A smart city refers to a city equipped with the basic infrastructure to provide a good quality of life and a clean and sustainable environment to its citizens using smart technology-based solutions. It is a smart way to provide the best services to its residents and develop the infrastructure. The smart city focuses on controlling available resources safely, sustainably, and efficiently to improve the economy and societal outcomes. People, systems, and things in the cities generate data. However, their heterogeneity makes it difficult to publish, organize, discover, interpret, combine, analyse, and consume them. The next generation of these technologies, including the 6G and intelligent internet of things (6G/IIoT), have been recently proposed aiming to provide endless networking capabilities to the city users. General estimates revealed that the number of smart IoT devices would approach over 50 billion by 2022. With the proliferation of smart IoT devices, smart applications are expected to lead to further innovation in 6G/IIoT-oriented cities. This special issue aims to stimulate discussion on the IoT and Big Data analytics for future smart cities with smart applications including smart health, smart governance, smart homes, and smart buildings, smart mobility and transportation, smart factories, and smart data-driven decision-making. In this special issue, each paper was reviewed by three or more experts during the assessment process. After evaluating the overall scores, six papers were selected for inclusion in this special issue. The selected papers present in-depth studies of practical issues and challenging problems in Big Data Analytics with IoT-oriented Infrastructures for Future Smart Cities. This paper (Haque et al., 2022) focuses on the overview and conceptual development of the smart city. Initially, the work discusses the smart city idea and fundamentals explored in various pieces of literature. Further various smart city applications along with notable implementations are put forth to understand the quality of living standards. This article (Zhang & Liu, 2022) conducts APP page management through technical analysis of mobile devices and user experience-oriented design. The framework design of the browser and the construction of the interface MVC design mode, and then through the questionnaire survey method to the user experience needs and expectations of the medical APP to design the main key of the page function. In this paper (Galyan et al., 2022), simulation results of the proposed method attain substantial performance improvement in target node 3D position accuracy than the earlier proposed range-free methods. The proposed technique is useful for mapping several instances like fire hazards in forests, tracking of workers at different installation sites, solar plant tracking in smart cities, and so forth. In this work (Jain et al., 2022), the authors have applied logistic regression, decision tree, support vector machine, linear discriminant analysis, quadratic discriminant analysis, naïve Bayes, random forest, and k-nearest neighbour algorithms to predict the stability of the grid. The authors have used the smart grid stability data set freely available on Kaggle to train and test the models. This work (Mandloi & Arya, 2022) proposed a Machine Programming based approach for the deployment of 5 G-enabled UmBSs. The centroid-based clustering algorithms such as; K-means, K-medoid, and FCM were proposed to find the centroid of the cluster. Then, the UmBSs were deployed at the centroid location of each cluster. This paper (Dixit et al., 2022) presents a systematic outlook of AI techniques in anomaly detection of AEVs. A solution taxonomy is proposed based on research gaps in existing surveys, and the evaluation metrics for AI-based anomaly detection are discussed. The open challenges and issues in AI deployments are discussed and a case study is presented on anomaly classification through a weighted ensemble technique.

