DATA GATHERING AND COMMUNICATION FOR WIRELESS SENSOR NETWORKS — A CENTRALIZED APPROACH

The sensor nodes are independent and work as sender, receiver and intermediate node in Wireless Sensor Network (WSN). The sensor nodes are forming the small network in which the one or more sender is sending data to one destination/s through intermediate nodes or sending information to Base Station (BS). The information collect by base station is further analyzed. The nodes are also static or mobile depends on the situation or conditions. The connection establishment and data sending is possible through routing protocols of WSN. The routing protocols of WSN are not same as traditional wireless routing protocols. One major issue on this network is security. The routing protocols are sending information to destination from particular source and the routing strategy is provides the better way of delivery in the network. The sensor nodes in network are performing through limited battery supply called node energy or power. The attacker are also affected the limited energy resource. In this paper the center of consideration is on the security issues related to WSN routing protocols. The routing in WSN remains a key issue because of that without accurately functioning of routing protocols, the network cleanly will not work the technique it's intended to. Unfortunately, routing also one of the most difficult to protect against attacks malicious activities because of the administration in WSN. The better protection scheme is provides the complete security from attacks and the secure routing is provides the better and trustful network performance.

À Load-balancing and Self-adaptation Clustering for Lifetime Prolonging in Large Scale Wireless Sensor Networks

Nodes in the Wireless sensor network (WSN) have the limited power, memory and battery capacity. In this work, we propose an efficient routing algorithm called Cluster Based Wireless Sensor Network using Ant Colony Optimization (CBACO). The Cluster Heads (CH) are selected based on the cost derived from node parameters remaining energy, number of neighbours and distance to base station. The weighted average method is used to compute cost. The routing processes are established in two levels. The cluster member to cluster head data transmission is handled at level one and in the second level path finding process between cluster head to base station handled by Ant Colony Optimization (ACO) method which is the biologically inspired optimization technique. All the cluster head nodes are participate in the second level inter-cluster routing operation. The performance of the CBACO algorithm in terms of delay is minimized by using the clustering method and ACO method. The efficiency of the proposed algorithm is analysed by compare with existing routing algorithm which uses LEACH and ACO method. The results indicate that our proposed work achieves low energy consumption and high throughput.

Localization of mobile nodes in wireless sensor network gets more and more important, because many applications need to locate the source of incoming measurements as precise as possible. Many previous approaches to the location-estimation problem need know the theories and experiential signal propagation model and collect a large number of labeled samples. So, these approaches are coarse localization because of the inaccurate model, and to obtain such data requires great effort. In this paper, a semi-supervised manifold learning is used to estimate the locations of mobile nodes in a wireless sensor network. The algorithm is used to compute a subspace mapping function between the signal space and the physical space by using a small amount of labeled data and a large amount of unlabeled data. This mapping function can be used online to determine the location of mobile nodes in a sensor network based on the signals received. We use independent development nodes to setup the network in metallurgical industry environment, outdoor and indoor. Experimental results show that we can achieve a higher accuracy with much less calibration effort as compared with RADAR localization systems.

Safe path-finding is extremely necessary for multihop wireless systems such as Wireless Sensor Networks. Multihop wireless systems are more unprotected to safety outbreaks as associated to single-stage wireless networks. Cross-layer design production is a precise significant character for wireless sensor Advanced security network is significant submissions. for the achievement of announcement among sensor nodes in wireless sensor network because the numbers composed is regularly less and the network is most vulnerable. Numerous Security methods have been suggested to deliver safety resolutions besides numerous threats to the Cross layer modification techniques in Wireless sensor networks. In this paper we overview the existing schemes for the security of cross-layer design in wireless sensor networks. The proposed Security model will provide more security between sensor nodes and the base station in wireless sensor network. Security is important for the success of the wireless sensor network because the data collected are often sensitive and the network is particularly vulnerable. In the cross-layer design, constraints are substituted between changed layers to protect the well-organized use of energy. In this paper, we propose a secure security model that is based on cross-layer design. It uses a cross layer optimization Machine Reproduction consequences confirm that our proposed safety model better in many situations and in unpromising violence-disposed to the situation.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

When using multiple sensor nodes in wireless sensor networks (WSNs) for monitoring (or measuring) parameters of the target and sending the result to the base station (BS), data redundancy is an inevitable problem. The measured data often contains the same information, and sending redundant data to BS causes the waste of energy of sensor nodes and the risk of congestion. Multi-sensor data fusion in WSNs is a technology of gathering and processing data applied from node to BS. It improves the performance of surveillance systems by allowing the obtained sensed information from multiple sensor nodes aggregated to one unified format data packet to send to BS to make decision. In this paper, we propose a solution namely DF-SWin for sampling sensor node in the cluster to optimize the energy conservation of sensor nodes in clusters and cluster head.

