Top PDF Failure detection of sensor nodes based on Round Trip Delay and Paths in Wireless Sensor Networks

Failure detection of sensor nodes based on Round Trip Delay and Paths in Wireless Sensor Networks

Failure detection of sensor nodes based on Round Trip Delay and Paths in Wireless Sensor Networks

In the proposed method, the faulty sensor nodes are detected by calculating the round trip delay (RTD) time of different round trip paths and comparing them with the threshold value [13]. The scalability of this method is checked by simulating the WSNs with a large number of sensor nodes in Network Simulator 2 (NS2). Energy consumption is increased by redundancy and the network lifetime is reduced, cluster head failure to detect the faulty node has data loss problem. The necessity of the received signal strength measurement in the cluster head variation and assigning separate wavelength of each of the link in other fault detection techniques are overcome in this method.
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Faulty node detection in wireless sensor network using round trip delay and path

Faulty node detection in wireless sensor network using round trip delay and path

Wireless sensor networks (WSNs) with large numbers of portable sensor nodes has tremendous applications in a variety of fields, like surveillance, home security, military operations, medical, environmental and industrial monitoring. Due to rapid growth in electronic fabrication technology it is possible to manufacture the portable sensor node at low cost with better accuracy and sensitivity. Hence large numbers of portable sensor nodes can be deployed in the field to increase the quality of service (QoS) of such wireless sensor networks. The practices to use large numbers of sensor nodes will increases the probability of sensor node failures in such WSNs. Data analysis based on such faulty sensor node will become incorrect or deviate from the mean value. This wills eventually collaps the quality of service (QoS) of WSNs. The sensor node in the WSNs can become faulty due to various reasons such as battery failure, environmental effects, hardware or software malfunctions. Better quality of service (QoS) is achieved by discarding the data from such faulty sensor nodes in the analysis. This will demand the efficient and accurate detection of faulty sensor nodes in WSNs. The faulty sensor nodes identification suggested is based on comparisons between neighboring nodes and dissemination of the decision. Made at each node. Algorithm proposed in this method can’t detect the malicious nodes. Cluster head failure recovery algorithm used to detect the faulty node has data loss problem, occurring due to transfer of cluster head. Path redundancy technique to detect faulty sensor node is suggested. Redundancy increases the energy consumption and reduces the number of correct responses in network lifetime. Excessive redundant paths in WSNs will slow down the fault detection process. Link failure detection based on monitoring cycles (MCs) and monitoring paths (MPs) is presented. Three-edge connectivity in the network, separate wavelength for each monitoring cycle and monitoring locations are the limitations of this method. The proposed method of fault detection is based on RTD time measurement of RTPs. RTD times of discrete RTPs are compared with threshold time to determine failed or malfunctioning sensor node. Initially this method is tested and verified on three wireless sensor nodes, implemented by using microcontroller and Zigbee.
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FAULT NODE DETECTION IN WIRELESS SENSOR NETWORK BASED ON ROUND TRIP DELAY

FAULT NODE DETECTION IN WIRELESS SENSOR NETWORK BASED ON ROUND TRIP DELAY

Wireless sensor networks (WSNs) with Portable sensor nodes are a large number of potential applications such as surveillance, security, military operations, and medical, environmental and industrial inspection fields. Due to the rapid enhancement of electronic production technology it is possible to produce the cost of portable sensor node with good accuracy and sensitivity. Therefore, large portable sensor nodes can be used in the area to maximize the quality of such wireless sensor network service. Practice increases such sensor node errors in such WSNs, sensor nodes are used extensively. Such faulty sensor nodes based data analysis is wrong or different from the mean value. This will eventually degrade WSNs service quality. WSNs may be corrupted by sensor nodes such as battery failure, environmental impact, hardware or software errors for various reasons. Such faulty sensor node data rejection in analysis has achieved a good quality service. These WSNs require efficient and accurate detection of faulty sensor nodes. The faulty sensor node is used in different ways to measure Round Trip Delay (RTD) time of discrete round trip paths in the form of comparison with threshold value First, the proposed method of
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Sensor node failure detection using round trip path and delay

