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A wireless sensor network (WSN) collects and routes information from the environment to an aggregation point, known as a sink node. The sink node processes the information or acts as a gateway to forward information to another network. Due to its essential role in the network, the sink node is a high priority target for an attacker who wishes to disable a WSN. In this thesis, we focus on the mitigation of sink-node vulnerability in a WSN. Specifically, in this thesis we study the issue of protecting the sink node through anonymity techniques. In particular, we use a technique known as k-anonymity. To achieve k-anonymity, we use a specific routing protocol designed to work within the constraints of WSN communication protocols, specifically IEEE 802.15.4. We use and modify the Lightweight Ad hoc On-Demand – Next Generation (LOADng) reactive-routing protocol to achieve anonymity. This modified protocol prevents an attacker from identifying the sink node without adding significant complexity to the regular sensor nodes. We simulate the modified LOADng protocol using a custom-designed simulator in MATLAB. We demonstrate the effectiveness of our protocol and also show some of the performance tradeoffs that come with this method.

Data fusion in wireless sensor networks can improve the performance of a network by eliminating redundancy and power consumption, ensuring fault-tolerance between sensors, and managing e®ectively the available com- munication bandwidth between network components. This thesis considers a data fusion approach applied to wireless sensor networks based on fuzzy logic theory. In particular, a cluster-based hierarchical design in wire- less sensor networks is explored combined with two data fusion methods based on fuzzy logic theory. A data fusion algorithm is presented and tested using Mamdani and Tsukamoto fuzzy inference methods. In addition, a concept related to the appropriate queuing models is presented based on classical queuing theory. Results show that the Mamdani method gives better results than the Tsukamoto approach for the two implementations considered. We noted that the proposed algorithm requires low processing and computational power. As a result, it can be applied to WSNs to provide optimal data fusion and ensures maximum sensor lifetime and minimum time delay.

We consider the problem of decentralized detection where peripheral nodes make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center over a sum-rate constrained multiple access channel. The fusion center then makes a decision about the state of the phenomenon based on the aggregate received data. Using the Chernoff information as a performance metric, Chamberland and Veeravalli previously studied the structure of optimal rate allocation strategies for this scenario under the assumption of an unlimited number of sensors. Our key contribution is to extend these result to the case where there is a constraint on the maximum number of active sensors. In particular, we find sufficient conditions under which the uniform rate allocation is an optimal strategy, and then numerically verify that these conditions are satisfied for some relevant sensor design rules under a Gaussian observation model.

A distributed data collection algorithm to accurately store and forward information obtained by wireless sensor networks is proposed. The proposed algorithm does not depend on the sensor network topology, routing tables, or geographic locations of sensor nodes, but rather makes use of uniformly distributed storage nodes. Analytical and simulation results for this algorithm show that, with high probability, the data disseminated by the sensor nodes can be precisely collected by querying any small set of storage nodes.

Research on the Novel Multi-Data Fusion Methods in Wireless Sensor Networks

The transmission rate, delivery reliability and network lifetime are three fundamental but conflicting design objectives in energy-constrained wireless sensor networks. In this paper, we address the optimal rate-reliability-lifetime tradeoff with link capacity constraint, reliability constraint and energy constraint. By introducing the weight parameters, we combine the objectives at rate, reliability, and lifetime into a single objective to characterize the tradeoff among them. However, the optimization formulation of the rate-reliability-reliability tradeoff is neither separable nor convex. Through a series of transformations, a separable and convex problem is derived, and an efficient distributed Subgradient Dual Decomposition algorithm (SDD) is proposed. Numerical examples confirm its convergence. Also, numerical examples investigate the impact of weight parameters on the rate utility, reliability utility and network lifetime, which provide a guidance to properly set the value of weight parameters for a desired performance of WSNs according to the realistic application's requirements.

We develop a queueing model for analyzing resource replication strategies in wireless sensor networks. The model can be used to minimize either the total transmission rate of the network (an energy-centric approach) or to ensure the proportion of query failures does not exceed a predetermined threshold (a failure-centric approach). The model explicitly considers the limited availability of network resources, as well as the frequency of resource requests and query deadlines, to determine the optimal replication strategy for a network resource. While insufficient resource replication increases query failures and transmission rates, replication levels beyond the optimum result in only marginal decreases in the proportion of query failures at a cost of higher total energy expenditure and network traffic.

