Wireless Sensor Networks: Deployment

Wireless Sensor Networks (WSNs) are distributed systems composed of battery-powered nodes that sense and collect information about the physical world. They enable applications in a wide variety of domains including but not limited to environmental monitoring, health care and disaster management. In such applications, nodes communicate the
sensed information over multiple radio links until it reaches its destination referred to as the sink. As wireless communication is the most energy hungry operation, the data collection causes the biggest drain from battery. This motivates research on energy efficient mechanisms for data collection.

Though there is a plethora of protocols proposed in research literature, they are not designed to collaborate with the appli-cations. One opportunity from such collaboration is exploiting complete knowledge about application characteristics to make data collection more energy efficient. This enables underlying layers not to provision the resources more than the needs of the application and therefore save valuable battery power. The aim of this thesis is to explore a complex interplay between application characteristics and adaptive mechanisms across network stack using concrete real world deployments. It will propose a generic framework that integrates the adaptations to achieve near-optimal energy efficiency for heterogeneous applications.

The efficiency of sensor networks strongly depends on the routing protocol used. In this paper, we analyze three different types of routing protocols: LEACH, PEGASIS, and VGA. Sensor networks are simulated using Sensoria simulator. Several simulations are conducted to analyze the performance of these protocols including the power consumption and overall network performance. The simulation results, using same limited sensing range value, show that PEGASIS outperforms all other protocols while LEACH has better performance than VGA. Furthermore, the paper investigates the power consumption for all protocols. On the average, VGA has the worst power consumption when the sensing range is limited, while VGA is the best when the sensing range is increased.

The sensor networks, or more completely referred to as wireless sensor networks (WSNs), do not need a predetermined positioning in most cases. The sensor nodes (SNs) are randomly deployed in the SN's field, making a network. The deployment of the sensor nodes in the WSN depends on such an application, coverage area, and connectivity. The WSNs can deploy the SNs over a field with planning or deterministic topology, and self-organizing topologies. In the self-organizing topology, the SN's positions are formed randomly while the routes are unreliable and random. Because the random properties have many issues, it makes the SN's deployment becoming an essential issue. This paper aims to detect the most extensive area not covered by the sensor nodes in the WSN using a genetic algorithm (GA). Machine learning implementation has made a big through in widely computation use. The GA method could detect the sensor node-less area in the performance of the WSN with an accuracy of 91.67%.

In wireless sensor networks (WSNs), there are many factors, such as the reciprocal interference of wireless links, battlefield applications and nodes are exposed to poor physical protection medium. All of these result in the sensor nodes being more exposed to be attacked and compromised. Since sensors are normally energy limited in WSNs, it is constantly basic to conserve the node energy and expand the lifetime of the network. Besides, hierarchical clustering is deemed as one of the numerous ways to deal with the reduction of energy consumption of nodes and increasing the network lifetime in WSNs. This paper conspicuously introduces an efficient and secure malicious node detection model based on a hybrid clustering network for WSNs (ESMCH) which is based on a trusted mobile node. WSNs are still suffering from some attacks like Man-in-the-Middle Attack and Black hole Attack, so by using the ESMCH model, we can avoid these attacks. Finally, simulation results also indicate that the proposed model can increase the network lifetime, and achieve an efficient and secure clustering network.

Resource limitations of sensor nodes in wireless sensor networks (WSN) bound the performance on its implementations. Main concern becomes utilizing these limited resources (CPU, memory, bandwidth, battery) as efficient as possible. Their efficiency is mostly affected by the applied routing algorithm, which carries gathered data to inclined/intended destinations. In this paper, a novel routing algorithm, stateless weight routing (SWR), is proposed. The SWR differs from other protocols in many ways. Major feature of the SWR is its simplicity. It is a completely stateless protocol without requiring any network or neighborhood information for routing. This feature decreases packet transmissions and energy consumption dramatically. For reliability, data flows to the sink node over multiple paths. Moreover, nodes have the ability of recovering from voids. Nodes process each packet independently and apply an adaptive approach according to the current conditions. These mechanisms are part of the applied simple routing algorithm, the SWR. The resultant of these features assures flexibility and smartness at nodes and in the network. Therefore, topological changes have a little effect on data packet transmissions. Performance evaluation of the proposed approach shows that the SWR is scalable for WSNs whose topology change instantly and frequently as well as remain stationary.