Sensor node failure detection using round trip path and delay

days, application of wireless sensor networks (WSNs) has been increased due to its vast potential to connect the physical world to the practical world. Also, advancement in microelectronic fabrication technology reduced the cost of manufacturing convenient wireless sensor nodes and now it becomes a trend s sensors in WSNs so that to increase the quality of service (QoS). The QoS of such WSNs is mainly affected by the faulty or malfunctioning sensor nodes. Probability of sensor node failure increases if number of sensor node increases in the network. For maintaining the better QoS under failure conditions such faulty sensor node should be detected and it should be removed. In this proposed method, faulty sensor node is detected by calculating the round trip delay (RTD) time of round them with threshold value. This proposed method is tested with three sensors Nodes designed using microcontroller, sensor and ZigBee. The main server section which will display the failure sensor node is also designed using microcontroller and ZigBee.
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Design And Implementation Of Detecting The Failure Of Sensor Node Based On Rtt Time And Rtps In Wsns

Design And Implementation Of Detecting The Failure Of Sensor Node Based On Rtt Time And Rtps In Wsns

Wireless Sensor Networks (WSNs) are widely used in various applications. The efficient and accurate design of WSNs to increase the quality of service (QoS) has become an important area of research. Implementing such networks requires deployment of the large numbers of portable sensor nodes in the field. The QoS of such network is affected by lifetime and failure of sensor node. The main function of wireless sensor networks is to gather data from the monitoring area. The collected data might be wrong due to fault nodes hence detecting failure nodes are important to improve the QoS. The objective is to reduce detection time by considering less number of nodes in round trip paths construction because the number of nodes (N) in WSN increases detection time increases exponentially and the maximum numbers of round trip paths produced are not adequate method to speed up detection time. The round trip transmission (RTT) time of discrete round trip paths (RTPs) are compared with threshold value and result shown by simulating the circular topology of WSNs.
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ENERGY EFFICIENT ADAPTIVE BROADCASTING SCHEME FOR WIRELESS SENSOR NETWORKS

ENERGY EFFICIENT ADAPTIVE BROADCASTING SCHEME FOR WIRELESS SENSOR NETWORKS

One of the most critical issues in the WSNs is energy efficiency, because sensor nodes are operated by battery power. Due to battery limitations, WSNs are commercialized based on ZigBee [2] or IEEE 802.15.4 [3], which are current standards for low power communication. The energy conserving resources are highly attractive, as they have a direct influence on network lifetime. Network lifetime is generally defined as the time period the network is able to perform the sensing functions and to send information to the sink. During the network lifetime, some nodes may become unavailable and additional nodes might be deployed. To reduce power consumption, a popular mechanism is to schedule the sensor node activity such that redundant nodes have to enter into the sleep mode as often as possible. Another method is to minimize the sensing range, while the sensing coverage objective is satisfied. Adapting the sensing range leads to minimization of sensing range and the sensor
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Delay Adjust Mac Protocol for Energy Efficiency in Wireless Sensor Networks

Delay Adjust Mac Protocol for Energy Efficiency in Wireless Sensor Networks

and our proposed protocol, is denoted as DA-MAC. Figure 8 shows the measured average energy consumption for intermediate nodes. The traffic is heavy when the message inter-arrival time is less than 4s. We can see in the light traffic case S-MAC consumes more energy than DA-MAC as idle listening occurrences are more vulnerable and consumes more energy. In heavy traffic case, S- MAC consumes slightly more energy than DA-MAC. One reason is that SMAC has synchronization overhead of sending and receiving SYNC packets. Another reason is that SMAC introduces more latency and actually uses more time to pass the same amount of data. In fact, if the traffic is extremely heavy and a node does not have any chance to follow its sleep schedule, the scheme of periodic listen and sleep does not benefit at all.
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Detection of False Data Distribution Nodes in Wireless Sensor Networks

