Smart Sensing Network for Smart Technologies

Author(s):  
Francina Sophiya D. ◽  
Swarnalatha P. ◽  
Prabu Sevugan ◽  
T. D. K Upeksha Chathurani ◽  
R. Magesh Babu

Smart environments based on wireless sensor networks represent the next evolutionary development step in engineering, such as industrial automation, video surveillance, traffic monitoring, and robot control. Sensory data come from multiple networks of interconnected sensors with complex distributed locations. The recent development of communication and sensor technology results in the growth of a new attractive and challenging area: wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors that do not only perceive ambient physical parameters but also are able to process information, cooperate with each other, and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption.

2020 ◽  
Vol 34 (34) ◽  
pp. 2050394
Author(s):  
Xiao Wang ◽  
Jian Du ◽  
Rongcheng Zou ◽  
Zebo Zhou

Wireless sensor networks (WSNs) have become one of the core technologies of the internet of things (IoT) system. They are information generation and acquisition systems used by the IoT to sense and identify the surrounding environment. They are also sensor technology, embedding computing technology, communication technology and important product in the development of Internet technology, which have made the whole society more intelligent and humanized. WSNs are multi-hop self-organizing networks consisting of a large number of micro-sensor nodes deployed in the monitoring area. They can collaboratively sense, collect and process the monitored objects and transmit them to the observers. In this paper, we use the cascade failure method to find the key nodes in the WSNs. First, a complex network cascade failure model based on load redistribution is proposed. Differences from the existing model are as follows: (1) for each node, an overload function is defined; (2) the evolution of the network topology is replaced by node weight evolution. Based on the cascade failure model, a method for evaluating the importance of complex load network nodes is proposed and a new definition of node importance is given. This method helps to discover some potential “critical nodes” in the network. The final experimental analysis verifies the effectiveness and feasibility of the proposed method.


2012 ◽  
Vol 588-589 ◽  
pp. 1095-1098 ◽  
Author(s):  
Bi Hua Zhu ◽  
Ying Li Zhu

With the development of agricultural modernization, agricultural environment protection, sensor technology, MEMS, wireless communications, Wireless Sensor Networks have been paid great attention in industry field and our daily life, this paper designs an agricultural environment monitoring system based on wireless sensor networks, and gives the hardware design of sensor nodes and the flowchart of software. In order to meet requirements of agricultural environment monitoring signals, MSP430F149 is chosen as the microprocessor, and CC2420 module acts as the wireless communication module. The system can real-timely monitor agriculture environmental information, such as the temperature, humidity and light intensity.


Author(s):  
Jie Min ◽  
Xingpo Ma ◽  
Hongling Chen

To ensure the security of spatial-temporal Top-k query in two-tiered wireless sensor networks, many schemes have been proposed in the literature in the past decade. However, most of them only consider the scenario where sensor nodes are static, and cannot achieve the security goal for spatial-temporal Top-k query in mobile sensor networks, because the mobility of the sensor nodes will affect the spatial-temporal relationships of the sensory data items generated by the sensor nodes. Although we have proposed some schemes for two-tiered mobile wireless sensor networks (TMWSNs) in our previous work, there is still large room to improve their performances. In this paper, we proposed a novel scheme named STQ-TMWSN for secure fine-grained spatial-temporal Top-k query in TMWSNs based on the virtual-grid construction and the size-order encryption binding. Theoretic analysis shows that STQ-TMWSN can achieve low computation complexity and high security performance. Simulation results indicate that STQ-TMWSN brings much lower communication cost than the state-of-the-art schemes on securing Top-k query in TMWSNs.


Author(s):  
RAJAT BHARDWAJ ◽  
HITESH SHARMA

Nowadays the science and technology has enriched man’s life. In today’s world everything depends upon the technology. One of such technology is sensor technology. Now in every field sensor technology is used. The Wireless Sensor Network has reduced the work of groups of people to one individual person. Wireless sensor network makes the work easy to monitor in the hazardous environments like wild forests, war fields, etc. During that, many of the problems occur. One of such problems is the Hole Formation in Wireless Sensor Networks. The holes are formed in the Wireless Sensor Networks when a group of sensor nodes are enabled to sense the area around it. Here we will discuss what Network Holes are, the different types of holes in the networks and the reasons for hole formation.


Author(s):  
A. Radhika ◽  
D. Haritha

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.


2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.


Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.


Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.


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