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

Maximizing Network Lifetime of Wireless Sensor-Actuator Networks under Graph Routing

Process industries are adopting wireless sensor-actuator networks (WSANs) as the communication infrastructure. The dynamics of industrial environments and stringent reliability requirements necessitate high degrees of fault tolerance in routing. WirelessHART is an open industrial standard for WSANs that have seen world-wide deployments. WirelessHART employs graph routing schemes to achieve network reliability through multiple paths. Since many industrial devices operate on batteries in harsh environments where changing batteries are prohibitively labor-intensive, WSANs need to achieve long network lifetime. To meet industrial demand for long-term reliable communication, this paper studies the problem of maximizing network lifetime for WSANs under graph routing. We formulate the network lifetime maximization problem for WirelessHART networks under graph routing. Then, we propose the optimal algorithm and two more efficient algorithms to prolong the network lifetime of WSANs. Experiments in a physical testbed and simulations show our linear programming relaxation and greedy heuristics can improve the network lifetime by up to 50% while preserving the reliability benefits of graph routing

Energy aware topology control protocols for wireless sensor networks

Wireless Sensor Network has emerged as an important technology of the future due to its potential for application across a wide array of domains. The collaborative power of numerous autonomousremote sensing nodes self configured into a multi hop network permits in-depth accurate observation of any physical phenomenon. A stringent set of computational and resource constraints make the design and implementation of sensor networks an arduous task. The issue of optimizing the limited and often non-renewable energy of sensor nodes due to its direct impact on network lifetime dominates every aspect of wireless sensor networks. Existing techniques for optimizing energy consumption are based on exploiting node redundancy, adaptive radio transmission power and topology control. Topology control protocols significantly impact network lifetime, routing algorithms and connectivity. We classify sensor nodes as strong and weak nodes based on their residual energy and propose a novel topology control protocol (NEC) which extends network lifetime while guarantying minimum connectivity. Extensive simulations in Network-Simulator (ns-2) show that our protocol outperforms the existing protocols in terms of various performance metrics. We further explore the effectiveness of data aggregation paradigm as a solution to the dominant problem of maximizing energy utilization and increasing network bandwidth utilization in sensor networks. We propose a novel energy efficient data aggregation protocol based on the well-known k-Means algorithm. Our protocol achieves energy efficiency by reduced number of data transmissions at each level of a hierarchical sensor network. Our protocol exploits the spatial and temporal coherence between the data sensed by neighboring sensor nodes in a cluster to reduce the number of packet transmissions. Sensor nodes apply k-Means algorithm to the raw data to generate a reduced set of mean values and forward this modified data set to cluster-head nodes. We further prove the effectiveness of our protocol in providing increased energy conservation in the network by extensive simulation results