Detection of False Data Distribution Nodes in Wireless Sensor Networks

deployed at a certain interested area as shown in Fig.2 The sink is a trust and powerful data collection device, which is responsible for collecting the data sensed by sensor nodes. Each sensor node Ni has a unique nonzero identifier and is stationary in allocation. The communication in the network is generality, assumed each sensor node periodically collects the sensed data and reports them to the sink via a predefined routing. In the attack model, assume that an adversary A can capture a small fraction of sensor nodes in a local area, reprogram them with malicious code, and redeploy them back into the network using the physical node compromise attack. Especially the adversary has two physical attack policies: First directly physically attack the sensor node at the sensor node’s original position then firstly shut down some sensor nodes and launch physical attack at other place. Without loss of generality, assume that there are n sensor nodes in a local area, and the adversary A can only simultaneously compromise k sensor nodes in the local area, where k<n.
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Forest Fire Monitoring System Based On ZIG-BEE Wireless Sensor Network

Forest Fire Monitoring System Based On ZIG-BEE Wireless Sensor Network

Research in wireless sensor networks has attracted a lot of attention in recent years. Real applications, such as habitat monitoring, environment and structure monitoring, start to work in practical. In this paper, we argue that wireless sensor network is very promising for fire rescue applications. First, we abstract four requirements of this specific application, including accountability of firefighters, real-time monitoring, intelligent scheduling and resource allocation, and web-enabled service and integration. To meet these requirements we propose Sensors for sensing Physical parameters (temperature and humidity), a wireless sensor network architecture for this specific type of application. Based on these requirements and the characteristics of wireless sensor networks, several research challenges in terms of new protocols as well as hardware and software support are examined[1].
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Secure Data Packet of Cluster Head and Base          Station in Wireless Sensor Networks

Secure Data Packet of Cluster Head and Base Station in Wireless Sensor Networks

Abstract-LEACH in wireless sensor networks (WSNs) achieves good performance with reserving energy consumption and decreasing system delay. LEACH protocol does not consider a security issue for ensuring the protection of the network. So the security in LEACH is a complicated task. were we improved the LEACH protocol called a novel algorithm to select cluster heads with highest and balanced energy in wireless sensor networks to choose the cluster head with the highest energy. Were the cluster heads gathered data from the surrounding nodes and send it to the base station. But this data collecting from surrounding area to the cluster heads and base station without consider about security. In this paper, we improved a novel algorithm to select cluster heads with highest and balanced energy in wireless sensor networks with authentication protocol to protect our previous work and network from attackers. This protocol uses RSA algorithms to secure packet during send to both cluster heads and base station. The results of simulation not only prolong the lifetime of wireless sensor networks, but also enhance routing security strongly.
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Failure Node Detection and Recovery in Wireless Sensor Networks

Failure Node Detection and Recovery in Wireless Sensor Networks

then schedule at unique packet maintenance into the cluster head from base station and specified allocation energy with less cost consumption and reduce the traffic off signal range, packet or wavelength collision rate till to reach the destination in the clustering network environment. Using random key generation mechanism [16], each mobile node having unique key and filter those key based on replication to be presented in the cluster network. The author of [3] proposes gradient routing with two-hop information for industrial wireless sensor networks to enhance real-time performance with energy efficiency. Accurate localization in cluttered and noisy environments is commonly provided by means of a mathematical algorithm referred to as a state estimator or filter. Author [5] proposes a novel hybrid particle/finite impulse response (FIR) filtering algorithm for improving reliability of Packet Filter based localization schemes under harsh conditions causing sample privation.
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Resource Aware Sensor Nodes in Wireless Sensor Networks

