Observing individual locations with a capable untrusted server impose secrecy threats to the monitored individuals. In this paper we propose “A NovelSolitudeConservingLocationMonitoringapproach for WirelessSensornetworks”. We design two approaches to study nondescript locations in-network approaches, namely quality-aware and resource-aware approaches, that aims to enable the system to give high end quality locationmonitoring services for end users, while conserving personal location privacy. Both approaches are worked based on k-anonymity solitude (i.e.,an object is indistinguishable among k objects), to enable highly trusted sensor nodes to provide the collective location data of monitored objects for our system. Each collective location is in a form of a observed area X along with the number of monitored objects reside in X. The resource-aware approach objective to optimize the computational and communication value, while quality-aware approach aims to increase the reliability of the collective location data by reducing their observing areas. We use spatial histogram methodology to estimates the distribution of observing objects based on the gathered collective location data. We evaluated these two approaches through simulated experiments. The simulation results shows that these approaches gives high quality location observing services for end users and assure the location secrecy of the monitored objects.
Vertex covering has important applications for wirelesssensornetworks such as monitoring link failures, facility location, clustering, and data aggregation. In this study, we designed three algorithms for constructing vertex cover in wirelesssensornetworks. The first algorithm, which is an adaption of the Parnas & Ron’s algorithm, is a greedy approach that finds a vertex cover by using the degrees of the nodes. The second algorithm finds a vertex cover from graph matching where Hoepman’s weighted matching algorithm is used. The third algorithm firstly forms a breadth-first search tree and then constructs a vertex cover by selecting nodes with predefined levels from breadth-first tree. We show the operation of the designed algorithms, analyze them, and provide the simulation results in the TOSSIM environment. Finally we have implemented, compared and assessed all these approaches. The transmitted message count of the first algorithm is smallest among other algorithms where the third algorithm has turned out to be presenting the best results in vertex cover approximation ratio.
Wirelesssensornetworks have become a hot research area due to their numerous applications in monitoring inaccessible areas, which are difficult to be monitored by conventional methods. A large number of wirelesssensor network based applications are location dependent, where the sensed data is meaningless without accurate location of its origin. Some of these applications require highly accurate location information of sensor nodes. However, in many applications, knowledge of coarse accuracy of sensor node localization is sufficient. In such applications, range-free localization techniques are being used as low cost alternative to the range based localization techniques. All nodes in a sensor network cannot be made location aware, as it may escalate the cost of sensor network deployment. Therefore, to reduce the cost, very few location aware nodes, known as anchor nodes are deployed in the sensor network, all other nodes need to determine their location with the help of anchor nodes. Therefore, localization in wirelesssensor network is to determine the geographical position of sensor nodes, based on the known position of anchor nodes. In this paper, range-free centroid schemes, based on fuzzy logic inference approach have been proposed. The proposed schemes have been compared with existing range- free centroid based localization schemes through extensive simulations. A new cooperative localization technique based on fuzzy logic inference approach has also been proposed, which require deployment of very less number of anchor nodes in sensing field as compared to the conventional techniques; yet it provides required accuracy in localization of sensor nodes. The cooperative scheme requires very small number of location aware anchor nodes to be deployed, which reduces the cost of sensor network deployment. The simulation results demonstrate that through proposed cooperative localization technique, the desired accuracy in localization can be achieved even by use of few number of anchor nodes.
The increasing complexity of WirelessSensorNetworks (WSNs) is leading towards the deployment of complex networked systems and the optimal design of WSNs can be a very difficult task because several constraints and requirements must be considered, among all the power consumption. This paper proposes a novel fuzzy logic based mechanism that according to the battery level and to the ratio of Throughput to Workload determines the sleeping time of sensor devices in a WirelessSensor Network for environmental monitoring based on the IEEE 802.15.4 protocol. The main aim here is to find an effective solution that achieves the target while avoiding complex and computationally expensive solutions, which would not be appropriate for the problem at hand and would impair the practical applicability of the approach in real scenarios. The results of several real test-bed scenarios show that the proposed system outperforms other solutions, significantly reducing the whole power consumption while maintaining good performance in terms of the ratio of throughput to workload. An implementation on off-the-shelf devices proves that the proposed controller does not require powerful hardware and can be easily implemented on a low-cost device, thus paving the way for extensive usage in practice.
