A Comprehensive Evaluation of Nature Inspired Routing Algorithm for Mobile Ad Hoc Network : DEA and BCA

This paper discussed about the comprehensive evaluation of nature inspired routing algorithms such as Dolphin Echolocation Algorithm (DEA) and Bee colony Algorithm (BCA) use for distance optimization. The influence of DEA and BCA algorithms on Quality of Service (QoS) performance matrices for Mobile Ad hoc Network (MANET) is analyzed. Ultimately with the help of DEA it is possible to achieve optimized routing path between source and destination nodes. Further this paper have the analysis of various results which gives the comprehensive evaluation of DEA algorithm and it is suitable for MANET for achieving good Throughput, packet delivery ratio, delay and overhand

ACSRO: Adaptive cuckoo search based rate adjustment for optimized congestion avoidance and control in wireless sensor networks

Several sensor nodes in the wireless network collect the data rigorously which aids in many of the applications. The network with high and the consistent data load is the only requirement of the wireless sensor networks. Due to the limited sources of the network and the high data loads, networks may be affected by congestion. Congestion is a highly objectionable issue which leads to information loss and the deprived performance of the wireless sensor networks. In this paper, an adaptive cuckoo search based optimal rate adjustment (ACSRO) for the congestion avoidance and control is proposed. The rate adjustment regulates the share rate of the node to mitigate the congestion. The performance of the proposed rate optimization approach is evaluated using the evaluation metrics such as throughput, delay, normalized packet loss, normalized queue size, and congestion level. The results of the proposed rate optimization show that the congestion is compacted and the performance of the WSN is improved. Keywords: Wireless sensor networks, Cuckoo search, Congestion avoidance and control, Congestion level

An approach involving dynamic group search optimization for allocating resources in OFDM-based cognitive radio system

Allocation of channel resources in a cognitive radio system for achieving minimized transmission energy at an increased transmission rate is a challenging research. This paper proposes a resource allocation algorithm based on the meta-heuristic search principle. The proposed algorithm is an improved version of the Group Search Optimizer (GSO), which is a currently developed optimization algorithm that works through imitating the searching behaviour of the animals. The improvement is accomplished through introducing dynamics in the maximum pursuit angle of the GSO members. A cognitive radio system, relying on Orthogonal Frequency Division Multiplexing (OFDM) for its operation, is simulated and the experimentations are carried out for sub-channel allocation. The proposed algorithm is experimentally compared with five renowned optimization algorithms, namely, conventional GSO, Particle Swarm Optimization, Genetic Algorithm, Firefly Algorithm and Artificial Bee Colony algorithm. The obtained results assert the competing performance of the proposed algorithm over the other algorithms. Keywords: Cognitive radio, OFDM, Resource, Allocation, Optimization, GS

Surface plasmon resonance based colorimetric probe for vitamin B1 detection: Applications to bio-fluid analysis

This study reports simple analytical approach for thiamine (Vitamin B1) detection based on induced aggregation and alternation in colorimetric properties of gold nanoparticles (AuNPs), which was synthesized through citrate reduction approach. Furthermore, the citrate capped AuNPs are characterized by various analysing tools. The addition of thiamine persuades the aggregation of citrate-AuNPs and further leading to red to blue colour transition with decrease in absorbance intensity. The proposed method achieves good linearity with a correlation coefficient of 0.9843. By using our proposed strategy, thiamine was detected by unassisted vision as well as absorption spectroscopy. Under the most favorable condition method achieves good linear relationship between concentration range 0.01–0.8 μg mL−1 with limit of detection of 0.0067 μg mL−1. Under the premium condition, the method offers excellent selectivity towards thiamine detection in presence of different interfering species. Further practical applicability of the method was checked by using blood serum and urine sample via standard addition method. The obtained recoveries were acceptable in the range of 98.70–102.97% for added thiamine concentration. Thus, the proposed method may emerge as a target specific and highly sensitive tool towards thiamine detection