The communication network where there is no requirement of infrastructure is termed as the wireless network. In wireless mode of communication the sensor nodes are established and provides help to the other sensor nodes directly or indirectly, the nodes available in the wireless network can play the role of the router or can work as the single node. There exist a wide range of applications of wireless network in today's communication scenario, as wide range of the applications are being supported by the wireless network which makes it more suitable and also due the decentralized facility provided by the network. The scalability of the network is increased as compared to the networks which are being supported by the wireless network, it is quite easy to identify the limitations of the network either the theoretical one or the practical one. The radio communication is being used for the administration and also for the implementation of the wireless network. The protection of information for long period time is very critical in many environments. Power is the most important concern for data transfer between wireless nodes. In this paper, we concern on the denial of sleep attack issue in WSN and also reviewed some of the methodologies for the same; DoS that targets a battery powered device's power supply in an effort to exhaust this constrained resource and reduce the network life time.

The emergence of sensor networks as one of the dominant technology trends in the coming decades has posed numerous unique challenges to researchers. These networks are likely to be composed of hundreds, and potentially thousands of tiny sensor nodes, functioning autonomously, and in many cases, without access to renewable energy resources. Cost constraints and the need for ubiquitous, invisible
deployments will result in small sized, resource-constrained sensor nodes. While the set of challenges in sensor networks are diverse, we focus on security of Wireless Sensor Network in this paper. We propose some of the security goal for Wireless Sensor Network. Further, security being vital to the acceptance and use of sensor networks for many applications; we have made an in depth threat analysis of Wireless Sensor Network. We also propose some countermeasures against these threats in Wireless Sensor Network.

In wireless sensor networks (WSNs), there are many factors, such as the reciprocal interference of wireless links, battlefield applications and nodes are exposed to poor physical protection medium. All of these result in the sensor nodes being more exposed to be attacked and compromised. Since sensors are normally energy limited in WSNs, it is constantly basic to conserve the node energy and expand the lifetime of the network. Besides, hierarchical clustering is deemed as one of the numerous ways to deal with the reduction of energy consumption of nodes and increasing the network lifetime in WSNs. This paper conspicuously introduces an efficient and secure malicious node detection model based on a hybrid clustering network for WSNs (ESMCH) which is based on a trusted mobile node. WSNs are still suffering from some attacks like Man-in-the-Middle Attack and Black hole Attack, so by using the ESMCH model, we can avoid these attacks. Finally, simulation results also indicate that the pr...

Wireless Sensor Networks (WSN) is widely deployed in different fields of applications of smart grid to provide reliable monitoring and controlling of the electric power grid. The objective of this paper is simulate and analyze impact of various smart grid environments on performance of four different WSN routing protocols namely the Low Energy Adaptive Clustering Hierarchy (LEACH) and Centralized LEACH (LEACT-C) as well as other two conventional protocols namely Minimum Transmission Energy (MTE) and Static Clustering. This analysis would be beneficial in making the correct choice of WSN routing protocols for various smart grid applications. The performance of the four protocols is simulated using NS-2 network simulation on Ubuntu. The results are analyzed and compared using number of data signals received at base station, energy consumption, and network lifetime as performance metrics.

