Suermondt, H.J. and G.F. Cooper, Initialization for the method of conditioning in Bayesian belief networks (Research Note), Artificial Intelligence 50 (1991) 83-94. The method of conditioning allows us to use Pearl's probabilistic-inference algorithm in multiply connected belief networks by instantiating a subset of the nodes in the network, the loop cutset. To use the method of conditioning, w...

In this article we develop probabilistic algorithms for estimating the number of active nodes in a multicomputer system which consists of independent computers that are interconnected by a communication network. The algorithms are based on routine exchange of messages among the nodes of the multicomputer. using random routing. We show that each active node can find an €-estimate of the fraction...

We develop a probabilistic approach for accurate network modeling using node popularities within the framework of the mixed-membership stochastic blockmodel (MMSB). Our model integrates two basic properties of nodes in social networks: homophily and preferential connection to popular nodes. We develop a scalable algorithm for posterior inference, based on a novel nonconjugate variant of stochas...

We present a new overlay, called theDeterministic Decentralized tree (D-tree). TheD-tree compares favourably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic load-balancin...

To achieve security in wireless sensor networks (WSN), it is important to be able to encrypt messages sent among sensor nodes. We propose a new cryptographic key management protocol, which is based on the clustering scheme but does not depend on the probabilistic key. The protocol can increase the efficiency to manage keys since, before distributing the keys by bootstrap, the use of public keys...

We propose a new passive system for indoor localization of mobile nodes. After the setup, our system only relies on arbitrary wireless communication from the nodes, whereby neither the mobile nodes nor the communication needs to be under our control. The presented system is composed of three Artificial Neural Networks (ANN) using a radiomap approach and the Received Signal Strength (RSS) for lo...

In this paper we describe some results on the linear integer programming formulation of the Probabilistic Minimum Power Multicast (PMPM) problem for wireless networks. The PMPM problem consists in optimally assigning transmission powers to the nodes of a given network in order to establish a multihop connection between a source node and a set of destination nodes. The nodes are subject to failu...

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maxi...

A PTP method in network security for misbehavior detection system is a method of detecting malicious misbehavior activity within networks. The System detects the malicious node and blocks them by adding into Blacklist. Malicious nodes are the compromised machine present in the network, which performs the task given by bot server i.e. it does not forward the legitimate message to another node in...

We propose a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher order temporal correlations due to feedback. This model, which we refer to as the temporal dependency model (TDM), can be constructed from the logic structure and is shown to be a dynamic Bayesian Network. Dynamic Bayesia...