A Weighted Voronoi Diagram Based Self-deployment Algorithm for Heterogeneous Mobile Sensor Network in Three-Dimensional Space

We present geometric broadcast for sensor and actor networks (GBSA), a novel broadcasting protocol for heterogeneous wireless sensor and actor networks. While broadcasting is a very energy-expensive protocol, it is also widely used as a building block for a variety of other network layer protocols. Therefore, reducing the energy consumption by optimizing broadcasting is a major improvement in heterogenous sensor networking. GBSA is a distributed algorithm where nodes make local decisions on whether to transmit based on a geometric approach. GBSA does not need any neighborhood information and imposes very low communication overhead. GBSA is scalable to the change in network size, node type, node density and topology. GBSA accommodates seamlessly such network changes, including the presence of actors in heterogeneous sensor networks. Indeed GBSA takes advantage of actor nodes, and uses their resources when possible, thus reducing the energy consumption by sensor nodes. Through simulation evaluations, we show that GBSA is very scalable and its performance is improved by the presence of actors. At best of our knowledge, GBSA is the first broadcast protocol designed specifically for heterogeneous sensor and actor networks.

Mobile sensor networks has been more attention in recent years, which networking algorithm is one of the important issues of their research. Existing mobile networking algorithm is divided into three categories -virtual force method, the Voronoi diagram method and Delaunay triangulation method. This paper analyzes the deficiencies of these three methods, given a new mobile networking algorithm for large-scale mobile sensor networks, really distributed real-time response to network topology changes. Simulations show that the algorithm has good performance.

This paper proposes a novel deployment algorithm for wireless sensor networks namely VFIPO based on individual particle optimization (IPO) incorporated with virtual force (VF) algorithm, which overcomes the shortcomings of applying the VF algorithm. Simulation results verify that mobile nodes deployment with VFIPO outperforms the previous deployment algorithms such as VF, PSO, VFPSO and IPO based approaches with respect to effective coverage area and computation time.

In order to prolong the network lifetime, energy-aware protocols should be designed to adapt the characteristic of wireless sensor networks. Clustering is a kind of key routing technique used to reduce energy consumption. In this paper, a new clustering algorithm MNLC (Maximum Network Lifetime Clustering Algorithm) for energy heterogeneous sensor networks is proposed. The algorithm uses distributed, dynamic clustering process. On the one hand, cluster-head selection is primarily determined by the residual energy level of each node, on the other hand, the ordinary nodes select which cluster to join according to the remaining energy level of the candidate cluster-heads and the parameter of communication cost in a cluster, so as to effectively achieve the balanced distribution of energy loss in the network. Simulation results show that MNLC could better implement load balance and prolong the network lifetime in heterogeneous environments.

As more and more innovative applications of wireless sensor networks emerge, the need for deploying heterogeneous sensors with different functionalities and capabilities rise rapidly. In this study, we consider a heterogeneous sensor network containing at least two types of sensors: powerful sensors and normal sensors. Powerful sensors have higher energy and computing capacities, and can communicate with normal sensors using the same network interface. Communications between powerful sensors may thus be facilitated by building an overlay on top of the normal sensors. The topology of the overlay is critical. The overlay must have a low diameter to efficiently support upper layer applications such as resource discovery. It must also consider the energy consumption of the relaying normal sensors. In this paper, we propose a distributed overlay formation protocol to achieve the above goals. Through simulation, we compare our protocol with two overlay formation protocols, fully connected graph and minimum spanning tree. The results show that our proposed protocol can achieve better performance both in message latency and energy consumption.

Fault tolerant aggregation in heterogeneous sensor networks

Automatic localization is one of the major issues in Wireless Sensor Networks (WSN). DV-hop algorithm is a well-known localization algorithm in WSN but with limited localization accuracy. In this paper, an improved DV-hop localization algorithm in hybrid optical wireless sensor networks is proposed based on the optimization of the parameters in WSN. Various factors that affect the localization accuracy of the DV-hop algorithm in WSN are investigated, including the communication radius of the node, the number of beacon nodes and the number of the total nodes. As the DV-hop algorithm is applied into hybrid optical sensor and WSNs (O-WSN) with rectangular topology, different parameters have to be optimized accordingly. Simulation results show that the square topology outperforms the rectangle topology more than 45 % under the same network parameters using the improved DV-hop algorithm. Therefore another improved DV-hop called Sub-Square Weighted DV-hop (SSW DV-hop) is proposed for the rectangle topology. Both simulation and experiment results demonstrate that applying the SSW DV-hop algorithmin O-WSNs could significantly improve the localization accuracy.

In clustering algorithm of wireless sensor networks, to solve the problem of excessive energy consumption in the cluster heads with multilevel energies, an improved reactive three level heterogeneous stable election protocol is proposed by combining the reactive routing mechanism and multilevel heterogeneous networks.In cluster heads election phase of every round, the algorithm considers the residual energy and higher initial energy of all nodes to elect an optimal cluster head.Furthermore, reactive routing mechanism is employed here to minimize the number of nodes transmitting data to the cluster heads.Simulation results show that the improved routing protocol has better performance in the network life cycle and network energy consumption than SEP, SEP-E and ESEP-E protocol respectively such that it is more suitable for dealing with the problem of multilevel energy heterogeneous sensor network.

