Communication Pattern Based Key Establishment Scheme in Heterogeneous Wireless Sensor Networks

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.

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.

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.

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.

Mobile target tracking consists in detecting and locating targets in a surveillance region. Wireless Multimedia Sensor Networks (WMSN) can provide more information about the moving target than classical Wireless Sensor Networks (WSN), but their process and the transmission of multimedia data are costly which reduces the network's lifetime. In this paper, we propose a low-cost new solution for tracking a mobile target called EAOT (Energy Aware Object Tracking). It consists of a distributed cooperative algorithm that runs in heterogeneous Wireless Sensor Networks composed of both scalar and multimedia sensors. The scalar sensors (MS) are equipped with a motion detector; their role is to detect the target and then activate the camera sensors (CS) through message exchanges. We conducted simulations to evaluate the performance of the proposed mechanism in terms of tracking accuracy, number of exchanged messages, energy consumption, and spatial average deviation. The results are compared to two existing solutions: one based on simple camera sensors which always run in active mode and the other one based on the optimal camera node selection (OCNS) to track the target. The obtained results show that for the same number of nodes, EAOT consumes between 2.6% and 44% less energy than OCNS depending on the distribution of MS/CS.

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.

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.

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.

Distributed key management is a major challenge in the design and deployment of secure wireless sensor networks (WSNs). In most existing distributed key management schemes, a common assumption is that all sensor nodes have the same capability. However, recent studies have demonstrated that heterogeneities of the sensor nodes, in particular the heterogeneities of energy capacity and transmission capability, can significantly improve the connectivity and lifetime of the WSNs. Consequently, it is important to design key management schemes for heterogeneous WSN (HWSN). In this paper, we provide a distributed key management scheme for HWSNs. The main contribution of this paper is to develop analytical models for evaluating the performance of the proposed scheme in terms of connectivity, reliability, and resilience. Extensive simulation results show that, with a small number of heterogeneous nodes, the WSN can achieve higher key connectivity, better reliability, and higher resilience. The results also show that our analytical models can accurately predict the performance under a variety of conditions

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

Aiming at the transmission of heterogeneous data in heterogeneous networks, a topology optimization algorithm of heterogeneous wireless sensor networks based on local tree reconstruction is proposed, which can achieve better data transmission in the heterogeneous networks. First, the algorithm divides the nodes of the network into different layers by their hops and chooses different numbers of nodes as relay nodes in different layers. Second, the nodes are set with different initial energies in different layers. Because the packets of different nodes have different sizes, we adopt the corresponding data aggregation coefficients according to the actual data requirements of the network in data transmission. Finally, the lifetime of the network is prolonged by real-time updating of the topology of the tree during the data transmission. The simulations indicate that after the aforementioned three steps, the proposed algorithm prolongs the lifetime of the heterogeneous networks and improves the nodes utilization effectively.

Wireless sensor networks are the networks with wireless sensors disseminated in a region which sense various types of information and then transmit this information to the other nodes or to the final destination.These nodes sense the changes in the physical parameters similar totemperature, pressure, etc.The data sensed by these nodes are then approved to the Base Station (BS) for estimation.Wireless sensor networks are used for the variety of purposes like military surveillances, habitat monitoring, forest fire detections, landslide detections.This paper presents the new clustering algorithm by modifying SEP (Stable Election Protocol) for heterogeneous wireless sensor network, called EE-SEP.Energy Efficient -SEP protocol is used to increase the number of alive nodes and thereby increasing the energy efficiency, stability period and network lifetime and balancing the energy consumption.Simulation results show that proposed Energy Efficient SEP algorithm performs better as compared to SEP.

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.