Connectivity Estimation Approaches for Internet of Things-Enabled Wireless Sensor Networks

2022 ◽  
pp. 104-122
Author(s):  
Zuleyha Akusta Dagdeviren ◽  
Vahid Akram
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Exact Algorithms ◽  
Estimation Problem ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Communication Layer ◽  
Main Ideas

Internet of things (IoT) envisions a network of billions of devices having various hardware and software capabilities communicating through internet infrastructure to achieve common goals. Wireless sensor networks (WSNs) having hundreds or even thousands of sensor nodes are positioned at the communication layer of IoT. In this study, the authors work on the connectivity estimation approaches for IoT-enabled WSNs. They describe the main ideas and explain the operations of connectivity estimation algorithms in this chapter. They categorize the studied algorithms into two divisions as 1-connectivity estimation algorithms (special case for k=1) and k-connectivity estimation algorithms (the generalized version of the connectivity estimation problem). Within the scope of 1-connectivity estimation algorithms, they dissect the exact algorithms for bridge and cut vertex detection. They investigate various algorithmic ideas for k connectivity estimation approaches by illustrating their operations on sample networks. They also discuss possible future studies related to the connectivity estimation problem in IoT.

scholarly journals Energy Management in Wireless Sensor Networks for Internet of Things Applications

2019 ◽  
Vol 3 (2) ◽  
pp. 48-52
Author(s):  
Reem Jafar Ismail ◽  
Samar Jaafar Ismae ◽  
Wisam H. Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Energy Management ◽  
System Performance ◽  
Routing Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Efficient Energy ◽  
Long Life

Internet of things (IoT) aims to develop a smart world based on sensing environment. The energy management of wireless sensor networks (WSNs) is a big challenge in IoT since sensor nodes have limited energy and they need to have long life for collecting data and information. The aim of this paper is to propose an efficient energy routing algorithm in WSN and infrastructure based on construction an adaptive energy map of sensor nodes. The results show improvement in overall system performance and lifetime of WSN compared to traditional scenario.

scholarly journals Internet of Things (IoT) Enabled Wireless Sensor Networks Security Challenges and Current Solutions

2019 ◽  
Vol 9 (1) ◽  
pp. 282-290
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Personal Information ◽  
Human Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Research Problems ◽  
The Cross

Nowadays Internet of Things (IoT) is emerging and effective technology along with Wireless Sensor Networks (WSNs) in a few constant applications in which the human intervention significantly reduced along with better human life. In IoT enabled WSNs, the sensor nodes used to assemble the fragile data and communicate towards the sink hub and actuators for automotive remote monitoring process. However as the WSNs operating at free frequency band, it is powerless against different attacks at various layers of WSNs protocol stack in which attackers may try to hack and compromise the user’s personal information. There are different types of attacks in WSNs and several research works conducted to protect from these attacks in WSNs. Majority of security methods proposed are based layered technique. However, the layer approach is not enough to protect the WSNs effectively as the many attackers used the cross-layer information to perform the attacks. This paper presents the study over the layered security solutions and their research problems at first to justify the importance of cross-layer solutions. The review of different ways of designing the cross-layer security techniques for WSNs with their behaviour presented as well. The challenges of IoT enabled WSNs single layered security solutions presented and then the various cross-layer solutions reviewed in this paper. The comparative study of different cross-layer techniques to demonstrate the layers and their parameters involved to detect of security threats. The outcome of this review work is the research challenges noticed from the present cross-layer solutions.

scholarly journals A Report on Designing of Wireless Sensor Networks for IoT Applications

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2004-2009 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Environmental Data ◽  
Internet Technology ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Internet ◽  
Air Conditioner ◽  
Night Time

Internet of things is defined in many ways is an internet technology connected to devices, machines and tools by the means of wireless technology, such as connected homes, cities, cars and roads, etc. The IoT is the platform to connect physical objects that contain built-in technology to interact and sends or communicate with their internal blocks or external environment. Nearly one trillion devices are internet connected devices which are available with mobile applications, linking all these connected things. Billions of devices are being communicated all the way though out the world over network protocols, in 2010 which was made by an IoT. Daily around 12.5 billion things or devices are interacting with internet. Since past two decades many researchers and industries were attracted towards IoT because of its reliability. If domestic appliances like Oven, Refrigerator, Air conditioner, Geezer, Smart TV are connected in a network, they all work together in association to provide an ideal service as an entire, not as a collection of independently working devices. IoT is a powerful tool which is used in many ways in the development of real-world applications and services, for example building a smart residence where light should ON when the person enters into the room at night time, windows can be closed automatically when it rains, and automatically windows will be open if any leakage of gas. Wireless Sensor Networks are included into the “Internet of Things”, where sensor nodes are connected to the Internet vigorously, and use it to act as a team and complete their action. Wireless Sensor Networks are well apt for long-term environmental data acquirement for IoT representation. In this paper, we provide the information on designing challenges on wireless sensor networks for an IoT application.. This paper presents an overview on an IoT, functional design of WSN for IoT application, details an architecture of IoT and related key issues.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

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.

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

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.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

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.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

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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