Polytype target coverage scheme for heterogeneous wireless sensor networks using linear programming

This paper is a performance survey on the residual energy of nodes in a wireless sensor network (WSN). Wireless sensor nodes are limited in application due to constraints in energy of nodes’ battery and addressing the problem of energy management is essential to lengthen the life of a deployed network of wireless sensors. In the method used, Sensor nodes were equally distributed on the complete border of the network field. An exclusive cluster, six hierarchical, and eighteen hierarchical clusters were formed based on even partition of the border of the network field. The choice of Cluster Head (CH) within each cluster formed was based on selection of a sensor node with minimal transmission distance to the Base Station. A comparison of the various hierarchical scenarios was simulated in MATLAB. The mean residue energies (MREs) after the network lifetime are 3%, 52%, and 35% of the initial node energy for single, six and eighteen hierarchical clusters respectively. The residual energies of sensor nodes above the recorded MREs were taken on a class interval of 50’s of the node identity (nid) and respective averages of residual energies of sensor nodes (AEr) of each selected class interval were evaluated. Based on the result, certain categories of sensor nodes at a section of the network field indicated that the battery energy of the affected nodes was not maximally utilized thereby leading to enormous residual energy. It was concluded that the residual energy of nodes in a WSN could be optimized to extend the lifetime.

We develop new algorithms for spatial field reconstruction, exceedance level estimation and classification in heterogeneous (mixed analog & digital sensors) Wireless Sensor Networks (WSNs). We consider spatial physical phenomena which are observed by a heterogeneous WSN, meaning that it consists partially of sparsely deployed high-quality sensors and partially of low-quality sensors. The high-quality sensors transmit their (continuous) noisy observations to the Fusion Centre (FC), while the low-quality sensors first perform a simple thresholding operation and then transmit their binary values over imperfect wireless channels to the FC. The resulting observations are mixed continuous and discrete (1-bit decisions) observations, and are combined in the FC to solve the inference problems. We first formulate the problem of spatial field reconstruction, exceedance level estimation and classification in such heterogeneous networks. We show that the resulting posterior predictive distribution, which is key in fusing such disparate observations, involves intractable integrals. To overcome this problem, we develop an algorithm that is based on a multivariate series expansion approach resulting in a Saddle-point type approximation. We then present comprehensive study of the performance gain that can be obtained by augmenting the high-quality sensors with low-quality sensors using real data of insurance storm surge database known as the Extreme Wind Storms Catalogue.

Recent advancements in miniaturization and inter-operability of wireless technologies have enabled a variant of Wireless Sensor Network (WSN), called Heterogeneous Wireless Sensor Network (HWSN). This plays a significant role in most popular applications of WSN such as habitat monitoring, volcano monitoring, military applications, etc. Similar to WSN, power resources are of utmost importance in HWSN too. Hence, several techniques have already been proposed to achieve energy-efficient network operations in heterogeneous networks. Among all those proposed schemes, the notion of clustering has proved its worth in obtaining energy-efficient clusters throughout the network. However, most of such clustering-based schemes utilize a dynamic probabilistic approach to deal with multilevel energy heterogeneity, which consumes many nodes' energy in the cluster formation. Moreover, with the varying degree of energy heterogeneity, most probabilistic schemes underperform and fail to compete. In this work, a Metaheuristic Multilevel Heterogeneous Clustering Technique (MMHCT) for Heterogeneous Wireless Sensor Networks has been proposed. MMHCT not only reduces the energy consumption in cluster-formation over the network rounds but also distributes the load evenly among the clusters to prolong the network lifetime. The supremacy of the proposed scheme is shown through various experiments against a state-of-the-art scheme, DEBCRP (Differential Evolution Based Clustering Routing Protocol) and the results confirm gains of 50%, 29.69%, 30.22%, 65.65%, & 37.17% in terms of network lifetime under 1-level, 2-level, 3-level, 4-level, & 5-level of energy heterogeneity respectively.

