 1 and?l? (G) =?(G) + 1 if and only if G is an odd cycle. This proves the well-known list edge coloring conjecture for outerplane graphs. (3)?l??(G) =?(G) + 1 if ?(G) ? 4 and ?l??(G) ? 5 if ?(G) ? 3. This proves a conjecture of O. V. Borodin, A. V. Kostochka and D. R. Woodall, List edge and list total coloring of multigraphs, J. Comb. Theory B, 71 (1997), 184?204 for outerplane graphs.
2396831
Mining coherent patterns from heterogeneous microarray data
Microarray technology is a powerful tool for geneticists to monitor interactions among tens of thousands of genes simultaneously. There has been extensive research on coherent subspace clustering of gene expressions measured under consistent experimental settings. However, these methods assume that all experiments are run using the same batch of microarray chips with similar characteristics of noise. Algorithms developed under this assumption may not be applicable for analyzing data collected from heterogeneous settings, where the set of genes being monitored may be different and expression levels may be not directly comparable even for the same gene. In this paper, we propose a model, F-cluster, for mining subspace coherent patterns from heterogeneous gene expression data. We compare our model with previously proposed models. We analyze the search space of the problem and give a naïve solution for it.