Sensor network are highly distributed networks of small light weighted wireless nodes deployed in large numbers to monitor the environment or system by the measurement of physical parameters such as temperature, pressure, light, vibration, humidity etc. Wireless sensor node consists of sensing, computing, actuation, communication and power component. An efficient method to extend sensor network lifetime by organizing the sensors into a maximal number of set cover thet are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collective data, while all other nodes are in low-energy sleep mode. By using different technique we increase the network lifetime.

In the past decades, Wireless Sensor Network WSN has become a wide area of research. In WSN, numerous sensor nodes are randomly setup with different energy level. Energy acts as power source and is available to each sensor node in limited quantity. The limiting factor is that sensor nodes are energy constrained and recharging or replacing battery is costly and complex process. This paper explores the different energy consumption factors which effect the lifetime and performance of the WSN's. The main factors which effect the energy consumption in WSN's are scalability, load balancing, reliability, communication, collision, over hearing, ideal listing and latency. Researchers have proved that the node near to sink node discharge very fastly. Apart from these, most of the energy is consumed during the transfer of data from sender to receiver. In this paper effort is made to analyze the effect of different factors on energy consumption in WSN's.  by Anupam Jain | Prof. Madhuvan Dixit "Analysis of Energy in Wireless Sensor Networks: An Assessment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019,  URL: https://www.ijtsrd.com/papers/ijtsrd22789.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-network/22789/analysis-of-energy-in-wireless-sensor-networks-an-assessment/anupam-jain

The Wireless Sensor Networks (WSN) is considered to be one of the most promising emerging technologies. However one of the main constraints which is holding back its wide range of applications is the battery life of the sensor node and thus effecting the network life. A new approach to this problem has been presented in this paper. The proposed method is suitable for event driven applications where the event occurrence is very rare. The system uses spread spectrum as a means of communication.

In Wireless Sensor Networks (WSNs), most of the existing key management schemes, establish shared keys for all pairs of neighbor sensor nodes without considering the communication between these nodes. When the number of sensor nodes in WSNs is increased then each sensor node is to be loaded with bulky amount of keys. In WSNs a sensor node may communicate with a small set of neighbor sensor nodes. Based on this fact, in this paper, an energy efficient Traffic-Aware Key Management (TKM) scheme is developed for WSNs, which only establishes shared keys for active sensors which participate in direct communication. The proposed scheme offers an efficient Re-keying mechanism to broadcast keys without the need for retransmission or acknowledgements. Numerical results show that proposed key management scheme achieves high connectivity. In the simulation experiments, the proposed key management scheme is applied for different routing protocols. The performance evaluation shows that proposed scheme gives stronger resilence, low energy consumption and lesser end to end delay.

Wireless sensor networks (WSNs) are the sensors that are dispersed in a different location that can sense the accumulated data in real-time and send it to the central location for the process of data aggregation. During the transfer of the information using the data nodes from the WSNs to the central location, there may be chances that the data node could be compromised by sensor failure or by an attack from a malicious user. To overcome this problem, we propose a two-phase secure data collection (TPSDC) technique for wireless sensor networks which provides confidentiality and integrity for the data nodes that are being sent to the central location and also during the data aggregation in the central location. Various existing methods have been proposed to secure the data when sent from the WSNs to the internet of things (IoT) devices but they lack to provide both confidentiality and integrity at the same time. Hence our model provides both integrity and confidentiality by providing security to the data nodes. Experimental results show that our model TPSDC performs better in terms of misclassification rate, detection rate, throughput, network lifetime analysis of the node, and communication overhead of the node when compared with the existing methods.

We consider a stochastic model of clock synchronization in a wireless network consisting of N sensors interacting with one dedicated accurate time server. For large N we find an estimate of the final time sychronization error for global and relative synchronization. Main results concern a behavior of the network on different time scales $t=t_N \to \infty$, $N \to \infty$. We discuss existence of phase transitions and find exact time scales on which an effective clock synchronization of the system takes place.

Wireless sensor networks (WSN), i.e. networks of autonomous, wireless sensing nodes spatially deployed over a geographical area, are often faced with acquisition of spatially sparse fields. In this paper, we present a novel bandwidth/energy efficient CS scheme for acquisition of spatially sparse fields in a WSN. The paper contribution is twofold. Firstly, we introduce a sparse, structured CS matrix and we analytically show that it allows accurate reconstruction of bidimensional spatially sparse signals, such as those occurring in several surveillance application. Secondly, we analytically evaluate the energy and bandwidth consumption of our CS scheme when it is applied to data acquisition in a WSN. Numerical results demonstrate that our CS scheme achieves significant energy and bandwidth savings wrt state-of-the-art approaches when employed for sensing a spatially sparse field by means of a WSN.

