A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

A Novel Cross-layer Communication Protocol for Vehicular Sensor Networks

Communication protocols in Vehicular Sensor Networks (VSNs) in urban areas play an important role in intelligent transport systems applications. Many cross layer communication protocols studies are originated from topology-based algorithms, which is not suitable for the frequently-changing computational scenario. In addition, the influence factors that have been considered for VSNs routing are not enough. With these aspects in mind, this paper proposes a multi-factor cross layer position-based routing (MCLPR) protocol for VSNs to improve reliability and efficiency in message delivery. Considering the complex intersection environment, the algorithm for vehicles selection at intersections (called AVSI) is further proposed, in which comprehensive factors are taken into account including the position and direction of vehicle, the vehicle density, the signal-to-noise-plus-interference ratio (SNIR), as well as the frame error rate (FER) in MAC layer. Meanwhile, the dynamic HELLO STREAM broadcasting system with the various vehicle speeds is proposed to increase the decisions accuracy. Experimental results in Network Simulator 3 (NS-3) show the advantage of MCLPR protocol over traditional state-of the-art algorithms in terms of packet delivery ratio (PDR), overhead and the mean end-to-end delay

Spectrum Estimation and Optimal Secondary User Selection in Cognitive Radio Networks

The high-speed development of wireless communication technology has emerged in the surging insistence on optimal spectrum resources. Nevertheless, in consonance to a contemporary study, most of the assigned frequency encounters notable underutilization as far as Cognitive Radio Network (CRN) is concerned. One important issue correlated with spectrum management is how to properly estimate and allocate the spectrum to a Secondary User (SU) for a highly dynamic environment in an optimal manner with minimum sensing delay. In this paper, a Chebyshev Vector Dynamic Spectrum and Kolmogorov-Smirnov Convolutional Network (CVDS-KSCN) method for dynamic spectrum estimation and optimal secondary user selection in CRN is developed. First, it is proposed to tackle the dynamic spectrum access issue with minimum sensing delay in CRN attaining robust spectrum channel throughput with minimum sensing delay. The spectrum estimation is modeled using the Chebyshev distance-based Harmonious Vector Spectrum Estimation model in a dynamic manner. With the dynamic spectrum estimated results, a Kolmogorov-Smirnov Convolutional Neural Network-based Secondary User Selection model is applied to retrieve optimal secondary users in CRN. The performance of CVDS-KSCN is assessed over numerous key aspects, where simulation results confirm the efficiency of the proposed method in achieving high reliable spectrum estimation and Secondary User selection. It is expressive in the simulation results that the proposed CVDS-KSCN method can achieve a good probability of throughput and reduction in sensing delay during Secondary User Selection with low probability of false alarm. The results show that the proposed method outperfroms the DRS and EFAHP algorithms quantitatively in terms of four parameters, namely throughput, sensing delay, false alarm percentage and Secondary User Selection Time