Survey on node deployment in wireless sensor networks

Node deployment strategy plays an important role in wireless sensor networks(WSNs)application because it determines the coverage,connectivity and network lifetime of WSNs.This paper reports the current research on the optimization means for achieving the desirable design goals in various applications.We categorize the placements strategies into are the static and the dynamic according to whether the node position change after the network is operational.The coverage,connectivity and energy consumption of WSNs are analysed and discussed in detail.

Genetic Algorithm Based Node Deployment in Hybrid Wireless Sensor Networks

In hybrid wireless sensor networks composed of both static and mobile sensor nodes, the random deployment of stationary nodes may cause coverage holes in the sensing field. Hence, mobile sensor nodes are added after the initial deployment to overcome the coverage holes problem. To achieve optimal coverage, an efficient algorithm should be employed to find the best positions of the additional mobile nodes. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the coverage holes problem. The proposed algorithm determines the minimum number and the best locations of the mobile nodes that need to be added after the initial deployment of the stationary nodes. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of the overall coverage ratio and the number of additional mobile nodes.

Cluster Based Secure Dynamic Keying Technique for Heterogeneous Mobile Wireless Sensor Networks

In Heterogeneous Wireless Sensor Networks, the mobility of the sensor nodes becomes essential in various applications. During node mobility, there are possibilities for the malicious node to become the cluster head or cluster member. This causes the cluster or the whole network to be controlled by the malicious nodes. To offer high level of security, the mobile sensor nodes need to be authenticated. Further, clustering of nodes improves scalability, energy efficient routing and data delivery. In this paper, we propose a cluster based secure dynamic keying technique to authenticate the nodes during mobility. The nodes with high configuration are chosen as cluster heads based on the weight value which is estimated using parameters such as the node degree, average distance, node's average speed, and virtual battery power. The keys are dynamically generated and used for providing security. Even the keys are compromised by the attackers, they are not able to use the previous keys to cheat or disuse the authenticated nodes. In addition, a bidirectional malicious node detection technique is employed which eliminates the malicious node from the network. By simulation, it is proved that the proposed technique provides efficient security with reduced energy consumption during node mobility.

Wireless sensor networks in relic protection:deployment methodology and cross-layer design

This paper describes the deployment optimization technology and the cross-layer design of a surveil-lance WSN system applied in relic protection.Facing the typical technical challenges in the applicationcontext of relic protection,we firstly propose a deployment technology based on ant colony optimization al-gorithm(DT-ACO)to overcome the difficulties in communication connectivity and sensing coverage.Meanwhile,DT-ACO minimizes the overall cost of the system as much as possible.Secondly we proposea novel power-aware cross-layer scheme(PACS)to facilitate adjustable system lifetime and surveillanceaccuracy.The performance analysis shows that we achieve lower device cost,significant extension of thesystem lifetime and improvement on the data delivery rate compared with the traditional methods.

Energy-Efficient Area Coverage in Heterogeneous Energy Wireless Sensor Networks

Sensing coverage and energy consumption are two primary issues in wireless sensor networks. Sensing coverage is closely related to network energy consumption. The performance of a sensor network depends to a large extent on the sensing coverage, and its lifetime is determined by its energy consumption. In this paper, an energy-efficient Area Coverage protocol for Heterogeneous Energy sensor networks (ACHE) is proposed. ACHE can achieve a good performance in terms of sensing area coverage, lifetime by minimizing energy consumption for control overhead, and balancing the energy load among all nodes. Adopting the hierarchical clustering idea, ACHE selects the active nodes based on the average residual energy of neighboring nodes and its own residual energy parameters. Our simulation demonstrates that ACHE not only provide the high quality of sensing coverage, but also has the good performance in the energy efficiency. In addition, ACHE can better adapt the applications with the great heterogeneous energy capacities in the sensor networks, as well as effectively reduce the control overhead.

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.

Study on key management scheme for heterogeneous wireless sensor networks

Heterogeneous wireless sensor network( HWSN) is composed of different functional nodes and is widely applied. With the deployment in hostile environment,the secure problem of HWSN is of great importance; moreover,it becomes complex due to the mutual characteristics of sensor nodes in HWSN. In order to enhance the network security,an asymmetric key pre-distributed management scheme for HWSN is proposed combining with authentication process to further ensure the network security; meanwhile,an effective authentication method for newly added nodes is presented. Simulation result indicates that the proposed scheme can improve the network security while reducing the storage space requirement efficiently.

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.

