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arXiv2021

Self-stabilizing Algorithm for Maximal Distance-2 Independent Set

In graph theory, an independent set is a subset of nodes where there are no two adjacent nodes. The independent set is maximal if no node outside the independent set can join it. In network applications, maximal independent sets can be used as cluster heads in ad hoc and wireless sensor networks. In order to deal with any failure in networks, self-stabilizing algorithms have been proposed in the literature to calculate the maximal independent set under different hypotheses. In this paper, we propose a self-stabilizing algorithm to compute a maximal independent set where nodes of the independent set are far from each other at least with distance 3. We prove the correctness and the convergence of the proposed algorithm. Simulation tests show the ability of our algorithm to find a reduced number of nodes in large scale networks which allows strong control of networks

cs.DC↗

arXiv2020

Self-stabilizing Algorithm for Minimal $α$-Dominating Set

A self-stabilizing algorithm for the minimal $α$-dominating set is proposed in this paper. The $α$-domination parameter has not used before in self-stabilization paradigm. Using an arbitrary graph with $n$ nodes and $m$ edges, the proposed algorithm converges in $O(nm)$ moves under distributed daemon. Simulation tests and mathematical proofs show the efficiency of the algorithm.

cs.DC↗

arXiv2020

Tracking COVID-19 by Tracking Infectious Trajectories

Nowadays, the coronavirus pandemic has and is still causing large numbers of deaths and infected people. Although governments all over the world have taken severe measurements to slow down the virus spreading (e.g., travel restrictions, suspending all sportive, social, and economic activities, quarantines, social distancing, etc.), a lot of persons have died and a lot more are still in danger. Indeed, a recently conducted study~\cite{ref2} has reported that 79\% of the confirmed infections in China were caused by undocumented patients who had no symptoms. In the same context, in numerous other countries, since coronavirus takes several days before the emergence of symptoms, it has also been reported that the known number of infections is not representative of the real number of infected people (the actual number is expected to be much higher). That is to say, asymptomatic patients are the main factor behind the large quick spreading of coronavirus and are also the major reason that caused governments to lose control over this critical situation. To contribute to remedying this global pandemic, in this paper, we propose an IoT (Internet of Things) investigation system that was specifically designed to spot both undocumented patients and infectious places. The goal is to help the authorities to disinfect high-contamination sites and confine persons even if they have no apparent symptoms. The proposed system also allows determining all persons who had close contact with infected or suspected patients. Consequently, rapid isolation of suspicious cases and more efficient control over any pandemic propagation can be achieved.

cs.CY↗