To the best of our knowledge, this is the first algorithm that can construct a structure with all these properties using small communication messages (at most 13n total messages, each with O(logn) bits) and small computation cost, where n is the number of wireless nodes.
We analytically prove that the node degree of the IMRG is at most 6, it is connected and planar, and more importantly, the total edge length of the IMRG is within a constant factor of that of the minimum spanning tree. Each node u keeps an edge uv only if uv is in the constructed minimum spanning tree. Each node then collects all its one-hop neighbors and the two-hop neighbors who have RNG edges to some of its one-hop neighbors, and builds an Euclidean minimum spanning tree of these nodes. In the construction algorithm, each node first builds a modified relative neighborhood graph (RNG'), and then informs its one-hop neighbors its incident edges in RNG'. We propose a new localized structure, namely, Incident MST and RNG Graph (IMRG), for topology control and broadcasting in wireless ad hoc networks. We describe the design space of multihoming load balancing systems, discuss the tradeoffs involved in load balancing and fail-over implementation strategies, and present quantitative performance measurements collected on a commercial multihoming load balancing system. Although there exist several commercial multihoming load balancing products in the marketplace, very little is published about the design tradeoffs and their performance implications. The key enabling technology for this revolution is multihoming load balancing, which spreads an enterprise's Internet traffic among multiple access links to increase the aggregate throughput, and diverts traffic away from non-functional links when they fail. One emerging theme is the replacement of dedicated lines based on frame relay or ISDN technologies with multiple inexpensive ADSL/cable TV links each of which potentially is subscribed from a different ISP. The growing popularity of consumer broadband connection technology, in particular cable TV and ADSL, has started a quiet revolution that will reshape the Internet connectivity solutions for commercial enterprises. Simulations validate the theoretical results and show that the bounds are much better in practice. We tested our algorithms on both uniformly random distributions of nodes, and on a realistic distributions of nodes in an urban setting. We also perform extensive simulations of our algorithms. In particular, we show that NNT produces a close approximation to the MST, and they can be maintained dynamically with polylogarithmic number of rearrangements under node insertions/deletions. We assume that the nodes are uniformly distributed in a unit square and show provable bounds on the performance with respect to both the quality of the spanning tree produced and the energy needed to construct them. Motivated by these considerations, we design and analyze a class of simple and local distributed algorithms called nearest neighbor tree (NNT) algorithms for energy-efficient construction of MSTs in a wireless ad hoc setting. In such networks, a sensor has very limited power, and any algorithm needs to be simple, local, and energy efficient for being practical. While there are distributed algorithms for the MST problem, these algorithms require relatively large number of messages and time this makes these algorithms impractical for resource-constrained networks such as ad hoc wireless sensor networks. These features make it suitable for large-scale, multidomain, heterogeneous environments, such as computational grids. The proposed approach also allows for dynamic resource aggregation in a nondedicated computational environment. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institutes HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm.
This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years.
In molecular biology, it is often desirable to find common properties in large numbers of drug candidates.
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