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

Comparison of Energy Consumption of Wireless Sensor Network at Various Topology Deployment: Array, Grid, and Random

This paper is review wireless sensor network and it’s energy consumption at different deployment methods. Wireless Sensor Networks (WSN) are emerging with many applications, because of the advances in large scale wireless communications. These networks are deployed to serve single objective application, with high optimization requirements such as power saving. The WSN design problem is of high complexity, and requires robust methodologies, including simulation support. We use NS2 as simulation program for this model. In this paper, the authors compare the energy consumption on three different deployment methods of WSN. These deployment methods refer to topology deployment. In this simulation, we deploy WSN on grid, array, and random topology. We use different numbers of WSN nodes for showing the scalability. We use AODV as routing protocol and CBR as the traffic. After that, we compare the energy consumption that consume by that networks. Based on simulation result, the array topology is the best topology for deployment. This topology is the lowest on energy consumption, 0.560%.

Reliable routing scheme for indoor sensor networks

Indoor Wireless sensor networks require a highly dynamic, adaptive routing scheme to deal with the high rate of topology changes due to fading of indoor wireless channels. Besides that, energy consumption rate needs to be consistently distributed among sensor nodes and efficient utilization of battery power is essential. If only the link reliability metric is considered in the routing scheme, it may create long hops routes, and the high quality paths will be frequently used. This leads to shorter lifetime of such paths; thereby the entire network's lifetime will be significantly minimized. This paper briefly presents a reliable load-balanced routing (RLBR) scheme for indoor ad hoc wireless sensor networks, which integrates routing information from different layers. The proposed scheme aims to redistribute the relaying workload and the energy usage among relay sensor nodes to achieve balanced energy dissipation; thereby maximizing the functional network lifetime. RLBR scheme was tested and benchmarked against the TinyOS-2.x implementation of MintRoute on an indoor testbed comprising 20 Mica2 motes and low power listening (LPL) link layer provided by CC1000 radio. RLBR scheme consumes less energy for communications while reducing topology repair latency and achieves better connectivity and communication reliability in terms of end-to-end packets delivery performance

Modelling and Verification of a Cluster-tree Formation Protocol Implementation for the IEEE 802.15.4 TSCH MAC Operation Mode

Correct and efficient initialization of wireless sensor networks can be challenging in the face of many uncertainties present in ad hoc wireless networks. In this paper we examine an implementation for the formation of a cluster-tree topology in a network which operates on top of the TSCH MAC operation mode of the IEEE 802.15.4 standard, and investigate it using formal methods. We show how both the mCRL2 language and toolset help us in identifying scenarios where the implementation does not form a proper topology. More importantly, our analysis leads to the conclusion that the cluster-tree formation algorithm has a super linear time complexity. So, it does not scale to large networks.Comment: In Proceedings MARS 2017, arXiv:1703.0581

The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks

Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I

Wireless Sensor Network Infrastructure: Construction and Evaluation

International audienceLarge area wireless sensor deployments rely on multi-hop communications. Efficient packet transmissions and virtual topologies, which structure sensor networks, are two main features for efficient energy management in wireless sensor networks. This paper aims to present a distributed and low-cost topology construction algorithm for wireless sensor networks, addressing the following issues: large-scale, random network deployment, energy efficiency and small overhead. We propose structuring nodes in zones, meant to reduce the global view of the network to a local one. This zone-based architecture is the infrastructure used by our hierarchical routing protocol. The experimental results show that the proposed algorithm has low overhead and is scalable