We presented a privacy-preserving locationmonitoring (PPLM) system, implemented for wirelesssensornetworks without disturbing the privacy of the individual persons or objects. The two in-network location anonymization algorithms, namely, resource- and qualityaware algorithms are implemented one after other for improved secured privacy. The resource-aware algorithm aims to minimize communication and computational cost, while the quality- aware algorithm aims to minimize the size of cloaked areas in order to generate more accurate aggregate locations. A spatial histogram approach is used to provide locationmonitoring services through answering the range queries. The system is evaluated through simulated experiments. The experimental results proved that the presented system provides a high quality locationmonitoring services while preserving the monitored object's location privacy. In this paper, the performance of PPLM system is evaluated in terms of generated aggregate locations, computational efficiency and cloaked area size. As part of the future enhancement of presented work on wirelesssensornetworks, the same process of monitoring can be implemented by using mobile devices which is provided with server activation feature.
College of Engineering. He received his Masters degree in Computer Science and Automation from Indian Institute of Science Bangalore. He was awarded Ph.D. in Economics from Bangalore University and Ph.D. in Computer Science from Indian Institute of Technology, Madras. He has a distinguished academic career and has degrees in Electronics, Economics, Law, Business Finance, Public Relations, Communications, Industrial Relations, Computer Science and Journalism. He has authored 31 books on Computer Science and Economics, which include Petrodollar and the World Economy, C Aptitude, Mastering C, Microprocessor Programming, Mastering C++ and Digital Circuits and Systems etc.. During his three decades of service at UVCE he has over 250 research papers to his credit. His research interests include Computer Networks, WirelessSensorNetworks, Parallel and Distributed Systems, Digital Signal Processing and Data Mining.
A WSN is built of sensor nodes, from a few to a large number of these small devices. The sensor nodes, generally spatially distributed trough a large area, are used to monitor different conditions such as temperature, sound, humidity or pressure, depending on their applications. They can be used to just sense the data or also to actuate somehow. The development of WSNs was motivated by military applications such as battlefield surveillance. This motivation is correlated with the fact that, in general, this type of network does not need infrastructures as the common applications use a sink node that collects all the data sensed by the sensors and it is that node which computes and performs the needed actions. The set up time and the implementation cost are also big advantages of using these networks .
Abstract— Mobile applications execute in an environment characterized by scarce and dynamically varying resources. We believe that applications have to adapt dynamically and transparently to the amount of resources available at runtime. To achieve this goal, we use the conventional extension of the client server model to a client-proxy-server model. The mobile devices execute the client, which provides the user interface and some part of the application logic. The proxy is a component of the application that executes in the wired network to support the client. As the user moves, the proxy may also move to remain on the communication path from the mobile device to a fixed correspondent host. Logically, the proxy hides the “mobile” client from the server, who thinks it communicates with a standard client (i.e., a client that executes on a powerful desktop directly connected to the wired network). Wirelesssensornetworks (WSNs) provide various environment data in the real-world, and also WSNs´s middleware is able to offer field data in real-time by user queries. WSNs also play an important role in ubiquitous computing with RFID technologies currently, and have evolved from many studies and being advanced to the future. In this paper, we propose a service-oriented sensor ontology which enables services based on service-oriented properties for materialization of the future ubiquitous computing. In contrast to legacy approaches, this paper defines the new service classes (Services, Location and Physical), as well as their properties and constraints that enable the service-oriented service based on service properties. We also have regard to reuse of ontology, service classes were designed to link with legacy OntoSensor ontology.
Wirelesssensornetworks consists of thousands of tiny, low cost, low power and multifunctional sensor nodes where each sensor node has very low battery life. Purpose is to conserve the transmitted energy from various sensor nodes. Various energy efficient algorithms have been designed for this. LEACH uses distributed cluster formation & randomized rotation of the cluster head to minimize the network energy consumption. Our paper is proposing an algorithm which is the enhancement of existing IB-LEACH. It reduces the energy consumption by using energy bank. This energy bank stores the energy after each round in both routing and clustering phase which overall increases the life time of the network. In this approach, ACTIVE_ROUTE_TIMEOUT is also enhanced by shamming the static parameters of HELLO_INTERVAL, RREQ_RETRIES and NET_DIAMETER. Results are compared through MATLAB and provide better approach than previous ones.