Multi-sink Deployment Strategy for Wireless Sensor Networks Based on Improved Particle Swarm Clustering Optimization Algorithm

In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deploying multiple sink nodes in WSNs is an effective strategy to solve this problem.A multi-sink deployment strategy based on improved particle swarm clustering optimization(IPSCO) algorithm for WSNs is proposed in this paper.The IPSCO algorithm is a combination of the improved particle swarm optimization(PSO) algorithm and K-means clustering algorithm.According to the sink nodes number K,the IPSCO algorithm divides the sensor nodes in the whole network area into K clusters based on the distance between them,making the total within-class scatter to minimum,and outputs the center of each cluster.Then,multiple sink nodes in the center of each cluster can be deployed,to achieve the effects of partition network reasonably and deploy multi-sink nodes optimally.The simulation results show that the deployment strategy can prolong the network lifetime.

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 non-cluster 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. © 2014 Chinese Association of Automation.

Reliable Data Storage in Heterogeneous Wireless Sensor Networks by Jointly Optimizing Routing and Storage Node Deployment

In the era of big data,sensor networks have been pervasively deployed,producing a large amount of data for various applications.However,because sensor networks are usually placed in hostile environments,managing the huge volume of data is a very challenging issue.In this study,we mainly focus on the data storage reliability problem in heterogeneous wireless sensor networks where robust storage nodes are deployed in sensor networks and data redundancy is utilized through coding techniques.To minimize data delivery and data storage costs,we design an algorithm to jointly optimize data routing and storage node deployment.The problem can be formulated as a binary nonlinear combinatorial optimization problem,and due to its NP-hardness,designing approximation algorithms is highly nontrivial.By leveraging the Markov approximation framework,we elaborately design an efficient algorithm driven by a continuous-time Markov chain to schedule the deployment of the storage node and corresponding routing strategy.We also perform extensive simulations to verify the efficacy of our algorithm.

Optimal Deployment of Heterogeneous Nodes to Enhance Network Invulnerability

Wireless sensor networks(WSN)can be used in many fields.In wireless sensor networks,sensor nodes transmit data in multi hop mode.The large number of hops required by data transmission will lead to unbalanced energy consumption and large data transmission delay of the whole network,which greatly affects the invulnerability of the network.Therefore,an optimal deployment of heterogeneous nodes(ODHN)algorithm is proposed to enhance the invulnerability of the wireless sensor networks.The algorithm combines the advantages of DEEC(design of distributed energy efficient clustering)clustering algorithm and BAS(beetle antenna search)optimization algorithm to find the globally optimal deployment locations of heterogeneous nodes.Then,establish a shortcut to communicate with sink nodes through heterogeneous nodes.Besides,considering the practical deployment operation,we set the threshold of the mobile location of heterogeneous nodes,which greatly simplifies the deployment difficulty.Simulation results show that compared with traditional routing protocols,the proposed algorithm can make the network load more evenly,and effectively improve energy-utilization and the fault tolerance of the whole network,which can greatly improve the invulnerability of the wireless sensor networks.

Energy Proficient Reliable Rim Routing Technique for Wireless Heterogeneous Sensor Networks Lifespan Fortification

Sensor nodes are mainly shielded in the field with limited power supply. In Wireless Sensor Networks, there must be a requirement of an efficient power management, because sensor nodes are deployed in unman attended area with non-rechargeable batteries. Power management can be done by different methods of routing protocols. The proposed Reliable Rim Routing (3R) technique is based on hybrid routing protocol for homogeneous and heterogeneous system for WSNs to ameliorate the performance of the overall system. In 3R, total node deployment area can be multipart in terms of rim and in each rim, and some of the sensor nodes transmit their sensed data directly to base station, and meanwhile remaining sensor nodes send the data through clustering technique to base station like SEP. Proposed 3R technique implementation proves its enhanced WSNs lifetime of 70% energy consumption and 40% throughput compared with existing protocols. Simulation and evaluation results outperformed in terms of energy consumption with increased throughput and network lifetime.

Sensor deployment strategy for chain-type wireless underground mine sensor network

Wireless sensor networks (WSNs) are very important for monitoring underground mine safety. Sensor node deployment affects the performances of WSNs. In our study, a chain-type wireless underground mine sensor network (CWUMSN) is first pre- sented. A CWUMSN can monitor the environment and locate miners in underground mines. The lowest density deployment strate- gies of cluster head nodes are discussed theoretically. We prove that the lifetime of CWUMSN with a non-uniform deployment strategy is longer than with a uniform deployment strategy. Secondly, we present the algorithm of non-uniform lowest density de- ployment of cluster head nodes. Next, we propose a dynamic choice algorithm of cluster head nodes for CWUMSN which can im- prove the adaptability of networks. Our experiments of CWUMSN with both non-uniform lowest density and uniform lowest den- sity deployments are simulated. The results show that the lifetime of CWUMSN with non-uniform lowest density deployment is almost 2.5 times as long as that of the uniform lowest density deployment. This work provides a new deployment strategy for wire- less underground mine sensor networks and then effectively promotes the application of wireless sensor networks to underground mines.