Resource Aware Sensor Nodes in Wireless Sensor Networks

Figure 5 shows how the residual power in the node’s batteries decreases through time. The values were obtained by taking the average over all the sensor nodes at each timestep. As expected, networks that do not feature energy harvesting or IDEALS are the first to deplete their energy reserves (a). If energy harvesting is added (b), the rate of depletion is reduced (as the nodes are receiving a small energy increase every timestep). It can be seen that once the power level of ‘b’ has dropped below 5%, it then begins to locally oscillate as the nodes toggle between PP0 and PP1. If IDEALS is implemented (c), as the power level drops, the rate of depletion decreases in steps at specific thresholds, determined by the PP (Power Priority) thresholds in the IDEALS setup. By decreasing the PP, the node is dropping messages in order of MP (Message Priority). If energy harvesting is added to IDEALS (d), the effect of IDEALS is emphasised, and the gradients decrease further.
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Survey on security in Wireless Sensor Networks

Survey on security in Wireless Sensor Networks

Sinkhole attack: It prevents the base station from obtaining complete and correct sensing data. A compromised data tries to draw all or as much traffic as possible from a particular area by making itself attractive to the surrounding nodes and then do selective forwarding, modifying or eavesdrop packets Hello flooding attack: New sensor node broadcasts “Hello” to find its neighbors and also it broadcast its route to the base station. It also validates that the node sending hello message is in the vicinity. Adversary can exploit this feature by using a high-powered wireless link. It can assure every node in the network that he is their neighbor, thus starting communication with nodes, As obvious by using this attack security of the information is compromised as the attacker gain access to the information flow in the network. Adversary should possess enough resources to manage this attack, and should be able to provide high quality routing path to other nodes in network. Traffic will find this path attractive enough to send packets through it, creating data congestion and disturbing the hierarchy of the data flow in network.
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WSN Using Clustering and Fault Detection

WSN Using Clustering and Fault Detection

Yang Qin at al The hierarchical routing protocols have been proposed to deal with the path search in wireless multi hop networks in various research works. Most existing designs of ad hoc network routing protocols are based on the assumption of non-adversarial environment, that every node in the network is cooperative and well behaved. However, such assumption usually does not hold in realistic environments. The performance of current routing protocols degrades significantly when misbehaving nodes exist in the network. an efficient and effective hierarchical algorithm for MANET, which is called Fault-tolerance Cluster Head based (FTCH) routing protocol. FTCH is proposed to provide a certain packet delivery fraction guarantee and low routing overhead in the presence of faulty nodes. The FTCH routing protocol is evaluated through both analysis and simulations compared with Max-Min Multi-Hop routing protocol (MMMH), AODV and DSR. The results show that FTCH greatly improves the ad hoc routing performance in the presence of misbehaving nodes.
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Filtering method in wireless sensor network management based on EMD algorithm and multi scale wavelet analysis

Filtering method in wireless sensor network management based on EMD algorithm and multi scale wavelet analysis

In wireless multi hop Ad hoc networks, media access control (MAC) layer protocol is mainly responsible for the two functions. One is to establish a network structure. Because tens of thousands of sensor nodes with high density distribution in the tested area, MAC layer mechanisms need to provide efficient communication links for data transmission, and the characteristics of self-organization network structure of wireless communication in multi hop transmission and network [5]. The second is for the sensor nodes effectively and reasonably allocate resources. Bluetooth and mobile Ad hoc network may be the existing network is most close to the sensor network. However, Bluetooth, the star network topology, and uses the time division multiplexing mechanism of centralized distribution, wireless sensor networks which often adjust for topology need is not favorable.
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Title: A Review on Improving Packet Analysis in Wireless Sensor Network using Bit Rate Classifier

Title: A Review on Improving Packet Analysis in Wireless Sensor Network using Bit Rate Classifier

Paper[7] determines several important performance matrices related to the sensor node’s energy consumption. Numerical analysis was provided to validate the proposed model and the results obtained. The results show that the energy consumption for switching between the active mode and sleep mode does not depend significantly on the number of data packets. However, the energy consumption for transmitting the data packets depends on the rate at which data packets are generated, which means that transmitting high-density data requires the expenditure of more energy.
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Biodegradable sensor nodes  Zero ecological impact nodes for wireless sensor networks