In wireless sensor networks (WSNs), the base station (BS) is a critical sensor node whose failure causes severe data losses. Deploying multiple fixed BSs improves the robustness, yet requires all BSs to be installed with large batteries and large energy-harvesting devices due to the high energy consumption of BSs. In this paper, we propose a scheme to coordinate the multiple deployed BSs such that the energy supplies required by individual BSs can be substantially reduced. In this scheme, only one BS is selected to be active at a time and the other BSs act as regular sensor nodes. We first present the basic architecture of our system, including how we keep the network running with only one active BS and how we manage the handover of the role of the active BS. Then, we propose an algorithm for adaptively selecting the active BS under the spatial and temporal variations of energy resources. This algorithm is simple to implement but is also asymptotically optimal under mild conditions. Finally, by running simulations and real experiments on an outdoor testbed, we verify that the proposed scheme is energy-efficient, has low communication overhead and reacts rapidly to network changes.

Wireless underground sensor networks (WUSNs) present a variety of new research challenges. Magnetic induction (MI) based transmission has been proposed to overcome the very harsh propagation conditions in underground communications in recent years. In this approach, induction coils are utilized as antennas in the sensor nodes. This solution achieves longer transmission ranges compared to the traditional electromagnetic (EM) waves based approach. Furthermore, a passive relaying technique has been proposed in the literature where additional resonant circuits are deployed between the nodes. However, this solution is shown to provide only a limited performance improvement under practical system design contraints. In this work, the potential of an active relay device is investigated which may improve the performance of the system by combining the benefits of the traditional wireless relaying and the MI based signal transmission.

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

In distributed target tracking for wireless sensor networks, agreement on the target state can be achieved by the construction and maintenance of a communication path, in order to exchange information regarding local likelihood functions. Such an approach lacks robustness to failures and is not easily applicable to ad-hoc networks. To address this, several methods have been proposed that allow agreement on the global likelihood through fully distributed belief consensus (BC) algorithms, operating on local likelihoods in distributed particle filtering (DPF). However, a unified comparison of the convergence speed and communication cost has not been performed. In this paper, we provide such a comparison and propose a novel BC algorithm based on belief propagation (BP). According to our study, DPF based on metropolis belief consensus (MBC) is the fastest in loopy graphs, while DPF based on BP consensus is the fastest in tree graphs. Moreover, we found that BC-based DPF methods have lower communication overhead than data flooding when the network is sufficiently sparse.

In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.

Pairwise key establishment is one of the fundamental security services in sensor networks which enables sensor nodes in a sensor network to communicate securely with each other using cryptographic techniques. It is not feasible to apply traditional public key management techniques in resource-constrained sensor nodes, and also because the sensor nodes are vulnerable to physical capture. In this paper, we introduce a new scheme called the identity based key pre-distribution using a pseudo random function (IBPRF), which has better trade-off between communication overhead, network connectivity and resilience against node capture compared to the other key pre-distribution schemes. Our scheme can be easily adapted in mobile sensor networks. This scheme supports the addition of new sensor nodes after the initial deployment and also works for any deployment topology. In addition, we propose an improved version of our scheme to support large sensor networks.

Sensor networks are rather challenging to deploy, program, and debug. Current programming languages for these platforms suffer from a significant semantic gap between their specifications and underlying implementations. This fact precludes the development of (type-)safe applications, which would potentially simplify the task of programming and debugging deployed networks. In this paper we define a core calculus for programming sensor networks and propose to use it as an assembly language for developing type-safe, high-level programming languages.

Wireless sensor networks (WSNs) have gained researchers' attention in the last several years. Small sensors powered by miniaturized microprocessors are capable of supporting several applications for civil and military domains. Determining the location of sensors is a basic and essential knowledge for most WSN algorithms and protocols including data tagging, routing, node identification, among others. This paper surveys the different algorithms that have been proposed to securely determine the location of a sensor node. By "secure", we mean that adversaries cannot easily affect the accuracy of the localized sensors. In other words, the localization algorithm must be robust under several attacks. We provide a taxonomy for classifying different secure localization schemes and describe possible attacks that can harm localization. In addition, we survey different secure localization schemes and show how they map to the proposed taxonomy. We also give a comparison between the different schemes, showing the attacks addressed by each.