The wireless sensor networks (WSNs) are usually deployed among widely area for environmental monitoring, data collection and other applications. In order to reduce the energy consumption and extend the lifetime of WSNs, as well as receive the data quickly, a source-based data aggregation algorithm (SBDA) for clustering wireless sensor networks is proposed. The method aggregated the data from sensor nodes and marked different transmission priority for the data. Simulation results show that, compared to existing protocols, the proposed method achieves a longer life time, and a lower packet drop ratio.

Recently, network localization systems that are based on inter-node ranges have received significant attention. Geographic routing has been considered an application which can utilize the location information from these localization systems. In this paper, we firstly recognize that sensor network localization algorithms generate positioning data with different error patterns compared to those networks where node positions are determined directly from GNSS measurements. Secondly, by simulating practical sensor network scenarios using data from our localization algorithm, we observe that existing geographic routing algorithms in wireless sensor networks (WSNs) adopt very simplistic methods in the treatment of position error, without due consideration of error distribution. Additionally, an insight is given into localization algorithms for WSNs with inhomogeneous error environments. Our observations represent an initial step toward a detailed understanding and design of efficient geographic routing algorithms in location aware WSNs.

Limited battery power directly affects the performance and survival time of sensor networks. In this study, solar energy was used to provide additional energy for sensor nodes, and a clustering algorithm for heterogeneous wireless sensor networks (WSNs) based on a solar energy supply is proposed. A cluster head is selected on the basis of the self-replenishment state and the remaining energy of the nodes. A cluster-head selection mechanism and network layer multi-hop routing are adopted to balance the energy consumption of the network. A set of experiments showed that the proposed algorithm can effectively prolong the network lifetime, improve the stability and efficiency of the network, and balance the energy consumption compared with other algorithms under the same environmental energy supply.

In order to effectively reduce the redundant information transmission in the network, a data fusion algorithm based on extreme learning machine optimized by bat algorithm for mobile heterogeneous wireless sensor networks is proposed. In this paper, the data fusion process of mobile heterogeneous wireless sensor networks is mainly studied, and regards the nodes of wireless sensor networks as neurons in the neural network of extreme learning machines. The neural network of the extreme learning machine extracts the sensory data collected by mobile heterogeneous wireless sensor network and combines the collected sensor data with the clustering route to greatly reduce the amount of network data sent to the sink node. Aiming at the problem that the extreme learning machine randomly generates the input layer weight and the hidden layer threshold before training, the output result is unstable, affecting the data fusion efficiency and the long delay, a new method of data fusion for mobile heterogeneous wireless sensor networks based on extreme learning machine optimized by bat algorithm is proposed. Simulation experiments are carried out from two aspects: mobile heterogeneous wireless sensor networks and heterogeneous mobile heterogeneous wireless sensor networks. The simulation results show that compared with the traditional SEP algorithm, BP neural network algorithm and ELM algorithm, the proposed BAT-ELM-based data fusion algorithm can effectively reduce network traffic, save network energy, improve network work efficiency, and significantly prolong network's lifetime.

A large number of small sensors in wireless sensor network are battery-powered; one of the most important design criteria for this type of network is energy efficiency. Clustering provides an effective way for extending the lifetime of a sensor network. In this paper, we propose a maximum-votes and load-balance clustering algorithm (VLCA) for wireless sensor network Each sensor collects votes from their neighbors and calculates the total vote received. The more votes a sensor accumulates, the more important it is in the whole network During the clustering phase, sensors compete with each other based on the total votes each has received. The algorithm is completely distributed, locating-unaware and independent of network size and topology. Simulation results show that our VLCA can reduce the number of clusters by 20-50% and prolong the lifetime of a sensor network.

To the problem of randomly deployed nodes failing to guarantee the network coverage and the objects detection probability, this study puts forward a coverage optimization algorithm of wireless sensor network based on simplified virtual forces-oriented particle swarm with mutate mechanism (SVF-PS-MA), which would improve the update speed of particle swarm algorithm, guide the direction of particle evolution and speed up the algorithm convergence by dislodging attractive forces from the virtual forces. And this algorithm introduces the mutate mechanism, take the mutation for particles, improve the particles diversity and reduce the probability of particles falling into the local optimization. The result shows that the algorithm can improve the network coverage effectively, and guarantee less time-consumption.

In this work, we propose a small world model to design Heterogeneous Sensor Networks (HSNs). The proposed model takes into account the communication pattern of this network to create shortcuts directed to the monitoring node, decreasing data communication latency. The endpoints of these shortcuts are nodes with more powerful communication range and energy reserves to support the long communication range. However, this kind of communication causes a high interference in the wireless channel. For this, the proposed model uses the multi-interface and multi-channel capability of the MAC layer to reduce the number of collisions during data communication. Simulation results showed that with just a few powerful nodes, a wireless sensor network can be tuned into a HSN with small world features. Also, when the shortcuts are directed to the monitoring node and assigned to a different wireless channel, the number of collisions and the data communication latency are reduced.