Presently, the field of wireless sensor networks (WSNs) is an important and challenging research area. Advancements in sensor networks enable a wide range of environmental monitoring and object tracking applications. Moreover, multihop routing in WSN is affected by new nodes constantly entering or leaving the network. Therefore, nature based self-optimized and independent mechanism is required to tackle problems arise in WSN. The ant inspired routing has shown an excellent performance for WSNs. In this paper, the model of selfoptimized autonomous routing algorithm BIOSARP with cross layer architecture for WSN and its results are presented. Certain parameters like energy level, delay and velocity are considered while making decisions. Energy level and velocity metrics are trade in from physical layer to network layer while discovering an optimal route and also in initialization process. These robust decisions will come up with the optimized route for WSN.
Interest in the cognitive radio sensor network (CRSN) paradigm has gradually grown among researchers. This concept seeks to fuse the benefits of dynamic spectrum access into the sensor network, making it a potential player in the next generation (NextGen) network, which is characterized by ubiquity. Notwithstanding its massive potential, little research activity has been dedicated to the network layer. By contrast, we find recent research trends focusing on the physical layer, the link layer and the transport layers. The fact that the cross-layer approach is imperative, due to the resource-constrained nature of CRSNs, can make the design of unique solutions non-trivial in this respect. This paper seeks to explore possible design opportunities with wireless sensor networks (WSNs), cognitive radio ad-hoc networks (CRAHNs) and cross-layer considerations for implementing viable CRSN routing solutions. Additionally, a detailed performance evaluation of WSN routing strategies in a cognitive radio environment is performed to expose research gaps. With this work, we intend to lay a foundation for developing CRSN routing solutions and to establish a basis for future work in this area.
The unpredictable nature of the wireless network and exponential growth in traffics with different quality of service requirements has led hardware complexity to escalate. In order to effectively control and manage the network traffics, there is a need for intelligent call admission control (CAC) in admitting traffics into the wireless network that provides necessary quality of service. In this paper, we propose a fuzzy logic partition-based call admission control (FZ CAC). The scheme primarily partitions the total link bandwidth into three which corresponds to constant bit rate (CBR), variable bit rate (VBR) and handover (HO) services. The fuzzy logic admission control scheme was implemented in the HO portion to intelligently keep dropping probability as low as possible based on the available bandwidth. Simulation results showed that the proposed approach outperformed both partition-based CAC (PB CAC) and conventional bandwidth allocation CAC (CB CAC).
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