Networks of wireless sensors are increasingly exploited in crucial applications of monitoring spatially correlated environmental phenomena such as temperature, rainfall, soil ingredients, and air pollution. Such a network provides an ability to monitor and model the environmental fields even at unobserved locations. This requires estimating number of sensors and their sampling locations which minimize the uncertainty of predictions. Therefore, the aim of this thesis is to present novel, efficient and practically feasible approaches to efficiently sample the environments, so that the uncertainties at predicted locations are minimized. Gaussian process (GP) is utilized to statistically model the spatial field. This thesis includes both stationary wireless sensor networks (SWSNs) and mobile robotic wireless sensor networks (MRWSNs), and thus the issues are correspondingly formulated into \textit{sensor selection} and \textit{sensor placement} problems, respectively. In the first part of this thesis, a novel performance metric for the sensor selection in the SWSNs, named average root mean square error, which reflects the average uncertainty of each predicted location, is proposed. In order to minimize this NP-hard and combinatorial optimization, a simulated annealing based algorithm is proposed so that the sensor selection problem is effectively addressed. Particularly, when considering the sensor selection in constrained environments, \textit{e.g.} gas phase hydrogen sulphide in a sewage system, a modified GP with a new covariance function is developed. A new yet efficient mutual information maximization criterion is also presented to select the most informative gaseous sensor locations along the sewer system. Furthermore, the second part of this thesis introduces centralized and distributed methods for spatial prediction over time in the MRWSNs. For the purpose of finding the optimal sampling paths of the mobile wireless sensors to take the most informative observations at each time iteration, a sampling strategy is proposed based on minimizing the uncertainty at all unobserved locations. A novel and very efficient optimality criterion for the adaptive sampling problem is then presented so that the minimization can be addressed by a greedy algorithm in polynomial time. The solution is proven to be bounded; and computational time of the proposed algorithm is illustrated to be practically feasible for the resource-constrained MRWSNs. In order to enhance the issue of computational complexity, Gaussian Markov random field (GMRF) is utilized to model the spatial field exploiting sparsity of the precision matrix. A new GMRF optimality criterion for the adaptive navigation problem is also proposed such that computational complexity of the resulting optimization is deterministic even with increasing number of measurements. The algorithms were tested and verified with different spatial phenomena data sets with appealing results.

The concentration of data traffic towards the sink in a wireless sensor network causes the nearby nodes to deplete their batteries quicker than other nodes, which leaves the sink stranded and disrupts the sensor data reporting. To mitigate this problem the usage of mobile sinks is proposed. Mobile sinks implicitly provide load-balancing and help achieving uniform energy-consumption across the network. However, the mechanisms to support the sink mobility (e.g., advertising the location of the mobile sink to the network) introduce an overhead in terms of energy consumption and packet delays. With these properties mobile sink routing constitutes an interesting research field with unique requirements. In this paper, we present a survey of the existing distributed mobile sink routing protocols. In order to provide an insight to the rationale and the concerns of a mobile sink routing protocol, design requirements and challenges associated with the problem of mobile sink routing are determined and explained. A definitive and detailed categorization is made and the protocols' advantages and drawbacks are determined with respect to their target applications.

Wireless sensor networks consist of a large number of sensor nodes having limited power. The most important feature of these networks is the presence of dynamic topology which will lead to the mobility of the nodes. This mobility requires a routing capable of adapting to these changes. Despite the power
restriction in these networks, the purpose in routing algorithm is not to find the shortest route; rather it is the power of each node which constitutes one of the most important issues. In this article, we have used soft computing techniques for routing in the network. The results obtained show that  the combined method based on soft computing as compared to previous methods some what improves the minimalization of used power.

In wireless sensor networks (WSNs), there are many factors, such as the reciprocal interference of wireless links, battlefield applications and nodes are exposed to poor physical protection medium. All of these result in the sensor nodes being more exposed to be attacked and compromised. Since sensors are normally energy limited in WSNs, it is constantly basic to conserve the node energy and expand the lifetime of the network. Besides, hierarchical clustering is deemed as one of the numerous ways to deal with the reduction of energy consumption of nodes and increasing the network lifetime in WSNs. This paper conspicuously introduces an efficient and secure malicious node detection model based on a hybrid clustering network for WSNs (ESMCH) which is based on a trusted mobile node. WSNs are still suffering from some attacks like Man-in-the-Middle Attack and Black hole Attack, so by using the ESMCH model, we can avoid these attacks. Finally, simulation results also indicate that the proposed model can increase the network lifetime, and achieve an efficient and secure clustering network.

In wireless sensor networks (WSNs), there are many factors, such as the reciprocal interference of wireless links, battlefield applications and nodes are exposed to poor physical protection medium. All of these result in the sensor nodes being more exposed to be attacked and compromised. Since sensors are normally energy limited in WSNs, it is constantly basic to conserve the node energy and expand the lifetime of the network. Besides, hierarchical clustering is deemed as one of the numerous ways to deal with the reduction of energy consumption of nodes and increasing the network lifetime in WSNs. This paper conspicuously introduces an efficient and secure malicious node detection model based on a hybrid clustering network for WSNs (ESMCH) which is based on a trusted mobile node. WSNs are still suffering from some attacks like Man-in-the-Middle Attack and Black hole Attack, so by using the ESMCH model, we can avoid these attacks. Finally, simulation results also indicate that the proposed model can increase the network lifetime, and achieve an efficient and secure clustering network.