To collect the data and transmit them on the base station is the main task of the sensor nodes in wireless sensor networks (WSNs). This transmission requires a specific routing algorithm. To prolong the network lifetime, sensor nodes need a secure load-balancing route. In this paper, we investigate the facts of ensuring secure sensed data in a balanced energy network backbone, and propose energy-efficient secure path algorithm (ESPA) for WSNs. It is a process of ensuring sensed data authenticity and integrity under a well-structured energy-efficient routing. To overcome the limitation caused by the symmetric key cryptography algorithms for securing data in WSNs, we proposed a mechanism for checking data integrity in a balanced energy network backbone. On this basis, we use the combined version of distance energy aware routing and a checking data integrity method for WSNs. ESPA provides a better performance in maximizing the network lifetime.

We study the scaling capacity of wireless sensor networks in case of multiple gateways are presented. In such a heterogeneous network, many gateways are needed to gather data from the sensor nodes in network. Different from the previously studied single-gateway model, our proposed gateway access model allows multiple gateway nodes being seamlessly connected with high speed wire-line or wide-band radios. Once the data from the sensor node is sent to any gateway node, it can be collaboratively sent to the appropriate sink node among multiple gateways, which could effectively avoid throughput reduction due to multi-hop routing among the sensor node. This mechanism is called ``Destination-hub", which could ensure the bounded time delay and network capacity. However under such a cooperative scheme, two research issues need to be tackled. One is the number of nodes in network and the second is the scaling capacity for each node when multiple gateway nodes are presented. Our proposed model is a fundamental research work for scaling capacity, which could also provide an instructive proposal for future gateway deployment. In this paper, we characterize the scaling capacity between gateways and sensor nodes under different gateway access model. If gateway nodes are randomly deployed, the number is Omega(log n), and there are at least 4 log l gateway nodes are needed in each squarelet region so as to keep the gateway connectivity, where r is the transmitting range of sensor nodes, and l is the side length of the deployed square region. And we can conclude that, the gateway nodes can be tightly bounded by Theta(log n). For random placement, the scaling capacity for such a scheme is (n). And we have also proposed an optimized scheme for reducing the number of gateway nodes. Considering the interference Voronoi cell, the reduced gateway nodes can be 2 lnl, and still bounded by Theta(log n).

During several decades, there has been a meteoric rise in the development and use of cutting-edge technology. The Wireless Sensor Network (WSN) is a groundbreaking innovation that relies on a vast network of individual sensor nodes. The sensor nodes in the network are responsible for collecting data and uploading it to the cloud. When networks with little resources are deployed harshly and without regulation, security risks occur. Since the rate at which new information is being generated is increasing at an exponential rate, WSN communication has become the most challenging and complex aspect of the field. Therefore, WSNs are insecure because of this. With so much riding on WSN applications, accuracy in replies is paramount. Technology that can swiftly and continually analyse internet data streams is essential for spotting breaches and assaults. Without categorization, it is hard to simultaneously reduce processing time while maintaining a high level of detection accuracy. This paper proposed using a Multi-Layer Perceptron (MLP) to enhance the classification accuracy of a system. The proposed method utilises a feed-forward ANN model to generate a mapping for the training and testing datasets using backpropagation. Experiments are performed to determine how well the proposed MLP works. Then, the results are compared to those obtained by using the Hoeffding adaptive tree method and the Restricted Boltzmann Machine-based Clustered-Introduction Detection System. The proposed MLP achieves 98% accuracy, which is higher than the 96.33% achieved by the RBMC-IDS and the 97% accuracy achieved by the Hoeffding adaptive tree.