Recently, it emerged an eminent need for using WirelessSensorNetworks (WSN) in scenarios dealing with mobility. A typical scenario could be robots moving through a factory while communicating with other robots and also with ﬁxed nodes to perform collaborative work. However, deploying mobile-WSN bring several challenges . For instance, the communication protocols should attempt to topology changes due to mobility, as it brings uncertainty about the connectivity between neighbors nodes. Indeed, the awareness of the remaining connectivity time is a key information for designing more reliable network protocols.
The large-scale aquatic applications demand us to build large-scale Underwater Ad hoc Networks (UANET) and Underwater SensorNetworks (UWSN) to explore the uninhabited oceans. The difference between UANET and UWSN is due to controlled mobility and associated implementation cost. In a UANET, mobile nodes can be implemented by Autonomous Underwater Vehicles (AUV) or Remotely Operated Vehicles (ROV), which are high cost robots that can move under the water by following pre-programmed or autonomous motion patterns. However, the implementation costs of such self-propelling nodes are much higher than the one of any non- powered node. In the near future, it is envisioned that these high-cost unmanned mobile robots will play important roles in underwater explorations, for example in aquatic military campaigns.
Wirelesssensor network (WSN) consists in utilizing homo- geneous or heterogeneous sensor nodes, capable of communi- cating wirelessly in order to forward packets to a centralized base station . A sensor nodes can be either static or dynamic dependently on the application in use . In fact, the type of application defines as well the rhythm of data collection which can be performed periodically or upon occurrence of an event. A set of biosensors deployed or implanted in the human body constitutes a subtype of WSN named Wireless Body Area Networks (WBANs) also known as Wireless Body SensorNetworks (WBSNs).The main purpose of this type of network is to measure physiological parameters and for- ward it to the local base station (PDA), which handles the retransmission of data packets to medical centers for analysis and treatment. WBAN has many constraints inherited from Adhoc networks such as: limited energy resource, reduced memory size, small transmission power etc. The biosensor is low-powered devices with miniaturized size that are able to detect medical signal such as: electroencephalography (EEG), electrocardiogram (ECG), blood pressure, insulin etc...(See Fig.1).There exist a various types of monitoring systems being currently used in medical applications. Most of them are based on wired connection which restricts the mobility of the patient . To this end, WBAN requires wirelesssensor devices communicating wirelessly to a control unit followed with a remote healthcare centers for diagnostic purposes . The remainder of this paper is organized as follows: In Section 2, we presented the IEEE 802.15.6 standard. Our proposed intrusion detection schema for 802.15.6 standard was presented in Section 3. The simulation results are depicted and analyzed
Traditionally, healthcare monitoring is performed on a periodic check basis where patients are constantly updated on their symptoms; the physician checks and makes a”diagnosis, then when possible monitors the patient’s progress during treatment. In most cases, health monitoring is done by wireless network infrastructures. But the coverage of these network infrastructures has limitations from bandwidth. These limitations in continued health surveillance services, it is not always possible to send emergency signals from patients to healthcare workers. With WSN, patients can get continuous health monitoring using wireless ad hoc networks which can transmit vital signs over shorts distances. In most systems, the health data of multiple patients may be resent using the wireless multi-jump routing scheme for a base station. 
In fig 7 we added the new layer in the wirelesssensor architecture. The sensor network transfer the information to the base station the based station is directly connected to the user or the middleware and in the pervious architecture no security layer is present so there is always a demand of security layer in the wirelesssensor network. So in this paper we presented a Kerberos authentication scheme to protect the wirelesssensor network for the unauthorized user. By adding the security layer in the wirelesssensor network we can prevent the network from the different security thread. The base station can’t be accessed directly because the user has to authentication him/her from the Kerberos server and then obtain the ticker to access the base station to retrieve the in the information provided by the sensors.