The performance of a surveillance wireless sensor network is generally measured with its detection capability within a monitored zone. This capability is affected by various parameters such as the sensor count, the sensor range, the area width and the target mobility model. In real life examples it is observed that intruders prefer some favorite regions because of their geographical advantages within a monitored border area. These regions, which bounds the randomly chosen trespassing paths, are generally in close vicinity. In this paper, we introduce the notion of trespassers’ favorite paths (TFP) and provide a tool that can be used to forecast the detection probability of a surveillance network in such a network with TFPs. The detection probability is reduced to the geometric line intersection problem using bijection and the boundary conditions of intruder trajectories for the border area and the favorite region are determined. The line intersection problem is solved using tools from the integral geometry and geometric probability. The effect of the favorable region on the detection quality under different conditions is calculated using probabilistic models. The accuracy of the proposed quality metric is validated by both analytical methods and simulation results. Furthermore, the importance of the intrusion model on the network performance is presented using realistic scenarios. It is shown that the existence of favorite paths has significant impact on the detection quality of the network. The proposed detection quality metric provides analytical tools suitable for both real life and simulation scenarios to the network designers to forecast and optimize the expected detection performance, and is computationally inexpensive compared to both simulation based and distributed quality measurements.

Surveillance of personal locations with an untrusted system causes privacy breach/threats to the individuals those who are monitored. At this point, we propose a quality-aware locality monitoring system for wireless sensor networks. In this system, we outline a couple of in-network location algorithms such as resource-aware and quality aware algorithms, aimed to provide high-end location monitoring services for system users with outstanding quality, while protecting personal location privacy. Two techniques are based on the well-established (K) anonymity privacy concept; i.e., a person is unique among (K) individuals, to enable trusted sensor nodes to provide the average location information of monitored objects of the system. Each compound location is a part of a surveyed area/ location (L) along with the number of surveyed objects residing in (L), where (L) contains at least (K) persons. The resource aware algorithm minimizes communication cost and computational cost, while the qu...

Surveillance of personal locations with an untrusted system causes privacy breach/threats to the
individuals those who are monitored. At this point, we propose a quality-aware locality monitoring system
for wireless sensor networks. In this system, we outline a couple of in-network location algorithms such as
resource-aware and quality aware algorithms, aimed to provide high-end location monitoring services for
system users with outstanding quality, while protecting personal location privacy. Two techniques are
based on the well-established (K) anonymity privacy concept; i.e., a person is unique among (K)
individuals, to enable trusted sensor nodes to provide the average location information of monitored
objects of the system. Each compound location is a part of a surveyed area/ location (L) along with the
number of surveyed objects residing in (L), where (L) contains at least (K) persons. The resource aware
algorithm minimizes communication cost and computational cost, while the quality aware algorithm
maximizes the correctness of the aggregate location by lowering their monitored regions. To use the
location information, to provide location monitoring service, we use a spatial histogram method, which
calculates the distribution of the monitored objects created on the collected aggregate location
information. Then, the calculated distribution provides location monitoring services by answering a series
of questions. The system is evaluated through virtual experiments. The results indicate that this system
provides an excellent location monitoring services while ensuring location privacy of the monitored
persons.

Model-driven data acquisition techniques aim at reducing the amount of data reported, and therefore the energy consumed, in wireless sensor networks (WSNs). At each node, a model predicts the sampled data; when the latter deviate from the current model, a new model is generated and sent to the data sink. However, experiences in real-world deployments have not been reported in the literature. Evaluation typically focuses solely on the quantity of data reports suppressed at source nodes: the interplay between data modeling and the underlying network protocols is not analyzed.

