A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks

How to design an energy-efficient algorithm to maximize the network lifetime in complicated scenarios is a critical problem for heterogeneous wireless sensor networks(HWSN).In this paper, a clustering-tree topology control algorithm based on the energy forecast(CTEF) is proposed for saving energy and ensuring network load balancing, while considering the link quality, packet loss rate, etc. In CTEF, the average energy of the network is accurately predicted per round(the lifetime of the network is denoted by rounds) in terms of the difference between the ideal and actual average residual energy using central limit theorem and normal distribution mechanism, simultaneously. On this basis, cluster heads are selected by cost function(including the energy, link quality and packet loss rate) and their distance.The non-cluster heads are determined to join the cluster through the energy, distance and link quality. Furthermore, several noncluster heads in each cluster are chosen as the relay nodes for transmitting data through multi-hop communication to decrease the load of each cluster-head and prolong the lifetime of the network. The simulation results show the efficiency of CTEF. Compared with low-energy adaptive clustering hierarchy(LEACH), energy dissipation forecast and clustering management(EDFCM) and efficient and dynamic clustering scheme(EDCS)protocols, CTEF has longer network lifetime and receives more data packets at base station.

Novel routing protocol for heterogeneous wireless sensor networks

An improved LEACH for heterogeneous wireless sensor networks is proposed. Nodes are distributed in a sensing area that is divided into a number of same equilateral hexagons. Heterogeneous nodes act as the cluster heads and ordinary nodes act as those cluster sensors in all clusters. The structure of WSNs is a two-layer structure. The upper layer consists of all cluster heads and the lower layer consists of all ordinary sensors managed by their corresponding cluster heads. The cluster heads and the ordinary sensors establish their pairwise keys respectively through utilizing different methods. The arithmetic balances energy expense among all kinds of nodes, saves the node energy, and prolongs the life of wireless sensor networks. Additionally, Analysis demonstrates that the security of wireless sensor networks has been improved obviously even with some heterogeneous nodes.

Joint Design of Clustering and In-cluster Data Route for Heterogeneous Wireless Sensor Networks

A heterogeneous wireless sensor network comprises a number of inexpensive energy constrained wireless sensor nodes which collect data from the sensing environment and transmit them toward the improved cluster head in a coordinated way. Employing clustering techniques in such networks can achieve balanced energy consumption of member nodes and prolong the network lifetimes.In classical clustering techniques, clustering and in-cluster data routes are usually separated into independent operations. Although separate considerations of these two issues simplify the system design, it is often the non-optimal lifetime expectancy for wireless sensor networks. This paper proposes an integral framework that integrates these two correlated items in an interactive entirety. For that,we develop the clustering problems using nonlinear programming. Evolution process of clustering is provided in simulations. Results show that our joint-design proposal reaches the near optimal match between member nodes and cluster heads.

Low-latency Data Gathering with Reliability Guaranteeing in Heterogeneous Wireless Sensor Networks

In order to achieve low-latency and high-reliability data gathering in heterogeneous wireless sensor networks(HWSNs),the problem of multi-channel-based data gathering with minimum latency(MCDGML),which associates with construction of data gathering trees,channel allocation,power assignment of nodes and link scheduling,is formulated as an optimization problem in this paper.Then,the optimization problem is proved to be NP-hard.To make the problem tractable,firstly,a multi-channel-based low-latency(MCLL)algorithm that constructs data gathering trees is proposed by optimizing the topology of nodes.Secondly,a maximum links scheduling(MLS)algorithm is proposed to further reduce the latency of data gathering,which ensures that the signal to interference plus noise ratio(SINR)of all scheduled links is not less than a certain threshold to guarantee the reliability of links.In addition,considering the interruption problem of data gathering caused by dead nodes or failed links,a robust mechanism is proposed by selecting certain assistant nodes based on the defined one-hop weight.A number of simulation results show that our algorithms can achieve a lower data gathering latency than some comparable data gathering algorithms while guaranteeing the reliability of links,and a higher packet arrival rate at the sink node can be achieved when the proposed algorithms are performed with the robust mechanism.

Optimal Control of Heterogeneous-Susceptible-Exposed-Infectious-Recovered-Susceptible Malware Propagation Model in Heterogeneous Degree-Based Wireless Sensor Networks

Heterogeneous wireless sensor networks(HWSNs)are vulnerable to malware propagation,because of their low configuration and weak defense mechanism.Therefore,an optimality system for HWSNs is developed to suppress malware propagation in this paper.Firstly,a heterogeneous-susceptible-exposed-infectious-recovered-susceptible(HSEIRS)model is proposed to describe the state dynamics of heterogeneous sensor nodes(HSNs)in HWSNs.Secondly,the existence of an optimal control problem with installing antivirus on HSNs to minimize the sum of the cumulative infection probabilities of HWSNs at a low cost based on the HSEIRS model is proved,and then an optimal control strategy for the problem is derived by the optimal control theory.Thirdly,the optimal control strategy based on the HSEIRS model is transformed into corresponding Hamiltonian by the Pontryagin’s minimum principle,and the corresponding optimality system is derived.Finally,the effectiveness of the optimality system is validated by the experimental simulations,and the results show that the infectious HSNs will fall to an extremely low level at a low cost.