Improved Implementation and Evaluation of Wireless Sensor Networks in Intelligent Building

A complete study for the implementation of wireless sensor networks in the intelligent building is presented. We carry out some experiments to find out the factors affecting the network performance. Several vital parameters which are related to the link quality are measured before deploying the actual system. And then, we propose an optimized routing protocol based on the analysis of the test data. We evaluate the deployment strategies to ensure the excellent performance of the wireless sensor networks under the real working conditions. And the evaluation results show that the presented system could satisfy the requirements of the applications in the intelligent building.

PUF-Based Key Distribution in Wireless Sensor Networks

Physical Unclonable Functions(PUFs)can be seen as kind of hardware one-way functions,who are easily fabricated but difficult to clone,duplicate or predict.Therefore,PUFs with unclonable and unpredictable properties are welcome to be applied in designing lightweight cryptography protocols.In this paper,a Basic Key Distribution Scheme(Basic-KDS)based on PUFs is firstly proposed.Then,by employing different deployment modes,a Random Deployment Key Distribution Scheme(RD-KDS)and a Grouping Deployment Key Distribution Scheme(GD-KDS)are further proposed based on the Basic-KDS for large scale wireless sensor networks.In our proposals,a sensor is not pre-distributed with any keys but will generate one by the embedded PUF when receiving a challenge from the gateway,which provides perfect resilience against sensor capture attacks.Besides,the unclonable and unpredictable properties of PUF guarantee the key uniqueness and two-way authentication.Analysis and experiment results show that our proposals have better performances in improving the resilience,secure-connectivity,and efficiency as compared to other schemes.

Monte Carlo Analysis of Nodes Deployment in Wireless Sensor Network Using Range-Free Location Methods

A Monte Carlo Analysis of nodes deployment for large-scale and non-homogeneous wireless sensor networks, has been done. Through simulations of random deployments of nodes over a square area using different densities, assuming that our network is composed by Anchor nodes （special sensors with known position） and simple Sensor nodes, the latter are supposed to estimate their own position after being placed within the coverage area with the minimum Anchor nodes needed to ＇feed＇ them with the necessary information. The goal is then to assist decision-makers in selecting among different alternatives to deploy the networks, according to resources features and availability, hence this method provides an estimate value of how many Anchor nodes should be deployed in a given area to trigger the location algorithm in the greatest possible number of Sensor nodes in the network.

Highly Resilient Key Distribution Strategy for Multi-level Heterogeneous Sensor Networks by Using Deployment Knowledge

The most important problem in the security of wireless sensor network (WSN) is to distribute keys for the sensor nodes and to establish a secure channel in an insecure environment. Since the sensor node has limited resources, for instance, low battery life and low computational power, the key distribution scheme must be designed in an efficient manner. Recently many studies added a few high-level nodes into the network, called the heterogeneous sensor network (HSN). Most of these studies considered an application for two-level HSN instead of multi-level one. In this paper, we propose some definitions for multi-level HSN, and design a novel key management strategy based on the polynomial hash tree (PHT) method by using deployment knowledge. Our proposed strategy has lower computation and communication overheads but higher connectivity and resilience.

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.

An Efficient Priority Based Routing Technique That Maximizes the Lifetime and Coverage of Wireless Sensor Networks

Recent development in sensor technologies makes wireless sensor networks (WSN) very popular in the last few years. A limitation of most popular sensors is that sensor nodes have a limited battery capacity that leads to lower the lifetime of WSN. For that, it raises the need to develop energy efficient solutions to keep WSN functioning for the longest period of time. Due to the fact that most of the nodes energy is spent on data transmission, many routing techniques in the literature have been proposed to expand the network lifetime such as the Online Maximum Lifetime heuristics (OML) and capacity maximization (CMAX). In this paper, we introduce an efficient priority based routing power management heuristic in order to increase both coverage and extend lifetime by managing the power at the sensor level. We accomplished that by setting priority metric in addition to dividing the node energy into two ratios;one for the sensor node originated data and the other part is for data relays from other sensors. This heuristic, which is called pERPMT (priority Efficient Routing Power Management Technique), has been applied to two well know routing techniques. Results from running extensive simulation runs revealed the superiority of the new methodology pERPMT over existing heuristics. The pEPRMT increases the lifetime up to 77% and 54% when compared to OML and CMAX respectively.