"One of the major challenges in the area of wireless sensor networks is simultaneously reducing energy consumption and increasing network lifetime. Efficient routing algorithms have received considerable attention in previous studies for achieving the required efficiency, but these methods do not pay close attention to coverage, which is one of the most important Quality of Service parameters in wireless sensor networks. Suitable route selection for transferring information received from the environment to the sink plays crucial role in the network lifetime. The proposed method tries to select an efficient route for transferring the information. This paper reviews efficient routing algorithms for preserving k-coverage in a sensor network and then proposes an effective technique for preserving k-coverage and the reliability of data with logical fault tolerance. It is assumed that the network nodes are aware of their residual energy and that of their neighbors. Sensors are first categorized into two groups, coverage and communicative nodes, and some are then re-categorized as clustering and dynamic nodes. Simulation results show that the proposed method provides greater efficiency energy consumption.
"

This paper addresses mobility control routing in wireless networks. Given a data flow request between a source-destination pair, the problem is to move nodes towards the best placement, such that the performance of the network is improved. Our purpose is to find the best nodes selection depending on the minimization of the maximum distance that nodes have to travel to reach their final position. We propose a routing protocol, the Routing Protocol based on Controlled Mobility (RPCM), where the chosen nodes’ path minimizes the total travelled distance to reach desirable position. Specifically, controlled mobility is intended as a new design dimension network allow to drive nodes to specific best position in order to achieve some common objectives. The main aim of this paper is to show by simulation the effectiveness of controlled mobility when it is used as a new design dimension in wireless networks. Extensive simulations are conducted to evaluate the proposed routing algorithm. Results show how our protocol outperforms a well-known routing protocol, the Ad hoc On Demand Distance Vector routing (AODV), in terms of throughput, average end-to-end data packet delay and energy spent to send a packet unit.

There are various challenges faced by HR departments while recruiting and selecting the candidates for a particular job/profile. However in current trends, diverse tools and technologies are used to overcome those challenges in the organizations. Several challenges faced in recruitment and selection aretime consumption, lack of recruitment sources and less applicants applying for the job. This research is carried out to know the diversity of challenges faced by different organizations of different sectors while conducting recruitment and selection and prime tools and technologies used to manage those challenges. This research mainly focuses on whether organizations situated in and around Ahmedabad face challenges in recruitment and selection and if they take help of technology to manage those challenges. The research also enlightens us about diversity of challenges faced in different sectors and to know about particular challenges that are faced most in recruitment and selection. In this research, Human Resource Department of Various Organizations were contacted in order to accumulate the insights regarding challenges faced in their respective organizations and structured questionnaire is used as a compiling tool.

Wireless Sensor Networks are considered an important part of the modern ICT solutions for greenhouse monitoring. Several communication technologies are already available and have been used both in pilot and commercial installations. Their attractiveness is based on their deployment flexibility and low cost. However, some special features of the greenhouses and their cultivations (variable microclimate conditions, greenhouse construction materials, size and composition of plants, spatiotemporally variable foliage) raise questions about the proper topology and network density in such an environment. In this paper, the findings of our experimentation regarding the use of ZigBee as the communication technology for a WSN deployed in a greenhouse complex with hydroponic cultivation of tomato crops are presented. Different topologies were investigated and the impact of the plants' foliage in the network nodes connectivity is assessed.

With the advent of Wireless Sensor Networks (WSN) and its immense popularity in a wide range of applications, security has been a major concern for these resource-constraint systems. Alongside security, WSNs are currently being integrated with existing technologies such as the Internet, satellite, Wi-Max, Wi-Fi, etc. in order to transmit data over long distances and handover network load to more powerful devices. With the focus currently being on the integration of WSNs with existing technologies, security becomes a major concern. The main security requirement for WSN-integrated networks is providing end-to-end security along with the implementation of in-processing techniques of data aggregation. This can be achieved with the implementation of Homomorphic encryption schemes which prove to be computationally inexpensive since they have considerable overheads. This paper addresses the ID-issue of the commonly used Castelluccia Mykletun Tsudik (CMT) [12] homomorphic scheme by proposing an ID slotting mechanism which carries information pertaining to the security keys responsible for the encryption of individual sensor data. The proposed scheme proves to be 93.5% lighter in terms of induced overheads and 11.86% more energy efficient along with providing efficient WSN scalability compared to the existing scheme. The paper provides analytical results comparing the proposed scheme with the existing scheme thus justifying that the modification to the existing scheme can prove highly efficient for resource-constrained WSNs.

