Hybrid Heterogeneous Routing Scheme for Improved Network Performance in WSNs for Animal Tracking

Wireless Sensor Networks (WSNs) experiences several technical challenges such as limited energy, short transmission range, limited storage capacities, and limited computational capabilities. Moreover, the sensor nodes are deployed randomly and massively over an inaccessible or hostile region. Hence WSNs are vulnerable to adversaries and are usually operated in a dynamic and unreliable environment. Animal tracking using wireless sensors is one such application of WSN where power management plays a vital role. In this paper, an energy-efficient hybrid routing method is proposed that divides the whole network into smaller regions based on sensor location and chooses the routing scheme accordingly. The sensor network consists of a base station (BS) located at a distant place outside the network, and a relay node is placed inside the network for direct communications from nodes nearer to it. The nodes are further divided into two categories based on the supplied energy; such that the ones located far away from BS and relay have higher energy than the nodes nearer to them. The network performance of the proposed method is compared with protocols like LEACH, SEP, and SNRP, considering parameters like stability period, throughput and energy consumption. Simulation result shows that the proposed method outperforms other methods with better network performance

Microgel/silica hybrid colloids: Bioinspired synthesis and controlled release application

In the present work, we demonstrate that polymer based functional microgels can be used as autocatalytic template for the bioinspired deposition of silica nanoparticles inside the microgel network under ambient conditions. Temperature responsive poly(N-vinyl caprolactam) based microgels were synthesized by precipitation polymerization using glycidyl methacrylate as a comonomer. These microgels were further reacted with aminoethanthiol to develop amine functional groups inside the microgels. A water soluble silica precursor (PEGPEOS) was developed by modification of hyperbranched polyethoxysiloxane with polyethylene glycol monomethyl ether. Microgel/silica hybrid colloids were prepared by simultaneous PEGPEOS conversion and silica deposition in the microgels. TEM studies showed that silica nanoparticles of approximately 10 nm in size were deposited inside the microgel network owing to the strong acidbase interaction between the acidic silica and basic amine groups. DLS results indicated that the incorporation of silica nanoparticles reduced the thermal sensitivity of microgels. Molecular dynamics simulations were performed to investigate the interaction between silica precursor and microgels based on radial distribution function and interaction energy. The developed hybrid microgels were further explored for controlled release of aspirin used as a model drug. The preliminary results indicated that the presence of silica rich domains in the microgel network remarkably retarded aspirin release

Hybrid Heterogeneous Routing Scheme for Improved Network Performance in WSNs for Animal Tracking

Wireless Sensor Networks (WSNs) experiences several technical challenges such as limited energy, short transmission range, limited storage capacities, and limited computational capabilities. Moreover, the sensor nodes are deployed randomly and massively over an inaccessible or hostile region. Hence, WSNs are vulnerable to adversaries and are usually operated in a dynamic and unreliable environment. Animal tracking using wireless sensors is one such application of WSN where power management plays a vital role. In this paper, an energy-efficient hybrid routing method is proposed that divides the whole network into smaller regions based on sensor location and chooses the routing scheme accordingly. The sensor network consists of a base station (BS) located at a distant place outside the network, and a relay node is placed inside the network for direct communications from nodes nearer to it. The nodes are further divided into two categories based on the supplied energy; such that the ones located far away from BS and relay have higher energy than the nodes nearer to them. The network performance of the proposed method is compared with protocols like LEACH, SEP, and SNRP, considering parameters like stability period, throughput and energy consumption. Simulation result shows that the proposed method outperforms other methods with better network performance

Epoxidized Soybean Oil-Based Epoxy Blend Cured with Anhydride-Based Cross-Linker: Thermal and Mechanical Characterization

The present research is based on a comparative study of anhydride cured biobased and petroleum-based epoxy network. The effect of epoxidized soybean oil (ESO) bioresin on petroleum-based epoxy (DGEBA) at varying compositions cured with methyl­hexahydrophthalic anhydride (MHHPA) as curing agent and 2-methyl imidazole (2-MI) as the catalyst has been investigated. The tensile strength of virgin epoxy (42.94 MPa) increased to 48.62 MPa with the addition of 20% of ESO. The fracture toughness parameters; critical stress intensity factor (<i>K</i>_IC) and critical strain energy release rate revealed enhancement of toughness in the biobased blends. Differential scanning calorimetry studies confirmed an enhancement in the peak temperature and a reduction in the heat of curing in virgin epoxy on incorporation of ESO content. The thermomechanical and fracture morphological properties of virgin epoxy, ESO, and its biobased blends were investigated by thermogravimetric analysis, dynamic mechanical analysis, atomic force microscopy, and scanning electron microscopy, respectively

CH Selection via Adaptive Threshold Design Aligned on Network Energy

Energy consumption in Wireless Sensor Networks (WSN) involving multiple sensor nodes is a crucial parameter in many applications like smart healthcare systems, home automation, environmental monitoring, and industrial use. Hence, an energy-efficient cluster-head (CH) selection strategy is imperative in a WSN to improve network performance. So to balance the harsh conditions in the network with fast changes in the energy dynamics, a novel energy-efficient adaptive fuzzy-based CH selection approach is projected. Extensive simulations exploited various real-time scenarios, such as varying the optimal position of the location of the base station and network energy. Additionally, the results showed an improved performance in the throughput (46%) and energy consumption (66%), which demonstrated the robustness and efficacy of the proposed model for the future designs of WSN applications