Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs

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

Simulation study for wireless sensor networks and load sharing routing protocol to increase network life and connectivity

LSU SensorSimulator is a framework for simulating wireless sensor networks. It is a customizable and extendible simulator, which allows testing and analyzing software for wireless sensor networks. The users can subclass the framework classes and customize the behavior of various network layers. This subclassing gives a way to the developers an opportunity to analyze and investigate, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, independent of hardware constraint. The results are compared against the simulation results for ns-2 for routing protocols Directed Diffusion and GEAR. Through the comparison of results for scalability, performance and memory utilization it is observed that LSU SensorSimulator performs much better. Buddy load sharing routing protocol is a routing protocol which can be combined with any geographically aware routing protocol to increase the network life and connectivity. The performance of Buddy load sharing algorithm for network life, and it is found that for a very negligible overhead the network life and connectivity and be improved by buddy load sharing

Non-Gaussian Hybrid Transfer Functions: Memorizing Mine Survivability Calculations

Hybrid algorithms and models have received significant interest in recent years and are increasingly used to solve real-world problems. Different from existing methods in radial basis transfer function construction, this study proposes a novel nonlinear-weight hybrid algorithm involving the non-Gaussian type radial basis transfer functions. The speed and simplicity of the non-Gaussian type with the accuracy and simplicity of radial basis function are used to produce fast and accurate on-the-fly model for survivability of emergency mine rescue operations, that is, the survivability under all conditions is precalculated and used to train the neural network. The proposed hybrid uses genetic algorithm as a learning method which performs parameter optimization within an integrated analytic framework, to improve network efficiency. Finally, the network parameters including mean iteration, standard variation, standard deviation, convergent time, and optimized error are evaluated using the mean squared error. The results demonstrate that the hybrid model is able to reduce the computation complexity, increase the robustness and optimize its parameters. This novel hybrid model shows outstanding performance and is competitive over other existing models

Dtn and non-dtn routing protocols for inter-cubesat communications: A comprehensive survey

CubeSats, which are limited by size and mass, have limited functionality. These miniaturised satellites suffer from a low power budget, short radio range, low transmission speeds, and limited data storage capacity. Regardless of these limitations, CubeSats have been deployed to carry out many research missions, such as gravity mapping and the tracking of forest fires. One method of increasing their functionality and reducing their limitations is to form CubeSat networks, or swarms, where many CubeSats work together to carry out a mission. Nevertheless, the network might have intermittent connectivity and, accordingly, data communication becomes challenging in such a disjointed network where there is no contemporaneous path between source and destination due to satellites’ mobility pattern and given the limitations of range. In this survey, various inter-satellite routing protocols that are Delay Tolerant (DTN) and Non Delay Tolerant (Non-DTN) are considered. DTN routing protocols are considered for the scenarios where the network is disjointed with no contemporaneous path between a source and a destination. We qualitatively compare all of the above routing protocols to highlight the positive and negative points under different network constraints. We conclude that the performance of routing protocols used in aerospace communications is highly dependent on the evolving topology of the network over time. Additionally, the Non-DTN routing protocols will work efficiently if the network is dense enough to establish reliable links between CubeSats. Emphasis is also given to network capacity in terms of how buffer, energy, bandwidth, and contact duration influence the performance of DTN routing protocols, where, for example, flooding-based DTN protocols can provide superior performance in terms of maximizing delivery ratio and minimizing a delivery delay. However, such protocols are not suitable for CubeSat networks, as they harvest the limited resources of these tiny satellites and they are contrasted with forwarding-based DTN routing protocols, which are resource-friendly and produce minimum overheads on the cost of degraded delivery probability. From the literature, we found that quota-based DTN routing protocols can provide the necessary balance between delivery delay and overhead costs in many CubeSat missions

Performance and energy efficiency in wireless self-organized networks

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