In this work, we propose a mechanism in which power consumption in a sensor network can be reduced greatly by taking into account the fairness factors and to increase the probability of nodes for successful packet transmission with lowest possible Signal to Noise Ratio (SNR) in a crowded environment. In other words we propose a high throughput and spectrally efficient network. The power consumption of the
network reduces drastically when the clustered approach is adopted, which has been confirmed using the Friss transmission formula. Here, we have used analytical  expressions from renewal reward theorem to deduce network throughput, probability of collisions and back-off periods upon collision in a random multiple access environment. Using those expressions we have made an analysis on network throughput,
probability of collisions, bandwidth availability per node and estimation of back-off intervals upon collisions. The total number of nodes in the network is kept constant for  observational purposes. The number of clusters has been varied to take observation of network throughput, probability of collisions, bandwidth availability per node and estimation of back-off intervals upon collisions. The analytical results
obtained show that the power requirement of the network reduces drastically as the number of clusters increases.

The nature of military operations introduces additional requirements on sensor and ad-hoc networks such as reliability and operating in real-time. Although there has been many techniques providing reliability and real-time data communication in the literature, their implementations challenge with resource limitations peculiar to Wireless Sensor Networks (WSN). Real-time data demand and reliability challenge with the objective of minimization of energy consumption. Moreover, most of these techniques require topological information of the deployed network which introduces communications and processing overhead. In this paper, we present an energy-efficient and reliable data acquisition approach for time-critical and real-time traffic in WSN applications. Real-time data is carried over multiple paths to provide reliability in communications. The proposed approach provides the ability to route data without topology information. Moreover no complex computations are required. The performance evaluation shows that the proposed technique fulfils the requirements of tactical communications of instantly deployable sensor networks in a hostile environment. Although the proposed method is developed for instantly deployable sensor and ad hoc networks such as those deployed in emergency cases, in hostile environment and, in dangerous environments, it can also be applicable for preconfigured networks.

Model-driven data acquisition techniques aim at reducing the amount of data reported, and therefore the energy consumed, in wireless sensor networks (WSNs). At each node, a model predicts the sampled data; when the latter deviate from the current model, a new model is generated and sent to the data sink. However, experiences in real-world deployments have not been reported in the literature. Evaluation typically focuses solely on the quantity of data reports suppressed at source nodes: the interplay between data modeling and the underlying network protocols is not analyzed.

In contrast, this paper investigates in practice whether i) model-driven data acquisition works in a real application; ii) the energy savings it enables in theory are still worthwhile once the network stack is taken into account. We do so in the concrete setting of a WSN-based system for adaptive lighting in road tunnels. Our novel modeling technique, Derivative-Based Prediction (DBP), suppresses up to 99% of the data reports, while meeting the error tolerance of our application. DBP is considerably simpler than competing techniques, yet performs better in our real setting. Experiments in both an indoor testbed and an operational road tunnel show also that, once the network stack is taken into consideration, DBP triples the WSN lifetime—a remarkable result per se, but a far cry from the aforementioned 99% data suppression. This suggests that, to fully exploit the energy savings enabled by data modeling techniques, a coordinated operation of the data and network layers is necessary.

In wireless sensor networks (WSNs), there are many factors, such as the reciprocal interference of wireless links, battlefield applications and nodes are exposed to poor physical protection medium. All of these result in the sensor nodes being more exposed to be attacked and compromised. Since sensors are normally energy limited in WSNs, it is constantly basic to conserve the node energy and expand the lifetime of the network. Besides, hierarchical clustering is deemed as one of the numerous ways to deal with the reduction of energy consumption of nodes and increasing the network lifetime in WSNs. This paper conspicuously introduces an efficient and secure malicious node detection model based on a hybrid clustering network for WSNs (ESMCH) which is based on a trusted mobile node. WSNs are still suffering from some attacks like Man-in-the-Middle Attack and Black hole Attack, so by using the ESMCH model, we can avoid these attacks. Finally, simulation results also indicate that the proposed model can increase the network lifetime, and achieve an efficient and secure clustering network.