Abstract In a graph, a matching cut is an edge cut that is a matching. Matching Cut is the problem of deciding whether or not a given graph has a matching cut, which is known to be $${\mathsf {NP}}$$ NP -complete. While Matching Cut is trivial for graphs with minimum degree at most one, it is $${\mathsf {NP}}$$ NP -complete on graphs with minimum degree two. In this paper, we show that, for any given constant $$c>1$$ c > 1 , Matching Cut is $${\mathsf {NP}}$$ NP -complete in the class of graphs with minimum degree c and this restriction of Matching Cut has no subexponential-time algorithm in the number of vertices unless the Exponential-Time Hypothesis fails. We also show that, for any given constant $$\epsilon >0$$ ϵ > 0 , Matching Cut remains $${\mathsf {NP}}$$ NP -complete in the class of n-vertex (bipartite) graphs with unbounded minimum degree $$\delta >n^{1-\epsilon }$$ δ > n 1 - ϵ . We give an exact branching algorithm to solve Matching Cut for graphs with minimum degree $$\delta \ge 3$$ δ ≥ 3 in $$O^*(\lambda ^n)$$ O ∗ ( λ n ) time, where $$\lambda$$ λ is the positive root of the polynomial $$x^{\delta +1}-x^{\delta }-1$$ x δ + 1 - x δ - 1 . Despite the hardness results, this is a very fast exact exponential-time algorithm for Matching Cut on graphs with large minimum degree; for instance, the running time is $$O^*(1.0099^n)$$ O ∗ ( 1 . 0099 n ) on graphs with minimum degree $$\delta \ge 469$$ δ ≥ 469 . Complementing our hardness results, we show that, for any two fixed constants $$1< c <4$$ 1 < c < 4 and $$c^{\prime }\ge 0$$ c ′ ≥ 0 , Matching Cut is solvable in polynomial time for graphs with large minimum degree $$\delta \ge \frac{1}{c}n-c^{\prime }$$ δ ≥ 1 c n - c ′ .

Abstract The generalized $k$-connectivity of a graph $G$ is a parameter that can measure the reliability of a network $G$ to connect any $k$ vertices in $G$, which is a generalization of traditional connectivity. Let $S\subseteq V(G)$ and $\kappa _{G}(S)$ denote the maximum number $r$ of edge-disjoint trees $T_{1}, T_{2}, \cdots , T_{r}$ in $G$ such that $V(T_{i})\bigcap V(T_{j})=S$ for any $i, j \in \{1, 2, \cdots , r\}$ and $i\neq j$. For an integer $k$ with $2\leq k\leq n$, the generalized $k$-connectivity of a graph $G$ is defined as $\kappa _{k}(G)= min\{\kappa _{G}(S)|S\subseteq V(G)$ and $|S|=k\}$. In this paper, we introduce a family of regular graph $G_{n}$ that can be constructed recursively and each vertex with exactly one outside neighbor. The generalized $3$-connectivity of the regular graph $G_{n}$ is studied, which attains a previously proven upper bound on $\kappa _{3}(G)$. As applications of the main result, the generalized $3$-connectivity of some important networks including some known results such as the alternating group network $AN_{n}$, the star graph $S_{n}$ and the pancake graphs $P_{n}$ can be obtained directly.

Tallini and Bose defined a random walk function on which an efficient encoding/decoding algorithm for second-order spectral-null (2-OSN) codes was based. Later, Yang enhanced Tallini-Bose code by using quasi 2-OSN codes. Both 2-OSN codes encode the information word into a balanced word and then append extra bits to make the length of this balanced word equal to 0 (or 2) modulo 4. The main innovation is to eliminate the need for appended bits, thereby increasing the code rate.

Measuring protein structural similarity attempts to establish a relationship of equivalence between polymer structures based on their conformations. In several recent studies, researchers have explored protein-graph remodeling, instead of looking a minimum superimposition for pairwise proteins. When graphs are used to represent structured objects, the problem of measuring object similarity become one of computing the similarity between graphs. Graph theory provides an alternative perspective as well as efficiency. Once a protein graph has been created, its structural stability must be verified. Therefore, a criterion is needed to determine if a protein graph can be used for structural comparison. In this paper, we propose a measurement for protein graph remodeling based on graph entropy. We extend the concept of graph entropy to determine whether a graph is suitable for representing a protein. The experimental results suggest that when applied, graph entropy helps a conformational on protein graph modeling. Furthermore, it indirectly contributes to protein structural comparison if a protein graph is solid.

This paper introduces the idea of a deferred-query approach to design O(n) algorithms for the domatic partition, optimal path cover, Hamiltonian path, Hamiltonian circuit, and maximum matching problems on interval graphs given n endpoint-sorted intervals. The previous best-known algorithms run in O(n log log n) or O(n +m) time, where m is the number of edges in the corresponding interval graphs. © 1999 John Wiley & Sons, Inc. Networks 34: 1–10, 1999