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Betweenness centrality of a node represents its influence over the spread of information in the network. It is normally defined as the ratio of the number of shortest paths passing through the node among all shortest paths. However, the spread of information may not just pass through the shortest paths which is captured by a new measure of betweenness centrality based on random walks [1]. The random...
When mobile sensors are initially deployed, some sensors may be located far away from the region of interest and due to the sensor's limited sensing of range, some sensors may not be able to participate in the coverage task. This paper proposes a new algorithm on the coverage problem for mobile sensor networks which guarantees all sensors to participate in the coverage task. The algorithm is a combination...
Self-stabilizing systems, intended to run for a long time, commonly have to cope with transient faults during their mission. We model the behavior of a distributed self-stabilizing system under such a fault model as a Markov chain. Adding fault detection to a self-correcting non-masking fault tolerant system is required to progress from non-masking systems towards their masking fault tolerant functional...
Motivated by the problem of multiple unlicensed cognitive radio users seek to access unused frequency channels licensed to the primary users in a wireless communication scenario, this paper presents a simulation environment that is able to simulate various effects of radio wave propagation and shadow fading in a software model. A cognitive radio designer's intent, knowledge about the critical issues...
Opportunistic scheduling has been recognized as an effective method that significantly outperforms fixed TDMA scheduling in both channel capacity and communication reliability. Nevertheless the superior system performance comes at a price of high computational complexity, large signaling overhead, and unfairness among users. In this paper, we find that in relay-assisted next-generation wireless networks,...
The paper studies the problem of distributed transmit beamforming with autonomous and self-organizing mobile antennas. The objective is to design a distributed algorithm for a network of autonomous mobile robots with carry-on antennas so that they can form a functional antenna array and cooperatively transmit messages to a remote station. Note that the spatial relationship of the antennas also contributes...
Clustering sensor nodes is an effective topology control for increasing network lifetime and scalability. It also, balances the load on the sensor nodes. HEED is a well known distributed clustering protocol that uses both energy and communication cost to elect Cluster Heads (CHs) in a probabilistic way. This paper improves HEED protocol using fuzzy logic and a non probabilistic approach for CH election...
A sequence of irreducible Markov chains with increasing state cardinality is called democratic if the sequence of corresponding invariant probabilities converges to 0 uniformly. Democracy is a relevant property which naturally shows up when we deal with distributed algorithms like consensus or with opinion dynamic models: it says that each agent measure/opinion is going to play a negligible role in...
Consensus strategies find extensive applications in coordination of robot groups and decision making of agents. Since balanced graph plays an important role in the average consensus problem for directed communication networks, this work explores the conditions and algorithms for the digraph balancing problem. It has been proved that a directed graph can be balanced if and only if the null space of...
By utilizing the must-link or cannot-link pair wise constraints in data, semi-supervised clustering improves the performance of unsupervised clustering significantly. A number of semi-supervised clustering algorithms have been proposed to consider such pair wise constraints. However, most of them assign a hard label to each data item and produce little information about the cluster itself. In this...
A collective cleanup task requires a multi-robot system to search for randomly distributed targets and remove them under a dynamic environment. In traditional methods, robots wandered in subareas (which caused too much repeat search) and interchanged all detected information with their neighbors, so global searching time and communication traffic increased. In this paper, we propose a swarm intelligence...
We develop adaptive scheduling and power control algorithms for random access in a multiple access channel where terminals acquire instantaneous channel state information but do not know the probability distribution of the channel. In each time slot, terminals measure the channel to the common access point. Based on the observed channel value, they determine whether to transmit or not and, if they...
This paper presents a general toolkit developed for discrete Estimation of distribution algorithms (EDAs). The essence and procedure of each algorithm is presented, and the toolkit is used to solve several toy problems, which is presented in the latter part of the paper. We implemented and presented a general toolkit for EDAs (gtEDA) as a Matlab toolkit for EDA experiments. The experiments conducted...
In the present article, a new algorithm called Noisy Univariate Marginal Distribution Algorithm (NUMDA) is proposed as an improvement of UMDA. The main idea is to introduce stochastic item into the probabilistic model of the selected solutions. Numerical experiments show that NUMDA has a better performance on some problems than UMDA. In addition, the updating progress of this new algorithm can be...
This paper investigates the use of empirical and Archimedean copulas as probabilistic models of continuous estimation of distribution algorithms (EDAs). A method for learning and sampling empirical bivariate copulas to be used in the context of n-dimensional EDAs is first introduced. Then, by using Archimedean copulas instead of empirical makes possible to construct n-dimensional copulas with the...
Using partitioning in wireless sensor networks to create clusters for routing, data management, and other protocols has been proven as a way to ensure scalability and to deal with sensor network shortcomings such as limited communication ranges and energy. Choosing a cluster head within each cluster is important because cluster heads use additional energy for their responsibilities and that burden...
In this paper, we propose the notion of sufficient set for distributed processing of probabilistic Top-k queries in cluster-based wireless sensor networks. Through the derivation of sufficient boundary, we show that data items ranked lower than sufficient boundary are not required for answering the probabilistic top-k queries, thus are subject to local pruning. Accordingly, we develop the sufficient...
We present a robust distributed fusion algorithm with intermittent observations via an interacting multiple model (IMM) approach and sliding window strategy that can be applied to a large-scale sensor network. The communication channel is modelled as a jump Markov system and a posterior probability distribution for communication channel characteristics is calculated and incorporated into the filter...
Due to the limited energy supplies of nodes in many applications like wireless sensor networks, energy efficiency is crucial for extending the lifetime of these networks. This paper addresses the routing problem for outage-restricted multihop wireless ad hoc networks based on cooperative transmission. The source node wants to transmit messages to a single destination. Other nodes in the network may...
We first propose a new proactive routing framework based on probabilistic decisions and a generic model to compute the existence probabilities of nodes and links. Then, we present a distributed algorithm to collect the cartography of the network. This cartography is used to instantiate the existence probabilities. Conducted simulations show that our proposal yields substantially better routing validity...
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