In this research work, the egg laying radius of cuckoo search algorithm is used to create a cluster and then search for the optimum node based on multiobjective genetic algorithm with pareto ranking, so that the data can be forwarded to the sink.The primary focus is onthe two performance metrics parameters,one is the maximization of network lifetime and other is the minimization of delay. For maximizing the network lifetime parameter, the overlapped target sensing by many sensors is wastage of energy by two or more sensors, where the same task can be done by one sensor. To overcome this problem, the sequence set cover methodology is used.For minimization of delay parameter, the sleep-wake scheduling mechanism will be considered, but substantial delays are introduced as transmitting node needs to wait for its next-hop relay node to wake up. These delays can be taken care by developing any cast based packet forwarding schemes where individual node forwards a packet to the first neighboring node that wakes up among multiple candidate nodes. This any cast forwarding schemes minimizes the expected packet-delivery delays from the sensor nodes to the sink node. The introduced work will perform energy proficient routing with an objective to improve the network life, packet loss ratio and overall network throughput. The proposed algorithm was simulated in MATLAB and compared with LEACH algorithm. The results show that our proposed algorithm issuperiorfor prolonging the network lifetime, minimizing the packet loss and increasing the throughput.

Ensuring connectivity in Wireless Sensor Networks (WSN) is a challenging issue, especially in hazardous areas (like battlefield). Many applications of WSN require an important level of connectivity in the network to detect a given event (like detection Intrusion) and forward it to the " sink " node in order to alert users. For these risky areas the deterministic deployment is not usually guaranteed and the network is composed by a set of disconnected Islands. We present in our work two strategies to relocate sensors in order to improve the connectivity using mobile Robots. These two solutions are called Multi-Robot Island-based Relocation (MRIBR) and Multi-Robot Grid-Based Island-based Relocation (MRGIR). Through several simulations, we show that MRGIR outperforms MRIBR. Our study can be used especially to make a trade-off between the number of deployed sensors and the numbers of the used mobile robots, according to the quality needed for the application.

In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance, congestion control are the important metrics that affect the performance of wireless sensor network. As many approaches were proposed to increase the performance of a wireless sensor network among them clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So there exists an option that nodes have to send the information that is already reached the base station by its own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high density of the nodes.

The future developments of the wireless sensor networks and its applications demands for the efficient and secure communication. For the solution of efficient and reliable security needs cryptography algorithms provides good solutions. For providing reliable security schemes mainly data confidentiality now-a-days key management is used. This paper provides a review over cryptography schemes being used to deal with security issues of wireless sensor networks.

In a typical wireless sensor network, the batteries of the nodes near the sink deplete quicker than other nodes due to the data traffic concentrating towards the sink, leaving it stranded and disrupting the sensor data reporting. To mitigate this problem, mobile sinks are proposed. They implicitly provide load-balanced data delivery and achieve uniform-energy consumption across the network. On the other hand, advertising the position of the mobile sink to the network introduces an overhead in terms of energy consumption and packet delays. In this paper, we propose Ring Routing, a novel, distributed, energy-efficient mobile sink routing protocol, suitable for time-sensitive applications, which aims to minimize this overhead while preserving the advantages of mobile sinks. Furthermore, we evaluate the performance of Ring Routing via extensive simulations.

The advancement of wireless sensor networks yields a variety of wireless sensor network for wildlife tracking. One typical application for wireless sensor networks is in animal tracking and monitoring in wildlife environments. A significant number of studies have been done in tracking animals with sensor networks. However from the recent literature it is observed that there is no much study has been done on an intelligent real time sensor network that is capable to alerting the rangers an incidence of animal poaching before it happened. In this paper an intelligent wireless sensor system for tracking and monitoring rhinos and elephants is proposed.

Low power and limited processing are characteristics of nodes in Wireless sensor networks. Therefore, optimal consumption of energy for WSN protocols seems essential. In a number of WSN applications, sensor nodes sense data periodically from environment and transfer it to the sink. Because of limitation in energy and selection of best route, for the purpose of increasing network remaining energy a node with most energy level will be used for transmission of data. The most part of energy in nodes is wasted on radio transmission; thus decreasing number of transferred packets in the network will result in increase in node and network lifetimes. In algorithms introduced for data transmission in such networks up to now, a single route is used for data transmissions that results in decrease in energy of nodes located on this route which in turn results in increasing of remaining energy. In this paper a new method is proposed for selection of data transmission route that is able to solve this problem. This method is based on learning automata that selects the route with regard to energy parameters and the distance to sink. In this method energy of network nodes finishes rather simultaneously preventing break down of network into two separate parts. This will result in increased lifetime. Simulation results show that this method has been very effective in increasing of remaining energy and it increases network lifetime.