Data aggregation processes aim to reduce the amount of exchanged data in wireless sensor networks and consequently minimize the packet overhead and optimize energy efficiency. Securing the data aggregation process is a real challenge since the aggregation nodes must access the relayed data to apply the aggregation functions. The data aggregation security problem has been widely addressed in classical homogeneous wireless sensor networks, however, most of the proposed security protocols cannot guarantee a high level of security since the sensor node resources are limited. Heterogeneous wireless sensor networks have recently emerged as a new wireless sensor network category which expands the sensor nodes’ resources and capabilities. These new kinds of WSNs have opened new research opportunities where security represents a most attractive area. Indeed, robust and high security level algorithms can be used to secure the data aggregation at the heterogeneous aggregation nodes which is impossible in classical homogeneous WSNs. Contrary to the homogeneous sensor networks, the data aggregation security problem is still not sufficiently covered and the proposed data aggregation security protocols are numberless. To address this recent research area, this paper describes the data aggregation security problem in heterogeneous wireless sensor networks and surveys a few proposed security protocols. A classification and evaluation of the existing protocols is also introduced based on the adopted data aggregation security approach.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

In this paper, we propose a symmetric key establishment scheme for wireless sensor networks which tries to minimize the resource usage while satisfying the security requirements. This is accomplished by taking advantage of the communication pattern of wireless sensor networks and adopting heterogeneous wireless sensor networks. By considering the unique communication pattern of wireless sensor networks due to the nature of information gathering from the physical world, the number of keys to be established is minimized and, consequently, the overhead spent for establishing keys decreases. With heterogeneous wireless sensor networks, we can build a hybrid scheme where a small number of powerful nodes do more works than a large number of resource-constrained nodes to provide enhanced security service such as broadcast authentication and reduce the burden of resource-limited nodes. In addition, an on-demand key establishment scheme is introduced to support extra communications and optimize the resource usage. Our performance analysis shows that the proposed scheme is very efficient and highly scalable in terms of storage, communication and computation overhead. Furthermore, our proposed scheme not only satisfies the security requirements but also provides resilience to several attacks.

Coverage has recently emerged as a premier research topic. More and more research focused on coverage in wireless sensor networks using Voronoi. While most existing research efforts in the area of wireless sensor networks have focused on networks with nodes which have the same capabilities. But for Heterogeneous Wireless Sensor Networks (HWSN), which is more universal, there is a lack of study for using Voronoi solves the problem of coverage. In this paper we address on X-Voronoi for solve coverage in heterogeneous networks. Simulations confirm that the X-Voronoi is able to solve the problem of analyzing coverage performance in heterogeneous networks. To our knowledge, this is the first study on Voronoi for Heterogeneous 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.

In Wireless Sensor Networks the nodes have restricted battery power and the exhaustion of battery depends on various issues. In recent developments, various clustering protocols have been proposed to diminish the energy depletion of the node and prolong the network lifespan by reducing power consumption. However, each protocol is inappropriate for heterogeneous wireless sensor networks. The efficiency of heterogeneous wireless sensor networks declines as changing the node heterogeneity. This paper reviews cluster head selection criteria of various clustering protocols for heterogeneous wireless sensor networks in terms of node heterogeneity and compares the performance of these protocols on several parameters like clustering technique, cluster head selection criteria, nodes lifetime, energy efficiency under two-level and three-level heterogeneous wireless sensor networks protocols Stable Election Protocol (SEP), Zonal-Stable Election Protocol (ZSEP), Distributed Energy-Efficient Clustering (DEEC), A Direct Transmission And Residual Energy Based Stable Election Protocol (DTRE-SEP), Developed Distributed Energy-Efficient Clustering (DDEEC), Zone-Based Heterogeneous Clustering Protocol (ZBHCP), Enhanced Distributed Energy Efficient Clustering (EDEEC), Threshold Distributed Energy Efficient Clustering (TDEEC), Enhanced Stable Election Protocol (SEP-E), and Threshold Stable Election Protocol (TSEP). The comparison has shown that the TDEEC has very effective results over other over two-level and three-level heterogeneous wireless sensor networks protocols and has extended the unstable region significantly. From simulations, it can also be proved that adding node heterogeneity can significantly increase the network life.