Wireless sensor networks (WSN) have evolved a vibrant and lively research field. It comprises numerous wise and low-power consumption devices for gathering the contiguous atmosphere's data. However, the energy dissipation matter that distorts network lifetime remains the challenge since the sensor node battery is non-rechargeable and irreplaceable. Clustering and routing protocol has become the furthermost solutions and invariably minimizes depletion and prolongs the sensor node lifetime. Such protocols have adopted metaheuristic algorithms to secure the efficiency of the clustering and routing protocols. However, the cluster head's extensive task favors consuming and draining more energy. This study proposed a fine-tuning solution for the sensor node's population and generation sizes. It benefits from the modified problem-oriented genetic algorithm parameters in securing the sensor node lifetime. Besides, the solution works effectively to balance the load of the cluster head nodes. A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.

WIRELESS SENSOR

Wireless Sensor Networks are one of the enabling technologies to realize the next generation electrical power grid called “Smart Grid”. Smart Grid provides the facility to integrate the advancement of information and communication technology with sensor technology to make the grid really smart, robust and adaptive. In spite of all these advancement, it is the application protocol that makes the technology useful to the end user either human or machine. Hypertext Transfer Protocol (HTTP), the internet’s de’facto application protocol is not efficient for WSN based smart grid applications due to bandwidth and energy inefficiency. Constraint Application Protocol (CoAP) and Message Queue Telemetry Transport (MQTT) are two candidate application protocols that can be used for smart grid application. In this Paper, We compare these three protocols applicability for smart grid application

In wireless sensor networks (WSN), data fusion should be energy efficient. But, determining the optimal number of aggregators in an energy efficient manner is a challenging task. Moreover, the existing data fusion techniques mostly use the same path for transmitting aggregated data to the sink which reduces the nodes lifetime. In this paper, we propose a technique which combines energy efficiency and multiple path selection for data fusion in WSN. The network is partitioned into various clusters and the node with highest residual energy is selected as the cluster head. The sink computes multiple paths to each cluster head for data transmission. The distributed source coding and the lifting scheme wavelet transform are used for compressing the data at the CH. During each round of transmission, the path is changed in a round robin manner, to conserve the energy. This process is repeated for each cluster. From our simulation results we show that this data fusion technique has less energy consumption with increased packet delivery ratio, when compared with the existing schemes.

This article is from Sensors (Basel, Switzerland) , volume 11 . Abstract RFID (Radio frequency identification) and wireless sensor networks are backbone technologies for pervasive environments. In integration of RFID and WSN, RFID data uses WSN protocols for multi-hop communications. Energy is a critical issue in WSNs; however, RFID data contains a lot of duplication. These duplications can be eliminated at the base station, but unnecessary transmissions of duplicate data within the network still occurs, which consumes nodes’ energy and affects network lifetime. In this paper, we propose an in-network RFID data filtering scheme that efficiently eliminates the duplicate data. For this we use a clustering mechanism where cluster heads eliminate duplicate data and forward filtered data towards the base station. Simulation results prove that our approach saves considerable amounts of energy in terms of communication and computational cost, compared to existing filtering schemes.

This article is from Sensors (Basel, Switzerland) , volume 11 . Abstract Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

A trade-off between energy efficiency and optimized routing is massively recommended for transmission efficiency enhancement in wireless sensor networks (WSNs). Therefore, in this paper, graph-based energy optimized dynamic routing (GEODR) mechanism is introduced to set up a balance between energy consumption minimization and throughput enhancement using a dynamic and optimized routing mechanism in WSNs. A clustering scheme is employed based on graph theory, and cluster boundaries are formed using distance vectors. Cluster head (CH) selection is performed based on residual energy, the distance between CHs, and the mobility of the sink node. Each cluster is scattered with multiple tiny nodes, and event monitoring is performed. A model for graph-based dynamic routing to transmit data packets, cluster and cluster boundary formation, and optimization of routing problems is discussed. The performance efficiency of the proposed GEODR mechanism is determined by taking 100 sensor nodes, and 20 nodes are selected as CHs in a sensor network, and several other network parameters are also considered. A massive improvement in energy is observed by using sink node mobility. Experimental results are obtained using the proposed GEODR mechanism in terms of data packet transmission, alive nodes, dead nodes, and residual energy and compared against classical routing mechanisms such as low energy adaptive clustering hierarchy (LEACH) and stable election protocol (SEP).

