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

Relay selection methods for maximizing the lifetime of wireless sensor networks

Combined analytical and fuzzy techniques are proposed for improving the battery lifetime, performance, as well as energy efficiency of wireless sensor networks (WSNs) with the aid of efficient relay selection methods. We determine the best relay selection method by striking an appealing performance versus network lifetime trade-off. Furthermore, the beneficial regions of cooperation are determined considering asymmetric traffic scenarios, where relaying provides energy saving

Leveraging Discrete Fourier Transform to Reduce Power Consumption in Underwater Wireless Sensor Network Communications

Wireless Sensor Networks (WSNs) have become an important means of gathering environmental and physical information from a wide range of areas. WSNs could be used in underground, aboveground and underwater applications. In this work, we propose a new solution for underwater Wireless Sensor Networks to overcome the problem caused by the ionized nature of seawater. This work presents a methodology to improve the lifetime of WSNs. The wireless sensors have three main functions: sensing, processing and transmitting. The first two consume very less power compared to the third. Thus, we need to guarantee the successful transmission of signal with nominal and efficient use of power to improve the lifetime of the sensors. Improving the lifetime of these sensors will improve the experience of the end user, as the information-gathering lifetime of the sensors increases. Our validated results showed reduction in the power consumption, thus improving the lifetime and the signal loss rate

Distributed Algorithms for Improving Wireless Sensor Network Lifetime with Adjustable Sensing Range

Wireless sensor networks are made up of a large number of sensors deployed randomly in an ad-hoc manner in the area/target to be monitored. Due to their weight and size limitations, the energy conservation is the most critical issue. Energy saving in a wireless sensor network can be achieved by scheduling a subset of sensor nodes to activate and allowing others to go into low power sleep mode, or adjusting the transmission or sensing range of wireless sensor nodes. In this thesis, we focus on improving the lifetime of wireless sensor networks using both smart scheduling and adjusting sensing ranges. Firstly, we conduct a survey on existing works in literature and then we define the sensor network lifetime problem with range assignment. We then propose two completely localized and distributed scheduling algorithms with adjustable sensing range. These algorithms are the enhancement of distributed algorithms for fixed sensing range proposed in the literature. The simulation results show that there is almost 20 percent improvement of network lifetime when compare with the previous approaches

Energy Consumption Minimization in WSN using BFO

The popularity of Wireless Sensor Networks (WSN) have increased rapidly and tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since sensor devices rely on battery power and node energy and may be placed in hostile environments, so replacing them becomes a difficult task. Thus, improving the energy of these networks i.e. network lifetime becomes important. The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency using fuzzy logic controller. It presents a comparison between the different methods on the basis of the network lifetime. It compares existing ABC optimization method with BFO algorithm for different size of networks and different scenario. It provides cluster head selection method with good performance and reduced computational complexity. In addition it also proposes BFO as an algorithm for clustering of WSN which would result in improved performance with faster convergence

Spread Spectrum based QoS aware Energy Efficient Clustering Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of small, resource-constrained sensor nodes that form self-organizing, infrastructure-less, and ad-hoc networks. Many energy-efficient protocols have been developed in the network layer to extend the lifetime and scalability of these networks, but they often do not consider the Quality of Service (QoS) requirements of the data flow, such as delay, data rate, reliability, and throughput. In clustering, the probabilistic and randomized approach for cluster head selection can lead to varying numbers of cluster heads in different rounds of data gathering. This paper presents a new algorithm called "Spread Spectrum based QoS aware Energy Efficient Clustering for Wireless sensor Networks" that uses spread spectrum to limit the formation of clusters and optimize the number of cluster heads in WSNs, improving energy efficiency and QoS for diverse data flows. Simulation results show that the proposed algorithm outperforms classical algorithms in terms of energy efficiency and QoS

Lifetime Improvement in Wireless Sensor Networks via Collaborative Beamforming and Cooperative Transmission

Collaborative beamforming (CB) and cooperative transmission (CT) have recently emerged as communication techniques that can make effective use of collaborative/cooperative nodes to create a virtual multiple-input/multiple-output (MIMO) system. Extending the lifetime of networks composed of battery-operated nodes is a key issue in the design and operation of wireless sensor networks. This paper considers the effects on network lifetime of allowing closely located nodes to use CB/CT to reduce the load or even to avoid packet-forwarding requests to nodes that have critical battery life. First, the effectiveness of CB/CT in improving the signal strength at a faraway destination using energy in nearby nodes is studied. Then, the performance improvement obtained by this technique is analyzed for a special 2D disk case. Further, for general networks in which information-generation rates are fixed, a new routing problem is formulated as a linear programming problem, while for other general networks, the cost for routing is dynamically adjusted according to the amount of energy remaining and the effectiveness of CB/CT. From the analysis and the simulation results, it is seen that the proposed method can reduce the payloads of energy-depleting nodes by about 90% in the special case network considered and improve the lifetimes of general networks by about 10%, compared with existing techniques.Comment: Invited paper to appear in the IEE Proceedings: Microwaves, Antennas and Propagation, Special Issue on Antenna Systems and Propagation for Future Wireless Communication

IMPROVED VIRTUAL CIRCUIT ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS UNDER THE ASPECT OF POWER AWARENESS

Routing algorithms have shown their importance in the power aware wireless micro-sensor networks. In this paper first we present virtual circuit algorithm (VCRA), a routing algorithm for wireless sensor networks. We analyze the power utilized by nodes to lengthen the battery life and thus improving the lifetime of wireless sensor network. We discuss VCRA in comparison with the Multihoprouter, an algorithm developed by UC Berkeley. Then we present Improved Virtual Circuit Routing Algorithm (IVCRA) which is an improved form of VCRA. In IVCRA node failure detection and path repairing scheme has been implemented. We also present the energy analysis of IVCRA and prove that IVCRA is the best choice. We first implement our routing algorithms in simulator TOSSIM and then on real hardware of mica2 mote-sensor network platform and prove the reliable routing of the data packets from different nodes to the base station. The motes used as nodes in our mote-sensor network are from Berkeley USA. By using simulator POWERTOSSIM, we estimate and present the energy utilized by different nodes of the network. At the end we present a comparison of our work with the network layer of Zigbee/IEEE 802.15.4, which is an emerging standard for wireless sensor networks and then compare its energy efficiency with the packet size chosen for our algorithm

ENERGY AWARE ROUTING FOR WIRELESS SENSOR NETWORKS

Wireless sensor networks are used in improving conditions in the practical field and real life which lead researchers and developers to further research it and work into improving this field. These networks consist of sensor nodes that can help acquire data and information about temperature and pressure dependent on the environment of the location which are sent from. After all that, we are bounded by a really important factor which can determine everything which is Energy. Since sensor nodes send data and information to web applications, they need an energy source to operate. Their main energy source is their batteries which offer limited source of energy. Hence, various protocols are introduced to help in many parameters of a wireless sensor network such as increasing lifetime and decreasing consumption of energy, in other words, increasing the Energy Efficiency (EF). In this paper, we evaluate consumption of average energy for various protocols used in this context after each complete logical round for these protocols, such as Energy Efficient Clustering Scheme and Stable Election Protocol. Finally, we used Matlab tool to generate results which indicate that the protocol used in this paper is efficient and reliable