We present a new and efficient algorithm for determining a consensus value for a network of agents. Different from existing algorithms, our algorithm evaluates the consensus value for very large networks using heat kernel pagerank. We consider two frameworks for the consensus problem, a weighted average consensus among all agents, and consensus in a leader-following formation. Using a heat kern...

Clustering ensembles have emerged as a powerful method for improving both the robustness and the stability of unsupervised classification solutions. However, finding a consensus clustering from multiple partitions is a difficult problem that can be approached from graph-based, combinatorial or statistical perspectives. We offer a probabilistic model of consensus using a finite mixture of multin...

<span>Signature-based collaborative intrusion detection system (CIDS) is highly depends on the reliability of nodes to provide IDS attack signatures. Each node in network responsible new signature be shared with other node. There are two problems exist CIDS highlighted this paper, first data consistency and second maintain trust among while sharing Recently, researcher find that blockchai...

Brain tissue segmentation is an important component of the clinical diagnosis brain diseases using multi-modal magnetic resonance imaging (MR). has been developed by many unsupervised methods in literature. The most commonly used are K-Means, Expectation-Maximization, and Fuzzy Clustering. clustering offer considerable benefits compared with aforementioned as they capable handling images that c...

Ark is an implementation of a consensus algorithm similar to Paxos[7] and Raft[11], designed as an improvement over the existing consensus algorithm used by MongoDB R © and TokuMX. Ark was designed from first principles, improving on the election algorithm used by TokuMX, to fix deficiencies in MongoDB’s consensus algorithms that can cause data loss. It ultimately has many similarities with Raf...

The paper considers the consensus problem in a partially synchronous system with Byzantine faults. It turns out that, in the partially synchronous system, all deterministic algorithms that solve consensus with Byzantine faults are leader-based. This is not the case of benign faults, which raises the following fundamental question: is it possible to design a deterministic Byzantine consensus alg...

In this paper we study the problem of designing optimal consensus algorithms for distributed estimation of dynamical systems. In particular, we show that for fixed estimation gain, the problem of finding optimal consensus matrix is convex and can be efficiently performed numerically. We also provide some numerical examples to common scenarios, like symmetric geometric random graphs, which are r...

In this paper we present an approach that employs a genetic algorithm (GA) to evolve the consensus sequences for DNA and protein sequences alignments. We have developed an encoding scheme such that the number of generations needed to find the optimal solution remains approximately the same regardless the number of sequences. The complexity instead depends only on the length of the consensus seq...