In various areas of the communication system, work based on Wireless Sensor Network (WSN) is being used these days. It is observed that trust-based model for WSN as a controlled secure, confidential and robustness with a consistent communication troubleshoots a lot of problems in delivering. This makes a node in WSN, that is, ready to deal with and act on attacks caused by additional nodes in different communication networks. This is a highly challenging task due to the lack of a trust resource and the dynamics that this network institute brings. In this paper, we propose Trust Calculation Algorithm for communicating nodes in WSN. Trust calculation algorithm provide the trust-based routing table for every node. It serves as an important role in the communication process for nodes from clusters, nodes from nodes and clusters from clusters in WSN

Life sciences: general issues

With the impact of global climate change, natural disasters such as prolonged drought, earthquakes, and tsunamis, have constantly increased over recent decades, putting those living in these areas in great danger. A natural disaster warning system has been established as an indispensable need to minimize possible high risks that cause human casualties. Several current natural disaster warning systems focus on building wireless sensor networks for forecasting and monitoring disasters as well as natural phenomena. This paper aims to develop a comprehensive model that integrates data visualization operations to identify and simultaneously predict threat proceedings in natural disasters. This technique can handle big data based on sensing data from wireless sensor networks and shows overview graphs about disasters' variability, floods, and earthquakes, in the areas. Based on the results collected from data visualization techniques, the system can issue alerts about the interest of the region in real time. In addition, we propose some levels for the warning system in which the networks only focus on the area with essential data that must be warned. This can save energy consumption for other areas of safety. This work shows promising points of effectiveness.

With the impact of global climate change, natural disasters such as prolonged drought, earthquakes, and tsunamis, have constantly increased over recent decades, putting those living in these areas in great danger. A natural disaster warning system has been established as an indispensable need to minimize possible high risks that cause human casualties. Several current natural disaster warning systems focus on building wireless sensor networks for forecasting and monitoring disasters as well as natural phenomena. This paper aims to develop a comprehensive model that integrates data visualization operations to identify and simultaneously predict threat proceedings in natural disasters. This technique can handle big data based on sensing data from wireless sensor networks and shows overview graphs about disasters' variability, floods, and earthquakes, in the areas. Based on the results collected from data visualization techniques, the system can issue alerts about the interest of the region in real time. In addition, we propose some levels for the warning system in which the networks only focus on the area with essential data that must be warned. This can save energy consumption for other areas of safety. This work shows promising points of effectiveness.

With the development of wireless communication, industrial wireless sensor networks (IWSNs) plays an important role in monitoring and control systems. In this paper, we extend the application of IWSNs into High Frequency Surface-Wave Radar (HFSWR) system. The traditional antenna is replaced by mobile IWSNs. In combination of the application precondition of super-directivity in HF band and circular topology of IWSNs, a super-directivity synthesis method is presented for designing super-directivity array. In this method, the dominance of external noise is ensured by constraining the Ratio of External to Internal Noise (REIN) of the array, and the desired side lobe level is achieved by implementing linear constraint. By using this method, the highest directivity will be achieved in certain conditions. Using the designed super directive circular array as sub-arrays, the compact receive antenna array is constructed, the purpose of miniaturization is achieved. Simulation verifies that the proposed method is correct and effective, the validity of the proposed method has been proved.

It has been shown that cooperative localization is capable of improving both the positioning accuracy and coverage in scenarios where the global positioning system (GPS) has a poor performance. However, due to its potentially excessive computational complexity, at the time of writing the application of cooperative localization remains limited in practice. In this paper, we address the efficient cooperative positioning problem in wireless sensor networks. A space-time hierarchical-graph based scheme exhibiting fast convergence is proposed for localizing the agent nodes. In contrast to conventional methods, agent nodes are divided into different layers with the aid of the space-time hierarchical-model and their positions are estimated gradually. In particular, an information propagation rule is conceived upon considering the quality of positional information. According to the rule, the information always propagates from the upper layers to a certain lower layer and the message passing process is further optimized at each layer. Hence, the potential error propagation can be mitigated. Additionally, both position estimation and position broadcasting are carried out by the sensor nodes. Furthermore, a sensor activation mechanism is conceived, which is capable of significantly reducing both the energy consumption and the network traffic overhead incurred by the localization process. The analytical and numerical results provided demonstrate the superiority of our space-time hierarchical-graph based cooperative localization scheme over the benchmarking schemes considered.

