Scale-free topology optimization for software-defined wireless sensor networks: A cyber-physical system

Due to the limited resource and vulnerability in wireless sensor networks, maximizing the network lifetime and improving network survivability have become the top priority problem in network topology optimization. This article presents a wireless sensor networks topology optimization model based on complex network theory and cyber-physical systems using software-defined wireless sensor network architecture. The multiple-factor-driven virtual force field and network division–oriented particle swarm algorithm are introduced into the deployment strategy of super-node for the implementation in wireless sensor networks topology initialization, which help to rationally allocate heterogeneous network resources and balance the energy consumption in wireless sensor networks. Furthermore, the preferential attachment scheme guided by corresponding priority of crucial sensors is added into scale-free structure for optimization in topology evolution process and for protection of vulnerable nodes in wireless sensor networks. Software-defined wireless sensor network–based functional architecture is adopted to optimize the network evolution rules and algorithm parameters using information cognition and flow-table configure mode. The theoretical analysis and experimental results demonstrate that the proposed wireless sensor networks topology optimization model possesses both the small-world effect and the scale-free property, which can contribute to extend the lifetime of wireless sensor networks with energy efficiency and improve the robustness of wireless sensor networks with structure invulnerability

Study on Different Topology Manipulation Algorithms in Wireless Sensor Network

Wireless sensor network (WSN) comprises of spatially distributed autonomous sensors to screen physical or environmental conditions and to agreeably go their information through the network to a principle area. One of the critical necessities of a WSN is the efficiency of vitality, which expands the life time of the network. At the same time there are some different variables like Load Balancing, congestion control, coverage, Energy Efficiency, mobility and so on. A few methods have been proposed via scientists to accomplish these objectives that can help in giving a decent topology control. In the piece, a few systems which are accessible by utilizing improvement and transformative strategies that give a multi target arrangement are examined. In this paper, we compare different algorithms' execution in view of a few parameters intended for every target and the outcomes are analyzed. DOI: 10.17762/ijritcc2321-8169.15029

A Swarm Optimization Based Power Aware Clustering Strategy for WSNs

The technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes

A Novel Skeleton Extraction Algorithm for 3d Wireless Sensor Networks

Wireless sensor network design is critical and resource allocation is a major problem which remains to be solved satisfactorily. The discrete nature of sensor networks renders the existing skeleton extraction algorithms inapplicable. 3D topologies of sensor networks for practical scenarios are considered in this paper and the research carried out in the field of skeleton extraction for three dimensional wireless sensor networks. A skeleton extraction algorithm applicable to complex 3D spaces of sensor networks is introduced in this paper and is represented in the form of a graph. The skeletal links are identified on the basis of a novel energy utilization function computed for the transmissions carried out through the network. The frequency based weight assignment function is introduced to identify the root node of the skeleton graph. Topological clustering is used to construct the layered topological sets to preserve the nature of the topology in the skeleton graph. The skeleton graph is constructed with the help of the layered topological sets and the experimental results prove the robustness of the skeleton extraction algorithm introduced. Provisioning of additional resources to skeletal nodes enhances the sensor network performance by 20% as proved by the results presented in this paper