Wireless Sensor Networks (WSNs) enable applications where target state estimation is essential. To deal with the energy source and communication bandwidth constraints, an energy-aware adaptive probabilistic tracking mechanism based on quantization was proposed. According to the relationship between the sensing radius and node properties which include stored information and position, a part of r...

In this paper we introduce an efficient algorithm for alignment of multiple large-scale biological networks. In this scheme, we first compute a probabilistic similarity measure between nodes that belong to different networks using a semi-Markov random walk model. The estimated probabilities are further enhanced by incorporating the local and the cross-species network similarity information thro...

Ad Hoc networks are self-organizing wireless networks, absent any fixed infrastructure. Nodes in such networks communicate through radio transmissions of limited range, sometimes requiring the use of intermediate nodes to reach a destination. Nodes in ad hoc networks are also limited in their power supply and wireless bandwidth. Node mobility further complicates the environment. A communication...

This paper presents a framework for specifying a probabilistic Quality of Service (QoS) guarantee in a mobile ad hoc network. The framework uses the mobility profiles of nodes in the network to establish probabilistic QoS. The network can deliver for a specified period of time. A mobility model was used to characterize the probabilities of path availability between two communicating nodes and Q...

We consider probabilistic systems modeled under the form of a special class of probabilistic timed automata. Such automata have “no choice”: when the automaton arrives at a node, the time at which it will leave it is determined; when the automaton leaves the node, there is just one distribution of target nodes. In the paper, we give a method for computing the expected time A for the automaton t...

In wireless sensor networks, sensor nodes are easily compromised due to their restricted hardware resources. These compromised nodes inject fabricated votes into legitimate reports, and generate false report and false vote injection attacks. These attacks deplete energy resources and block report transmission. A probabilistic voting-based filtering scheme was proposed to detect the bogus votes ...

Large probabilistic graphs arise in various domains spanning from social networks to biological and communication networks. An important query in these graphs is the k nearestneighbor query, which involves finding and reporting the k closest nodes to a specific node. This query assumes the existence of a measure of the “proximity” or the “distance” between any two nodes in the graph. To that en...

The distributed systems in which nodes and/or edges may fail with certain probabilities have been modelled by a probabilistic network or a graph G. Computing the residual connectedness reliability (RCR), denoted by R(G), of probabilistic networks under the fault model with both node and edge faults is very useful, but is an NP-hard problem. Since it may need exponential time of the network size...

A PTP approach 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 ...

A Bayesian network (BN) Charniak (1991) Pearl (1988) Jensen (1996) Neapolitan (1990) is a directed acyclic graph (DAG) consisting of nodes and arrows, in which node represents random variables, and arrow represents dependence relationship between connected nodes in the sense of the probabilistic, deterministic, or functional. Each node in BN has a specified conditional probability distribution ...