In this poster paper we present a data dissemination transmission abstraction for over the air programming (OAP) protocol which is fundamentally different from the previous hop by hop transmission protocols. Instead of imposing the greedy requirement that at least one node in the ith hop receives all packets before transmitting packets to the next hop and its neighbours, we take advantage of the spatial diversity and broadcast nature of wireless transmission to adopt a cooperative approach in which node broadcast whatever packets it has received with the expectation that it will recover the lost packets with high probability by overhearing the broadcast transmissions of its neighbours. The use of coded transmissions ensures that this does not lead to the broadcast storm problem. We validate the improved performance our of proposed transmission scheme with respect to the previous state of the art OAP protocols on a proof-of-concept two-hops TelosB wireless sensor network testbed.

In this paper we present an application of techniques from statistical signal processing to the problem of event detection in wireless sensor networks used for environmental monitoring. The proposed approach uses the well-established Principal Component Analysis (PCA) technique to build a compact model of the observed phenomena that is able to capture daily and seasonal trends in the collected measurements. We then use the divergence between actual measurements and model predictions to detect the existence of discrete events within the collected data streams. Our preliminary results show that this event detection mechanism is sensitive enough to detect the onset of rain events using the temperature modality of a wireless sensor network.

Wireless sensor detection is readily accessible, easily deployable, and usable technology that provides public-safety personnel with an early-warning and identification tool in the event of a Chemical Biological Radiological Nuclear (CBRN) incident. This is accomplished by incorporating wireless sensor detection capability into the Los Angeles Fire Departments (LAFD) hazardous-materials operations. Due to the relative ease of use and low cost of deployment, it makes sense that the LAFD employ wireless technology, capitalizing on the advantages. The question regarding CBRN wireless sensor network capability is whether this technology is suitable, reliable, user friendly, and quickly deployable. Furthermore, will this technology provide critical early warning, detection, and subsequent notification in real time The goal of this thesis is to determine CBRN wireless sensor detection capability in terms of reliability, deployment, early warning, and notification. The objective is to outline a concept of operations document providing the need structure for incorporating wireless sensor detection capability into public-safety operations. Through field deployments and exercises using sensor detectors, standardized equipment, and software, the LAFD will have better access to early detection and notification of CBRN material releases. The end result means a more efficient, cost-effective tool that readily detects hazardous products, providing an early warning capability.

Wireless sensor network research is being performed to address medical applications. In particular, a common vision found in the research arena is to provide sensing and wireless communication for assisted living facilities to improve lifestyle, to improve health care, and to support long term medical studies. Our research work is solving WSN problems for real-time response, data association, reliability and dependability, security and privacy, and analysis via programs that determine circadian rhythms. The work is taking an end-to-end view from collecting the data (via dust-like motes) to its analysis and use by doctors. As part of this research we are building (and have partly constructed) a WSN-based medical testbed. The medical testbed focuses on continuous, automatic monitoring of physiological, environmental and activity data for residents in independent and assisted-living facilities. It employs a Wireless Sensor Network (WSN) which is an enabling technology for medical applications in this type of environment. For example, the WSN could detect epileptic seizures or strokes and provide smart homecare by collecting biometric and environmental data for analysis. If an event is detected, it may also provide real-time assistance by notifying emergency healthcare providers and family members. Our proposed WSN system will integrate heterogeneous devices as sensors, actuators and a body network. Some body network systems will be wearable on the patient and some will be placed inside the living space. Also, the multi-hop backbone of the new testbed will connect other traditional systems, such as PDAs, PCs, and databases. The databases will be used for long-term archiving and data mining. We will also be able to connect to large clusters for backend processing, e.g., to execute time consuming circadian rhythm programs. This talk will describe our research problems, research ideas and the dust to doctor system being developed. It will also describe various collaborations that we have with the UVA medical school, with a medical security project at UVA, and Harvard. ©2005 Microsoft Corporation. All rights reserved.

