Journal of Interconnection Networks

Fault tolerance is critical to reliability analysis of interconnection networks since the vulnerability of component failure increases with the growth of network scale. Extra connectivity and extra diagnosability are two decisive indicators of the ability of parallel and distributed systems to tolerate and diagnose faulty nodes. This paper mainly establishes the $3$-extra connectivity and $3$-extra diagnosability of augmented $3$-ary $n$-cubes $A{Q}_{n,3}$, which is a generalization of $k$-ary $n$-cubes and augmented cubes. In addition, we explore the $3$-extra diagnosis algorithm of $A{Q}_{n,3}$ under the MM* model.

In this paper, to avoid congestion in the wireless channel of vehicular ad hoc networks (VANETs), a joint beaconing rate and beaconing power based on game theory are proposed in this paper. The game is formulated as a non-cooperative game, a Bayesian game, and a cooperative game. Three distributed and iterative algorithms (Best Response Algorithm, Fictitious Play Algorithm, and Cooperative Bargaining Algorithm) are proposed for computing the beaconing power and beaconing rate of each vehicle. Extensive simulations show the convergence of a proposed algorithm to the equilibrium beaconing power and beaconing rate and give some insights on how the game parameters may vary the game outcome.

Data security is critical in wireless sensor networks (WSNs) because communication signals are highly available due to data transmission in free space. Attacks ranging from passive eavesdropping to active snooping are more common on these networks. This paper proposes secure data transfer using data encryption based on the improved Rivest–Shamir–Adleman (RSA) with Diffie–Hellman (DH) key exchange algorithm (IRSA-DH). For this purpose, the adaptive distance-based agglomerative hierarchical (ADAH)-based clustering method is used. Then the cluster head (CH) is selected using the improved weight-based rain optimization (IWRO) to improve the network’s lifespan. This study aims to design a secure group communication method for WSNs. In order to generate and distribute the key to the group, the RSA and DH and key exchange algorithm had been hybridized with the Key Management Center (KMC). For safe communication between users, the key exchange technique is investigated. The performance measures such as throughput, packet loss ratio (PLR), packet delivery ratio (PDR), latency, energy consumption, end-to-end delay (EED) and network lifetime are analyzed and compared with the existing approaches.

Let $V(G)$ and $E(G)$ be the vertex set and edge set of graph $G$. Let $d_G(x,y)$ be the distance between vertices $x$ and $y$ in the graph $G$ and $G-e$ be the graph obtained by deleting edge $e$ from $G$. For a vertex set $M\subseteq V(G)$ and an edge $e\in E(G)$, let $P(M,e)$ be the set of pairs $(x,y)$ with a vertex $x\in M$ and a vertex $y\in V(G)$ such that $d_G(x,y)\ne d_{G-e}(x,y)$. A vertex set $M\subseteq V(G)$ is distance-edge-monitoring set, introduced by Foucaud, Kao, Klasing, Miller, and Ryan, if every edge $e\in E(G)$ is monitored by some vertex of $M$, that is, the set $P(M,e)$ is nonempty. In this paper, we determine the smallest size of distance-edge-monitoring sets of hierarchical and corona graphs.

Typically, wireless sensor networks (WSNs) are used to monitor as well as detect different kinds of objects in realistic monitoring, where security remains as a major confront. Estimation of node trust is established to be an effectual way of enhancing the security, thus aiding in nodes collaboration and decision-making in wireless and wired networks. Nevertheless, conventional methods of trust management generally highlight on trust modeling and fail to notice the overhead issues. In this paper, a security aware ring cluster routing technique is introduced. The routing is undergone based on the multi-objectives including trust (security) parameters, energy, and distance. Here, the trust parameters include both the direct trust evaluation and indirect trust evaluation. Thereby, the lifetime of the network gets maximized even with secured manner. An innovative Self-Adaptive Deer Hunting Optimization (SA-DHO) is presented in this study because the optimization plays a significant role in selecting the neighbors as ring nodes. Finally, the superiority of the suggested approach is demonstrated in relation to various measures.

The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.