Study on energy efficient routing protocols scheme in heterogeneous wireless sensor networks (network & mobility)

Ongoing advancements in electromechanical, power electronics and wireless communications have made possible the use of wireless sensor networks in remote applications. A wide range of applications such as monitoring of environmental conditions, forest fire protection, disaster management, and target monitoring in military applications utilize these sensor networks to solve problems. This has made wireless sensor networks the hottest topic for research today. These remote and unattended applications require a huge number of sensor nodes working efficiently together for a common goal. Since sensor nodes have limited resources, like processing, power and sensing capacity, these resources need to be used in efficient manner in order to improve a network’s lifetime. One of the most important methods to achieve this is using clusters. Nodes may not have the same energy levels, which makes it even more important for these clusters to work efficiently together to save power. Wireless sensor networks are of homogeneous and heterogeneous type. This paper presents a survey of energy-efficient clustering mechanisms in heterogeneous wireless sensor networks. Nodes in homogeneous wireless sensor networks have similar resources, however heterogeneous networks have nodes with different energy levels that can be effectively used to enhance a network’s lifetime.

This paper concentrates an efficient event detection approa ch exploiting data fusion technology for the heterogeneous wireless sensor networks. In this type of wireless sensor networks, each sensor is equipped with multiple sensing units. Particularly, in this paper, we study on the data fusion approach based on the type of complementary heterogeneous wireless sensor networks, and the fire disaster detection is utilized as an example of event det ection. The proposed event detection model is constructed of data fusion level and information fusion level. In the data fusion level , resource data are collected from the sensors which are both in the sensing field out of the sensing field. In the information fusion level , the event can be detected by computing the data fusion probabilities. For the fire disaster detection process, data collected from temperature sensors and humidity sensors are combined, and then all the measurements are supposed independent on normal random variables. Afterwards, the data fusion process is implemented utilizing genetic algorithm, by which the population is evolved through a predetermined number of consults. Therefore, for each generation of answers, a new set of artificial creatures can be calculated. Furthermore, the answers can be solved by fragments of the most suitable individuals. Finally, experiments are conducted on a series of simulations using the OMNeT++ tool. Compared with other methods, the proposed data fusion based event detection algorithm can effectively find the event through detecting the notify sta te and alert state, and performs better than other two methods both in the fusion quality and fusion efficiency.

Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide fault-tolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different transmission radii. Depending on the level of desired fault-tolerance, such problems can be categorized as: (1) full fault-tolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ges 1) vertex-disjoint paths between every pair of sensor and/or relay nodes; (2) partial fault-tolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ges 1) vertex-disjoint paths only between every pair of sensor nodes. Due to the different transmission radii of sensor nodes, these problems are further complicated by the existence of two different kinds of communication paths in heterogeneous wireless sensor networks, namely two-way paths, along which wireless communications exist in both directions; and one-way paths, along which wireless communications exist in only one direction. Assuming that sensor nodes have different transmission radii, while relay nodes use the same transmission radius, this paper comprehensively analyzes the range of problems introduced by the different levels of fault-tolerance (full or partial) coupled with the different types of path (one-way or two-way). Since each of these problems is NP-hard, we develop O(sigmak <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> )-approximation algorithms for both one-way and two-way partial fault-tolerance relay node placement, as well as O(sigmak <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> )-approximation algorithms for both one-way and two-way full fault-tolerance relay node placement (sigma is the best performance ratio of existing approximation algorithms for finding a minimum k-vertex connected spanning graph). To facilitate the applications in higher dimensions, we also extend these algorithms and derive their performance ratios in d-dimensional heterogeneous wireless sensor networks (d ges 3). Finally, heuristic implementations of these algorithms are evaluated via simulations.

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.

Due to the increase of Wireless Sensor Network (WSN) technologies demand, the optimal sensor node deployment is considered as one of the most important factors that directly affect the network coverage. Most researches in WSNs that solved the problem of coverage in homogeneous and heterogeneous cases are suffering from many drawbacks such as consumed energy and high cost. In this paper, we propose an efficient deployment model based on probabilistic sensing model (PSM) and harmony search algorithm (HSA) to achieve the balance between the network coverage performance and the network cost in a heterogeneous wireless sensor network (HEWSN). The HSA is used for deployment optimization of HEWSN nodes which makes a balance between the coverage and financial cost. The PSM is used to solve the overlapping problem among the sensors. The performance of the proposed model is analyzed in terms of coverage ratio and cost evaluations. The simulation results showed the capability of the proposed heterogeneous deployment model to achieve maximum coverage and a minimum number of sensors compared to homogeneous deployment. Furthermore, a comparative study with a meta-heuristic genetic-based algorithm in HEWSN has also been conducted, and its results confirm the superiority of the proposed model.