Forward-deployed maneuver sustainment operations, such as Forward Arming and Refueling Points (FARPs), are a critical center of gravity that adversaries seek to disrupt or destroy in order to jeopardize friendly scheme of maneuver and operations. With adversaries’ increased ability to attack such operating bases through indirect fire and infiltration, it becomes more difficult for perimeter defense assets to maintain situational awareness in order to respond to threats. A low-cost wireless sensor network composed of Raspberry Pi nodes equipped with short-range radars, cameras, and motion sensors was built to give force protection personnel early warning and to help them maintain situational awareness. While each layer alone had flaws, deployment of the wireless network of sensor nodes using the defense in depth principle proved capable of not only providing early warning to defenders, but also giving defenders detailed imagery and kinetic information on the intruder.

The rapid development of medical sensors has increased the interest in Wireless Body Area Network (WBAN) applications where physiological data from the human body and its environment is gathered, monitored, and analyzed to take the proper measures. In WBANs, it is essential to design MAC protocols that ensure adequate Quality of Service (QoS) such as low delay and high scalability. This paper investigates Medium Access Control (MAC) protocols used in WBAN, and compares their performance in a high traffic environment. Such scenario can be induced in case of emergency for example, where physiological data collected from all sensors on human body should be sent simultaneously to take appropriate action. This study can also be extended to cover collaborative WBAN systems where information from different bodies is sent simultaneously leading to high traffic. OPNET simulations are performed to compare the delay and scalability performance of the different MAC protocols under the same experimental conditions and to draw conclusions about the best protocol to be used in a high traffic environment.

This paper proposes a Traffic-Differentiated Two-Hop Routing protocol for Quality of Service (QoS) in Wireless Sensor Networks (WSNs). It targets WSN applications having different types of data traffic with several priorities. The protocol achieves to increase Packet Reception Ratio (PRR) and reduce end-to-end delay while considering multi-queue priority policy, two-hop neighborhood information, link reliability and power efficiency. The protocol is modular and utilizes effective methods for estimating the link metrics. Numerical results show that the proposed protocol is a feasible solution to addresses QoS service differenti- ation for traffic with different priorities.

In this work, M-LEACH (Modified Distributed Energy Efficient Clustering) protocol, a new variant of LEACH is proposed after survey of LEACH. The proposed M-LEACH is designed for three different segregations for the nodes to elongate the stability & lifetime of the network. Hence, it increases the heterogeneity & energy level of the network. In LEACH, amplification energy is set same for all kinds of transmissions. Using low energy level for intra cluster transmissions with respect to cluster head to BS transmission leads in saving much amount of energy. Moreover, multi power levels also reduce the packet drop ratio, collisions and or interference for other signals. The proposed M-LEACH outperforms to existing classical LEACH. Aditi Beohar | Prof. Pankaj Sahu | Prof. Rajender Singh Yadav"Efficient Cluster Head Replacement LEACH Protocol for Wireless Sensor Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18332.pdf http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18332/efficient-cluster-head-replacement-leach-protocol-for-wireless-sensor-networks/aditi-beohar

Advanced Communication for Wireless Sensor Networks was proposed to focus on the development of innovative technologies for networked sensing, information processing, and control. This focus was in support of the Army Research Laboratorys (ARL) research and development program in advanced communications for mobile networks. More specifically the primary objective was to develop and demonstrate key sensor-network capabilities, lower-power electronic technology, and flexible, highly reliable communication systems to support small unit military operations.

Data fusion in wireless sensor networks can improve the performance of a network by eliminating redundancy and power consumption, ensuring fault-tolerance between sensors, and managing effectively the available communication bandwidth between network components. This thesis considers a data fusion approach applied to wireless sensor networks based on fuzzy logic theory. In particular, a cluster-based hierarchical design in wire- less sensor networks is explored combined with two data fusion methods based on fuzzy logic theory. A data fusion algorithm is presented and tested using Mamdani and Tsukamoto fuzzy inference methods. In addition, a concept related to the appropriate queuing models is presented based on classical queuing theory. Results show that the Mamdani method gives better results than the Tsukamoto approach for the two implementations considered. We noted that the proposed algorithm requires low processing and computational power. As a result, it can be applied to WSNs to provide optimal data fusion and ensures maximum sensor lifetime and minimum time delay.