Biodegradable sensor nodes Zero ecological impact nodes for wireless sensor networks

The stakeholder groups were based on a brainstorm session with peers. This session was mainly focused on correcting personal bias, and closing gaps in knowledge about possible groups. As a result the identified stakeholder groups of biodegradable sensor nodes are mostly researchers in ecological fields, civil engineering contractors and researchers, farmers, the DIY community and companies with large outdoor facilities, like Rijkswaterstaat. These are the main stakeholders because these groups can either use biodegradable sensor nodes for their own research, innovative monitoring of systems, structures and locations, or add to its value by innovation on the base system. These users are among many possible users but should be seen as examples. They originate from a brainstorm session with peers. As can be seen there are three categories they can be divided in. Researchers, surveillers and innovators. These groups will be analysed further and people from each group will be found and interviewed. Researchers
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A Wormhole Attack Detection and Prevention Technique in Wireless Sensor Networks

A Wormhole Attack Detection and Prevention Technique in Wireless Sensor Networks

Security is one of the major and important issues surrounding net- work sensors because of its inherent liabilities, i.e. physical size. Since network sensors have no routers, all nodes involved in the network must share the same routing protocol to assist each other for the transmission of packets. Also, its unguided nature in dy- namic topology makes it vulnerable to all kinds of security at- tack, thereby posing a degree of security challenges. Wormhole is a prominent example of attacks that poses the greatest threat be- cause of its difficulty in detecting and preventing. In this paper, we proposed a wormhole attach detection and prevention mech- anism incorporated AODV routing protocol, using neighbour dis- covery and path verification mechanism. As compared to some pre- existing methods, the proposed approach is effective and promising based on applied performance metrics.
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USING SWARM INTELLIGENCE TECHNIQUE IN RZLEACH FOR WIRELESS SENSOR NETWORKS

USING SWARM INTELLIGENCE TECHNIQUE IN RZLEACH FOR WIRELESS SENSOR NETWORKS

As MS cannot be closed to all the nodes for collecting data. So a new idea has been developed called Rendezvous Node (RNs) [4,6]or Rendezvous Point (RPs). The RP is a point near the trajectory of MS and a node located nearby. This node transmits data to MS as it passes nearby. The MS sends signals called beacons that notify the RNs of the MS arrival. The advantage of RZ is that it reduces the energy consumption to a great extent. The most important condition for RZ is the distance from the MS trajectory i.e.

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Design of wireless sensor network node based on CyFi technology and ARM7 system

Design of wireless sensor network node based on CyFi technology and ARM7 system

CY3271 kit CD-ROM provides design examples of each PSoC, part PSoC the design revisions based on these examples is the. In order to realize the function, you need to add the destination node in the node A sends B message ID information, so that Hub will receive the message and then forwarded out. Each CyFi transceiver 2 ID; a 6 byte Radio ID, the ID transceiver factory burned into, cannot be changed and the only global; another is 1 bytes of Node ID, the ID identified in node bindings, can be specified in advance can be dynamically allocated by Hub. Because Ra-dio ID is complex, developers can ignore the RadioID in the development process, and focus only on Node ID. Wireless communication circuit using NRF905 as the control chip to send and receive data. The NRF905 is a monolithic RF transceiver chip produced by Nordic company, working on the 433/868/915MHz3 ISM channel, low power consumption. The built-in integrated data protocol and CRC tree error detection can automatically complete word processing [11]. Automatic completion of Manchester is coding / decoding. Simply complete the wireless transmission of all through the SPI can be very convenient for model configuration for the four industries: power off and SPI programming mode, standby and SPI programming mode, transmission mode, the receiving mode. NRF905 is a data packet transmission rate up to 32Mb/s, additional antenna communication distance is more than 120m, can meet a variety of wireless sensor network data transmission requirements.
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