In this section the use of aggregation and scheduling in a M2M application context, where the source and sink of notifications are both internal WSN networks (not edge routers), is analysed. The subject being asked, and client node requesting it, are randomly generated using an uniform distribution. Subjects are requested only once while the client node is chosen from the set of nodes not having the generated subject in its namespace or cache. The benefits of using aggregation/scheduling, when compared with a non aggre- gation/scheduling scenario, are also plotted considering the optimal values obtained by the CPLEX optimizer. Figures 5.11 and 5.12 relate to energy con- sumptions, for the two topologies, while Figures from 5.13 and 5.14 show the average loads per node, also for both topologies, which will influence delay.
omposed of n nodes, with a
ation range of r , and distributed in a two-dimensional squared sensor eld Q = [0, s] × [0, s] . For the sake of simpli
on- sider symmetri
ation links, i.e., for any two nodes u and v , u rea
hes v if and only if v rea
hes u and with the same signal strength. In this work we also
onsider homogeneous WSNs, i.e., networks in whi
h all of the nodes have the same hardware spe
With the above characteristics in mind, WSNs can be developed in many application do- mains.For example, in the agriculture business, WSNs can be used to monitor the humidity of the land near the plantations so it can trigger irrigation systems. For home/office environments, they can be used to monitor the temperature of the rooms and communicate with the air con- ditioning system. It is also possible to detect fires or floods, or even to prevent unauthorized physical access to some areas through wireless security systems. In cars, a WSN may be de- vised as a Vehicular AdHoc Network to monitor the pressure of the tyres or even in a dense monitoring environment of engine and chassis parameters. In a military scenario, WSNs can be stealthily dropped from airplanes in enemy territory to monitor,detect and track movement of soldiers or vehicles. On home land, WSNs may be deployed in forests to monitor temperature
In order to find the position of sensor node, minimum of three RN are needed. The distance between these RN are used to calculate the exact position of unknown node. In our proposed technique, distance estimation between the OrN and RN will be found by TOA method. For TOA-based systems, the one-way propagation time is measured, and the distance between measuring unit and signal transmitter is calculated. This algorithm estimates the distance between nodes by measuring the propagation time of a signal. So it requires precise time synchronization between two nodes. In this case the distance between two nodes is directly proportional to the time the signal takes to propagate from one point to another. If signal is sent at time t1 and reached the receiver node at time t2, the distance between two nodes can be defined as in equation (1). Where Sr is the propagation speed of acoustic signal (1500 m/s). From this method we get the list of all possible RN’s in the communication range.
This complex network strategy is important in WSNs be- cause a high cluster coefficient avoids the data delivery delay and unnecessary energy consumption by concentrating the data sensing in a given hub node. Interferences and link layer pro- cessing are avoided when different communication frequencies are used between hubs. The low average shortest path length avoids, mainly, the data delivery delay but on the other hand more local energy is consumed. This discussion shows the truthfulness of the Main hypothesis presented in Section II. Finally, features of more specific complex networks, e.g. small world or scale free networks, can be easily incorporated in the design of WSNs.
The fourth part of this research work, which was described in chapter 5 and 6, included the proposal of a new method to optimize the real-time query processing on WSNs for both latency and energy minimization and a new proposal of real-time query processing optimization for cloud-based wireless body area Networks (WBANs). The second main contribution of this thesis was accomplished by presented a new real-time query processing optimization for WSNs. According to the previous research work, the distributed approach allows performing in-network query processing that diminishes the data communication activities, which cause the most energy depletion in the network. In addition, it supports instant-queries and long-running queries processing, which are quasi-real-time queries processing. Therefore, this proposal combines statistical modeling techniques with the distributed approach to provide a new architecture and a query processing algorithm for optimizing the real-time user query processing for both latency and energy minimization with valid data. This valid data is stained of some uncertainty ( ε ) the user/application is willing to tolerate. In fact, the previous study reveled that in real-time systems, for some applications, the accuracy of results may be sacrificed under some limit to reduce the response time. Thus, Instead of periodically send the sensor readings to the database server for off-line processing or process the query directly into the network, the proposed hybrid approach uses statistical modeling techniques to perform a query processing based on admission control that uses the error tolerance and the confidence interval as the admission parameters to the system. A new concept of virtual network, composed by logical sensors which, in their turn, are composed by a probabilistic model and memory, is used to approximate in the gateway the answers of the query according to a given error tolerance and confidence interval. If the sensor data inside the virtual network is not sufficiently rich to answer the query, the admission controller routes the query towards the physical network. The experimental results based on real world as well as synthetic data sets show that the general proposed architecture provides, among other advantages, good individual query latency and valid data for real-time applications and energy-efficiency for WSNs.