Wireless sensor networks area collection of a large number of unattended sensor nodes. The sensor nodes are dynamically deployed in the region. In wireless sensor networks, the unlicensed sensor nodes use their temporarily available vacant licensed channels or spectrum band in a telecommunication network. The many open challenges with issues such as adaptive in self-organisation, fault-tolerance and network scalability with cooperative spectrum sensing and sharing are identifying new challenges in wireless sensor networks. In this paper, we proposed the bio-inspired adaptive routing algorithm for cognitive radio wireless sensor networks. The utilisation of the foraging approach of ANTs and BEEs for making the decision of using the available spectrum sensing and sharing of channels over multi-hops communication, provides the method to utilise idle channel and decrease the delay for communication in wireless sensor network. In this paper, we design the algorithm to solve the issue of wireless sensor network and performance of classical routing protocol LEACH and cognitive radio sensor networks (CRSN) evaluates the parameters which proof the self-organisation routing algorithm.

Mobility of sensor nodes in wireless sensor network (WSN) has posed new challenges particularly in packet delivery ratio and energy consumption. Some real applications impose combined environments of fixed and mobile sensor nodes in the same network, while others demand a complete mobile sensors environment. Packet loss that occurs due to mobility of the sensor nodes is one of the main challenges which comes in parallel with energy consumption. In this paper, we use cross layer design between medium access control (MAC) and network layers to overcome these challenges. Thus, a cluster based routing protocol for mobile sensor nodes (CBR-Mobile) is proposed. The CBR-Mobile is mobility and traffic adaptive protocol. The timeslots assigned to the mobile sensor nodes that had moved out of the cluster or have not data to send will be reassigned to incoming sensor nodes within the cluster region. The protocol introduces two simple databases to achieve the mobility and traffic adaptively. The proposed protocol sends data to cluster heads in an efficient manner based on received signal strength. In CBR-Mobile protocol, cluster based routing collaborates with hybrid MAC protocol to support mobility of sensor nodes. Schedule timeslots are used to send the data message while the contention timeslots are used to send join registration messages. The performance of proposed CBR-Mobile protocol is evaluated using MATLAB and was observed that the proposed protocol improves the packet delivery ratio, energy consumption, delay and fairness in mobility environment compared to LEACH-Mobile and AODV protocols.

The sensor nodes in wireless sensor network (WSN) come with limited battery life, thus energy usage in WSN is to be handled with great care. The routing protocols are the major research area to work on the QoS of the network such as network lifetime, scalability, energy consumption, packet overhead, etc. Since sensor node posses limited battery life, to use nodes efficiently yet not loosing connectivity in the network becomes a major issue in designing the routing protocols. To achieve energy efficiency and better network lifetime, grouping of sensor nodes into small clusters and selecting one cluster head seems to have more advantages in comparison with other network models to get better scalability, robustness and end-to-end data delivery. In this paper, we have discussed and studied the different energy-efficient routing protocols for clustering of sensor nodes in wireless sensor network, its merits, demerits and applications.

Efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks

To increase railway use efficiency, the European Railway Traffic Management System (ERTMS) Level 3 requires all trains to constantly and reliably self-monitor and report their integrity and track position without infrastructure support. Timely train separation detection is challenging, especially for long freight trains without electrical power on cars. Data fusion of multiple monitoring techniques is currently investigated, including distributed integrity sensing of all train couplings. We propose a wireless sensor network (WSN) topology, communication protocol, application, and sensor nodes prototypes designed for low-power timely train integrity (TI) reporting in unreliable conditions, like intermittent node operation and network association (e.g., in low environmental energy harvesting conditions) and unreliable radio links. Each train coupling is redundantly monitored by four sensors, which can help to satisfy the train collision avoidance system (TCAS) and European Committee for Electrotechnical Standardization (CENELEC) software integrity level (SIL) 4 requirements and contribute to the reliability of the asynchronous network with low rejoin overhead. A control center on the locomotive controls the WSN and receives the reports, helping the integration in railway or Internet-of-Things (IoT) applications. Software simulations of the embedded application code virtually unchanged show that the energy-optimized configurations check a 50-car TI (about 1-km long) in 3.6-s average with 0.1-s standard deviation and that more than 95% of the reports are delivered successfully with up to one-third of communications or up to 15% of the nodes failed. We also report qualitative test results for a 20-node network in different experimental conditions.