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Modeling and Simulation Tools for Mobile Ad Hoc Networks
Published in Jonathan Loo, Jaime Lloret Mauri, Jesús Hamilton Ortiz, Mobile Ad Hoc Networks, 2016
Kayhan Erciyes, Orhan Dagdeviren, Deniz Cokuslu, Onur Yılmaz, Hasan Gumus
A connected dominating set (CDS) is a subset S of a graph G such that S forms a dominating set and is connected. Figure 3.8c shows a sample CDS. CDSs have many advantages in network applications such as ease of broadcasting and constructing virtual backbones [9]; however, when we try to obtain a CDS, we may have undesirable number of cluster heads. So, in constructing CDSs, our primary problem is the minimum CDS decision problem. Wu’s distributed algorithm [10] is an important study in this field where researchers attempted to improve the performance of this work later [11,12]. The steps of Wu’s algorithm are given below: Each node u finds the set of neighbors Γ(u).Each node u transmits Γ(u) and receives Γ(v) from all its neighbors.If node u has two neighbors v, w and w is not in Λ(v), then u marks itself being in the set CDS. In Figure 3.9, a sample output of this algorithm is shown. A detailed survey about CDS can be found in [13].
Integer linear programming formulations for double roman domination problem
Published in Optimization Methods and Software, 2022
Qingqiong Cai, Neng Fan, Yongtang Shi, Shunyu Yao
A set is called a dominating set if every vertex of G is either in S or adjacent to a vertex of S. The minimum cardinality of a dominating set in G, denoted by , is called the domination number. Domination of graphs has been extensively studied in the scientific literature. The variants of domination have abundant applications, including error-correcting codes constructions for digital communication and efficient data routing in wireless networks [9,10,12,18,28]. Many different kinds of domination arose, such as the connected dominating set [16], the edge dominating set [33], the total domination [24,27], the independent domination [19], Roman domination [32], etc.
GLS and VNS based heuristics for conflict-free minimum-latency aggregation scheduling in WSN
Published in Optimization Methods and Software, 2021
Roman Plotnikov, Adil Erzin, Vyacheslav Zalyubovskiy
As mentioned before, most MLAS algorithms solve the problem in two consecutive phases: aggregation tree construction and link scheduling. Shortest Path Tree (SPT) and Connected Dominating Set (CDS) are the usual patterns for the aggregation tree. In SPT based algorithms [4,19,24], a sensor transmits data through a path with minimum length, which reduces aggregation delay, but they do not take potential collisions into consideration. As for CDS based algorithms, due to the topological properties of CDS, it is often possible to prove for them the upper bound of data aggregation delay, which usually depends on network radius R and maximum node degree Δ. Huang et al. [17] proposed an aggregation scheduling method based on CDS with the latency bound . Based on the deeper study of the properties of neighbouring dominators in CDS, Nguyen et al. [25] provided a proof of an upper bound for their algorithm.
Consensus in multi-agent systems over time-varying networks
Published in Cyber-Physical Systems, 2020
Magdi S. Mahmoud, Mojeed Oyedeji
Resilient distributed consensus was studied in [113] for MAS with trusted nodes under sparse topologies. An important conclusion in this paper suggests that the network is resilient against attacks when the trusted set of nodes form a connected dominating set. Resilient consensus for MAS over quantised directed networks was investigated in [114] under the assumption that each agent can only exchange quantised information with its neighbours. Their results suggest that consensus can be reached when the number of attack nodes is bounded in each neighbourhood. Parameter-independent fault-tolerant algorithms which does not require initial knowledge of the number of faulty agents were proposed in [115] for MAS with misbehaving agents. It was shown that the algorithm converges if the network of non-faulty agents is robust, where is the number of faulty agents.