This paper addresses the problem of selecting the most informative sensor locations out of all possible sensing positions in predicting spatial phenomena by using a wireless sensor network. The spatial field is modelled by Gaussian Markov random fields (GMRF), where sparsity of the precision matrix enables the network to benefit from computation. A new spatial sensor selection criterion is proposed based on mutual information between random variables at selected locations and those at unselected locations and interested but unlikely sensor placed positions, which enhances resulting prediction. The GMRF based optimality criterion is then proven to be computationally and efficiently resolved, especially in a large-scale sensor network, by a polynomial time approximation algorithm. More importantly , with demonstrations of monotonicity and submodularity properties of the mutual information set function in the proposed selection criterion, our near-optimal solution is also guaranteed by at least within (1 − 1/e) of the optimal performance. The effectiveness of the proposed approach is compared and illustrated using two real-life large data sets with promising results.

The paper addresses the problem of efficiently deploying sensors in spatial environments, e.g. smart buildings , for the purpose of monitoring environmental phenomena. By modelling the environmental fields using spatio-temporal Gaussian processes, a new and efficient optimality criterion of minimizing prediction uncertainties is proposed to find the best sensor locations. Though the environmental processes spatially and temporally vary, the proposed approach of choosing sensor positions is not affected by time variations, which significantly reduces computational complexity of the optimization problem. The sensor deployment problem is then solved by a practically and feasibly polynomial algorithm, where its solutions are guaranteed. The proposed approaches were implemented in a real tested space in a university building, where the obtained results are highly promising.

Prolonging the network lifetime is one of the main challenges in wireless sensor networks (WSNs). This paper proposes a layered-based routing tree called LBRT that solves the energy holes in WSNs. It uses several layers in a ring network in a way that each layer is composed of four sectors. The number of nodes in first layer is more than that of in other layers. The nodes construct a cluster at each sector, except sectors of first layer, to transmit the data packets via cluster head (CH) nodes. CH nodes are selected based on their remaining energy and average distance to neighboring nodes. They receive data packets from non-cluster head (NCH) nodes and forward them toward the sink through CH nodes located at the lower layer. Simulation results demonstrate that the proposed method surpasses than another routing method in terms of network lifetime, network traffic, system throughput, and delivery time.

A novel strategy is proposed to manage the sleep of the nodes in the network so that energy can be
conserved and network connectivity can be kept. The novelty of the strategy is its extreme simplicity. The
existing Gossip Based Sleep Protocol (GSP) is extended to achieve network reliability through
piggybacking. Piggybacking is a convenient and effective approach and has been successfully applied to
several areas of the networking. In the proposed work, we will develop a sleep management protocol and
network reliability for wireless sensor networks. Then the protocol will be extended to the synchronous
network, where nodes manage their own mode (sleep or awake mode) independently

Recent advances in integrated electronic devices motivated the use of Wireless Sensor Networks (WSNs) in many applications including target surveillance and tracking. A number of sensor nodes are scattered within a sensitive region to detect the presence of intruders and forward subsequent events to the analysis center(s). Obviously, the sensor deployment should guarantee an optimal event detection rate. This paper proposes a tracking framework based on Voronoi tessellations. Two mobility models are proposed to control the coverage degree according to target presence. The objective is to set a non-uniform coverage within the monitored zone to allow detecting the target(s) by multiple sensor nodes. We show how the proposed algorithm adapts to the situation where multiple targets move in the monitored zone. Moreover, we introduce an algorithm to discover redundant nodes (which do not provide additional information about target position). This algorithm is shown to be effective in reducing the energy consumption using an activity scheduling approach. Simulations are carried out to underline the efficiency of the proposed models.

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One of the important and challenging matters in
sensor network is energy of life span of nodes in the network.
Directed routing algorithm is one of propounded methods in
sensor networks which are a data-oriented algorithm. This
algorithm focuses on saving energy within life span of network
nodes. One of problems of directed diffusion method is
existence of multiple routes. Now, consider that some sinks
from the same origin request the same data who's Data
Volume is very much. Directed routing algorithm establishes
one route toward targeted route for each query. The problem
of this algorithm is multiplicity of routes for the same data.
Therefore, if we can establish a route which has the most
common feature with regards to nodes which forms the route,
we have prevented wasting energy.
In this paper, it is tried to remove problem of multiplicity of
routes for the same data by learning automata. We named this
algorithm RDDLA. RDDLA decrease overhead and energy in
the network Considerable against with some others methods.