scholarly journals AMPC: A Lightweight Hybrid Cryptographic Algorithm for Wireless Sensor Networks

Author(s):  
Md. Navid Bin Anwar ◽  
Maherin Mizan Maha

Wireless sensor network (WSN) is a group of several autonomous sensor nodes attached to each other. Wireless sensor networks are commonly used in a lot of applications and are expected to have a cheap deployment cost. The network of sensors continues to grow aiding the need of the system. Due to that, sensors become vulnerable to attacks and need strong security mechanism. To strengthen the security of data which are transmitted through sensors in WSN, different cryptographic schemes are used. As WSN has limited energy source, therefore, complex cryptographic algorithms may require excessive computational time which not only make the data transmission slow but the life time of sensor network will be significantly affected. To overcome these challenges a new hybrid cryptographic scheme, AES and Modified Playfair Cipher (AMPC), is introduced in this paper.

Sensor nodes are exceedingly energy compelled instrument, since it is battery operated instruments. In wsn network, every node is liable to the data transmission through the wireless mode [1]. Wireless sensor networks (WSN) is made of a huge no. of small nodes with confined functionality. The essential theme of the wireless sensor network is energy helpless and the WSN is collection of sensor. Every sensor terminal is liable to sensing, store and information clan and send it forwards into sink. The communication within the node is done via wireless network [3].Energy efficiency is the main concentration of a desining the better routing protocol. LEACH is a protocol. This is appropriate for short range network, since imagine that whole sensor node is capable of communication with inter alia and efficient to access sink node, which is not always correct for a big network. Hence, coverage is a problem which we attempt to resolve [6]. The main focus within wireless sensor networks is to increase the network life-time span as much as possible, so that resources can be utilizes efficiently and optimally. Various approaches which are based on the clustering are very much optimal in functionality. Life-time of the network is always connected with sensor node’s energy implemented at distant regions for stable and defect bearable observation [10].


Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.


2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.


2017 ◽  
Vol 13 (04) ◽  
pp. 45 ◽  
Author(s):  
Liping LV

<p class="0abstract"><span lang="EN-US">Wireless sensor network is a new field of computer science and technology research. It has a very broad application prospects. In order to improve the network survival time, it is very important to design efficient energy-constrained routing protocols. In this paper, we studied the characteristics of wireless sensor networks, and analyzed the design criteria of sensor network routing algorithms. In view of the shortcomings of traditional algorithms, we proposed an energy-aware multi-path algorithm. When selecting a data transmission path, the energy-aware multi-path algorithm can avoid nodes with low energy levels. At the same time, it takes the remaining energy of the node and the number of hops as one of the measures of the path selection. The multi-path routing algorithm realized the low energy consumption of the data transmission path, thus effectively prolonging the network lifetime. Compared with the traditional algorithm, the results show that our method has high reliability and energy efficiency.</span></p>


2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime


Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4281
Author(s):  
Ngoc-Thanh Dinh ◽  
Younghan Kim

Wireless sensor network (WSN) studies have been carried out for multiple years. At this stage, many real WSNs have been deployed. Therefore, configuration and updating are critical issues. In this paper, we discuss the issues of configuring and updating a wireless sensor network (WSN). Due to a large number of sensor nodes, in addition to the limited resources of each node, manual configuring turns out to be impossible. Therefore, various auto-configuration approaches have been proposed to address the above challenges. In this survey, we present a comprehensive review of auto-configuration mechanisms with the taxonomy of classifications of the existing studies. For each category, we discuss and compare the advantages and disadvantages of related schemes. Lastly, future works are discussed for the remaining issues in this topic.


Author(s):  
Saloni Dhiman ◽  
Deepti Kakkar ◽  
Gurjot Kaur

Wireless sensor networks (WSNs) consist of several sensor nodes (SNs) that are powered by battery, so their lifetime is limited, which ultimately affects the lifespan and hence performance of the overall networks. Till now many techniques have been developed to solve this problem of WSN. Clustering is among the effective technique used for increasing the network lifespan. In this chapter, analysis of multi-hop routing protocol based on grid clustering with different selection criteria is presented. For analysis, the network is divided into equal-sized grids where each grid corresponds to a cluster and is assigned with a grid head (GH) responsible for collecting data from each SN belonging to respective grid and transferring it to the base station (BS) using multi-hop routing. The performance of the network has been analyzed for different position of BS, different number of grids, and different number of SNs.


2019 ◽  
Vol 29 (09) ◽  
pp. 2050141 ◽  
Author(s):  
Muhammed Enes Bayrakdar

In this paper, a monitoring technique based on the wireless sensor network is investigated. The sensor nodes used for monitoring are developed in a simulation environment. Accordingly, the structure and workflow of wireless sensor network nodes are designed. Time-division multiple access (TDMA) protocol has been chosen as the medium access technique to ensure that the designed technique operates in an energy-efficient manner and packet collisions are not experienced. Fading channels, i.e., no interference, Ricean and Rayleigh, are taken into consideration. Energy consumption is decreased with the help of ad-hoc communication of sensor nodes. Throughput performance for different wireless fading channels and energy consumption are evaluated. The simulation results show that the sensor network can quickly collect medium information and transmit data to the processing center in real time. Besides, the proposed technique suggests the usefulness of wireless sensor networks in the terrestrial areas.


2014 ◽  
Vol 15 (1) ◽  
pp. 42-52 ◽  
Author(s):  
Mario Collotta ◽  
Mario Denaro ◽  
Gianfranco Scatà ◽  
Antonio Messineo ◽  
Giuseppina Nicolosi

Abstract The dynamic management of traffic light cycles is a really interesting research issue considering modern technologies, which can be used in order to optimise road junctions and then improve living conditions of the roads. Wireless sensor networks represent the most suitable technology, as they are easy to deploy and manage. The data relating to road traffic flows can be detected by the sensor network and then processed through the innovative approach, proposed in this work, in order to determine the right green times at traffic lights. Although wireless sensor networks are characterized by very low consumption devices, the continuous information transmission reduces the life cycle of the whole network. To this end, the proposed architecture provides a technique to power the sensor nodes based on piezoelectric materials, which allow producing potential energy taking advantage of the vibration produced by the passage of vehicles on the road.


Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.


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