The ability to securely disseminate data in a timely manner is critical to military missions within a hostile environment. Tactical wireless sensor networks (WSN) consist of power-constrained devices spread throughout a region-of-interest to provide data extraction in real time. In this thesis, we develop cyber security mechanisms to be implemented on a tactical WSN using the 6LoWPAN protocol for use by the United States Marine Corps (USMC). Specifically, we develop an architectural framework for tactical WSNs by studying cyber security gaps and vulnerabilities within the 6LoWPAN security sublayer, which is based on the IEEE 802.15.4 standard. We develop a key management scheme and a centralized routing mechanism that is non-broadcast but feasible in an operational scenario. In addition, we modify the6LoWPAN enabled IEEE 802.15.4 frame structure to facilitate the newly developed keying and centralized routing mechanisms. Methods to aid in deployment planning are also discussed. The tactical WSN architecture was tested against a variety of well-known network attacks. The attacks simulated were spoofing, man-in-the-middle, and denial-of-service. Through MATLAB simulations, we showed the effectiveness and efficiency of the developed cyber security mechanisms to provide integrity and reliability to a deployed tactical WSN.

In wireless sensor networks, the majority of data transmitted by sensor nodes is repeated over and over, and performing processes on them in many cases leads to increased power consumption and reduced network lifetime. Data aggregation is one of the techniques in reducing redundancy and improving energy efficiency; it also increases the lifespan of wireless sensor networks. In this paper, we address the issues of constructing the data aggregation tree that minimizes the total energy cost of data transmissions for two types of networks: without relay nodes and using relay nodes. Traditionally, evolutionary algorithms focus on constructing data aggregation trees for either without relay node networks or using relay nodes networks. Therefore, we show a new approach utilizing a multifactorial evolutionary algorithm, called Potential individuals based Multi-factorial Evolutionary Algorithm (P-MFEA), to solve both issues simultaneously. The proposed scheme shows improved performance in terms of energy consumption.

New advance and integrated technologies have changed the traditional systems and convert these systems into more intelligent, feasible and cost effective systems. In all data communications domain, data gathering is one of the significant task performed by using any techniques, tools and devices. Wireless sensor networks (WSN) also gained popularity in various fields where the sensor node sensed the information by using sink or gateway nodes and further send to central units for decision making. With passage of time, these networks have faced complexities where most of the existing techniques have suffered with load balancing, complex processes, overhead and energy consumption issues. Firstly, this paper provides detail comparison of existing data gathering techniques adopted for WSN and then provides their performance analysis. After comparison, this paper proposes a novel data gathering techniques called a sink based data gathering techniques (ASDG) to collect the data from the sensor nodes and further send for decision making. Experimental results show that proposed techniques is better than existing techniques and provide more efficient data delivery ratio with more network lifetime. The results also indicated that when using the proposed technique, the no of dead sensor nodes are less as compared to the existing ones at different rounds.

New advance and integrated technologies have changed the traditional systems and convert these systems into more intelligent, feasible and cost effective systems. In all data communications domain, data gathering is one of the significant task performed by using any techniques, tools and devices. Wireless sensor networks (WSN) also gained popularity in various fields where the sensor node sensed the information by using sink or gateway nodes and further send to central units for decision making. With passage of time, these networks have faced complexities where most of the existing techniques have suffered with load balancing, complex processes, overhead and energy consumption issues. Firstly, this paper provides detail comparison of existing data gathering techniques adopted for WSN and then provides their performance analysis. After comparison, this paper proposes a novel data gathering techniques called a sink based data gathering techniques (ASDG) to collect the data from the sensor nodes and further send for decision making. Experimental results show that proposed techniques is better than existing techniques and provide more efficient data delivery ratio with more network lifetime. The results also indicated that when using the proposed technique, the no of dead sensor nodes are less as compared to the existing ones at different rounds.

Location information is of paramount importance for Wireless Sensor Networks (WSN). The accuracy of collected data can significantly be affected by an imprecise positioning of the event of interest. Despite the importance of location information, real system implementations, that do not use specialized hardware for localization purposes, have not been successful. In this paper, we propose a location estimation scheme that uses a probabilistic approach for estimating the location of a node in a sensor network. Our localization scheme makes use of additional knowledge of topology deployment. We assume a sensor network is deployed in a controlled manner, where the goal of the deployment is to form a grid topology. We evaluate our localization scheme through simulations, showing localization errors as low as 3% of radio range. We outperform similar localization schemes by obtaining 50% less error in localization, when compared to them. We also evaluate our localization solution and the DV-Hop scheme in a real implementation, obtaining an average error in location of 79% of radio range, outperforming DV-Hop by approximately 40%. We analyze the significant differences in performance between simulations and a real implementation and stress the importance of further evaluations of real implementations. The result is an effective and realistic protocol that works in an actual implementation, under certain assumptions, because it exploits deployment information.