Abstract. We prove that finding a rooted subtree with at least k leaves in a digraph is a fixed parameter tractable problem. A similar result holds for finding rooted spanning trees with many leaves in digraphs from a wide family L that includes all strong and acyclic digraphs. This settles completely an open question of Fellows and solves another one for digraphs in L. Our algorithms are based on the following combinatorial result which can be viewed as a generalization of many results for a ‘spanning tree with many leaves ’ in the undirected case, and which is interesting on its own: If a digraph D ∈ L of order n with minimum in-degree at least 3 contains a rooted spanning tree, then D contains one with at least (n/2) 1/5 − 1 leaves. 1

The problem of minimum cost in-network fusion of measurements, collected from distributed sensors via multihop routing is considered. A designated fusion center performs an optimal statistical-inference test on the correlated measurements, drawn from a Markov random field. Conditioned on the delivery of a sufficient statistic for inference to the fusion center, the structure of optimal routing and fusion is shown to be a Steiner tree on a transformed graph. This Steiner-tree reduction preserves the approximation ratio, which implies that any Steinertree approximation can be employed for minimum cost fusion with the same approximation ratio. The proposed fusion scheme involves routing packets of two types viz., raw measurements sent for local processing, and aggregates obtained on combining these processed values. The performance of heuristics for minimum cost fusion are evaluated through theory and simulations, showing a significant saving in routing costs, when compared to routing all the raw measurements to the fusion center.

Abstract. Initial deployments of wireless sensor networks (WSNs) were based on a many-to-one communication paradigm, where a single sink collects data from a number of data sources. Recently, however, scenarios with multiple sinks are increasingly being proposed, e.g., to deal with actuator nodes or to support high-level programming abstractions. The resulting many-to-many communication makes the existing solutions for single-sink scenarios inefficient. In this paper, we propose a scheme for routing data efficiently from multiple sources to multiple sinks. We first study the problem from a theoretical standpoint, by mapping it to the multi-commodity network design problem. This allows us to derive an optimal solution that, albeit based on global knowledge and therefore impractical, provides us with a theoretical lower bound to evaluate decentralized solutions against. Then, we propose our own decentralized scheme, based on a periodic adaptation of the message routes aimed at minimizing the number of network links exploited. The resulting protocol is simple and easily implementable on WSN devices. The evaluation of our implementation shows that our protocol generates 50 % less overhead than the base scheme without adaptation, a result close to the theoretical optimum we derived. 1

In the classical approach, the problem of distributed statistical inference and the problem of minimum cost routing of the measurements to the fusion center are treated separately. Such schemes cannot exploit the “inherent” saving in routing costs arising from data reduction in a sufficient statistic for inference. Our approach is to conduct in-network processing of the likelihood function which is the minimal sufficient statistic and deliver it to the fusion center for inference. We employ the Markov random field (MRF) model for spatial correlation of sensor data. The structure of the likelihood function is well known for a MRF from the famous Hammersley-Clifford theorem. Exploiting this structure, we show that the minimum cost routing for computation and delivery of the likelihood function is a Steiner tree on a transformed graph. This Steiner-tree reduction preserves the approximation ratio, which implies that any Steinertree approximation can be employed for minimum cost fusion with the same approximation ratio. In this chapter, we present an overview of this approach to minimum cost fusion.

The classical framework on distributed inference considers a set of nodes taking measurements and a fusion center making the final decision on the underlying phenomenon, without dealing with the issue of transporting the measurements to the fusion center. Such an approach introduces significant overhead in communication. Communicating all the raw data for inference is not scalable: in this case, the per-node average energy consumption and the total bandwidth requirement become unbounded as the network grows. We design scalable algorithms for two scenarios with guarantees for inference whose communication requirements and complexity are bounded even as the network grows. This is achieved through distributed computation of a sufficient statistic, which results in reduction of data dimensionality while ensuring no loss in inference accuracy at the fusion center. The first scenario deals with multihop routing and fusion of spatially correlated measurements, incorporated through a Markov random field model. The second scenario deals with design of medium-access control (MAC) with the aim of computing a sufficient statistic

mosaicing graph, panoramic image, spanning tree, spatial cluster

In this paper, we discuss the problem of reoptimization of Steiner tree. We are given an instance of Graph and also an optimal Steiner tree of it. If some changes occurs later on in the given graph. New optimal Steiner tree is to be determine, this process is known as re optimization. We consider two cases of change: one is addition of a new edge and second is, Deletion of an existing edge. For both the cases, we provide approximation algorithms with corresponding approximation ratio equal to (1+δ) where 0<δ<1.

Network congestion and signal quality degradation are the major problems of the Global System for Mobile communication (GSM) most especially as the number of customers increases. They are issues that constantly and continuously demand for further researches to improve network performance. Congestion in various systems has always been tackled with various attempts, all of which falls

The parameterized max-leaf problem on undirected graphs (which is also named the max-leaf spanning-tree problem) is formulated as follows: given an undirected graph G and a parameter k, either construct a spanning tree with at least k leaves for G or report ‘No ’ if such a tree does not exist. The problem also has a version for directed graphs that is named the max-leaf out-branching problem. In this paper, we present a simple branch-and-search algorithm of running time O ∗ (4 k) that solves the max-leaf out-branching problem. This significantly improves the previous best algorithm for the problem that runs in time O ∗ (2 O(k log k)). Our main contributions consist of new observations on the combinatorial structures of the problem and the introduction of a new algorithmic technique that provides new perspectives for design and analysis of parameterized algorithms. Our algorithm of running time O ∗ (4 k) is also applicable to the simpler max-leaf spanning-tree problem, improving the previous best algorithm of running time O ∗ (6.75 k) for the problem. 1

A main objective of this paper is using artificial intelligence technique to web service agents and increase the efficiency of the agent communications. In recent years, web services have played a major role in computer applications. Web services are essential, as the design model of applications are dedicated to electronic businesses. This model aims to become one of the major formalisms for the design of distributed and cooperative applications in an open environment (the Internet). Current commercial and research-based efforts are reviewed and positioned within these two fields. A web service as a software system designed to support interoperable machineto-machine interaction over a network. It has an interface described in a machine-process able format (specifically Web Services Description Language WSDL). Other systems interact with the web service in a manner prescribed by its description using SOAP messages, typically conveyed using HTTP with an XML serialization in conjunction with other Web-related standards. Particular attention is given to the application of AI techniques to the important issue of WS composition. Within the range of AI technologies considered, we focus on the work of the Semantic Web and Agent-based communities to provide web services with semantic descriptions and intelligent behavior and reasoning capabilities. Re-composition of web services is also considered and a number of adaptive agent approaches are introduced and implemented in publication domain with three dimensional databases and one of the areas of work is eCommerce.