A Reliable Merging Link Scheme Using Weighted Markov Chain Model in Vehicular Ad Hoc Networks.

The vehicular ad hoc network (VANET) is a potential technology for intelligent transportation systems (ITS) that aims to improve safety by allowing vehicles to communicate quickly and reliably. The rates of merging collision and hidden terminal problems, as well as the problems of picking the best match cluster head (CH) in a merged cluster, may emerge when two or more clusters are merged in the design of a clustering and cluster management scheme. In this paper, we propose an enhanced cluster-based multi-access channel protocol (ECMA) for high-throughput and effective access channel transmissions while minimizing access delay and preventing collisions during cluster merging. We devised an aperiodic and acceptable merge cluster head selection (MCHS) algorithm for selecting the optimal merge cluster head (MCH) in centralized clusters where all nodes are one-hop nodes during the merging window. We also applied a weighted Markov chain mathematical model to improve accuracy while lowering ECMA channel data access transmission delay during the cluster merger window. We presented extensive simulation data to demonstrate the superiority of the suggested approach over existing state-of-the-arts. The implementation of a MCHS algorithm and a weight chain Markov model reveal that ECMA is distinct and more efficient by 64.20-69.49% in terms of average network throughput, end-to-end delay, and access transmission probability.

Prioritized Shortest Path Computation Mechanism (PSPCM) for wireless sensor networks.

Routing Protocol for Low-power and Lossy Networks (RPL), the de facto standard routing protocol for the Internet of Things (IoT) administers the smooth transportation of data packets across the Wireless Sensor Network (WSN). However, the mechanism fails to address the heterogeneous nature of data packets traversing the network, as these packets may carry different classes of data with different priority statuses, some real-time (time-sensitive) while others non-real-time (delay-tolerant). The standard Objective Functions (OFs), used by RPL to create routing paths, treat all classes of data as the same, this practice is not only inefficient but results in poor network performance. In this article, the Prioritized Shortest Path Computation Mechanism (PSPCM) is proposed to resolve the data prioritization of heterogeneous data and inefficient power management issues. The mechanism prioritizes heterogeneous data streaming through the network into various priority classes, based on the priority conveyed by the data. The PSPCM mechanism routes the data through the shortest and power-efficient path from the source to the destination node. PSPCM generates routing paths that exactly meet the need of the prioritized data. It outperformed related mechanisms with an average of 91.49% PDR, and average power consumption of 1.37mW which translates to better battery saving and prolonged operational lifetime while accommodating data with varying priorities.

Seluge++: a secure over-the-air programming scheme in wireless sensor networks.

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.