Comprehensive and systematic review of the service composition mechanisms in the cloud environments

The Industry 4.0 IoT network integration with blockchain architecture is a decentralized, distributed ledger mechanism used to record multi-user transactions. Blockchain requires a data storage system designed to be secure, reliable, and fully transparent, emerged as a preferred IoT-based digital storage on WSN. Blockchain technology is being used in the paper to construct the node recognition system according to the storage of data for WSNs. The data storage process on such data must be secure and traceable in different forensics and decision making. The primary theme of the dynamic data security is therefore for rejecting exploitation of the unauthorized user and for evaluating the mechanism in tracing and evidence of system’s data operation in a dynamic manner, growth and quality features under the stochastic state of the model; (1) a mathematical method for the secured storage of data in dynamic is built through distributed node cooperation in IoT industry. (2) the ownership transition feature and the dynamic storage of data system architecture are configured, (3) the emerging distributed storage architecture for blockchain-based WSN will substantially reduce overhead storage for each node without affecting data integrity; (4) minimize the latency of data reconstruction in distributed over storage system, and propose an effective and scalable algorithm for optimizing storage latency issue. In addition to this research, the system implements verified possession of data for replacing the evidence in original digital currency for mining and to store new data blocks that will be compared to the proof system, dramatically reduces computational capacity. The proposed ODSD framework has exceptional benefits for real-time applications while maintaining the security of the dynamic storage of data.

Optimized dynamic storage of data (ODSD) in IoT based on blockchain for wireless sensor networks

Wireless sensor network (WSN) is one of the interesting issues in the information technology domain. It is used in various fields such as medicine, agriculture, meteorology, etc. that eases lots of difficult tasks to do but have some challenges too. Deployment is the greatest challenge in WSN that affects other features like coverage, connectivity, energy efficient and lifetime. Despite the importance of the deployment problem in WSN, to the best of our knowledge, there isn't any systematic literature review to give us systematical analyses the state-of-the mechanisms in this field. Therefore, this study reviewed the deployment mechanisms which have been used in WSN systematically. The deployment mechanisms can be classified into two main categories: deterministic and nondeterministic. Also, this study represents a comparison of the important techniques of the selected articles in each category to offer a guideline for further studies and new challenges. We also have noted some open issues for future research.

Deployment Strategies in the Wireless Sensor Networks: Systematic Literature Review, Classification, and Current Trends

Large-scale wireless sensor network (LSWSN) is composed of a huge number of sensor nodes that are distributed in some region of interest (ROI), to sense and measure the environmental conditions like pressure, temperature, pollution levels, humidity, wind, and so on. The objective is to collect data for real-time monitoring so that appropriate actions can be taken promptly. One of the sensor nodes used in an LSWSN is called the sink node, which is responsible for processing and analyzing the collected information. It works as a station between the network sensor nodes and the administrator. Also, it is responsible for controlling the whole network. Determining the sink node location in an LSWSN is a challenging task, as it is crucial to the network lifetime, for keeping the network activity to the most possible extent. In this paper, the Harris' hawks optimization (HHO) algorithm is employed to solve this problem and subsequently the Prim's shortest path algorithm is used to reconstruct the network by making minimum transmission paths from the sink node to the rest of the sensor nodes. The performance of HHO is compared with other well-known algorithms such as particle swarm optimization (PSO), flower pollination algorithm (FPA), grey wolf optimizer (GWO), sine cosine algorithm (SCA), multi-verse optimizer (MVO), and whale optimization algorithm (WOA). The simulation results of different network sizes, with single and multiple sink nodes, show the superiority of the employed approach in terms of energy consumption and localization error, and ultimately prolonging the lifetime of the network in an efficacious way.

/pdf/optimal-sink-node-placement-in-large-scale-wireless-sensor-2tqzx0dw6l.pdf

Optimal Sink Node Placement in Large Scale Wireless Sensor Networks Based on Harris’ Hawk Optimization Algorithm

Strategies based on various aspects of clustering in wireless sensor networks using classical, optimization and machine learning techniques: Review, taxonomy, research findings, challenges and future directions

Among the various parameters and constraints considered that are affected by optimal deployments, performance as per the mac layer has attained limited attention. This article is aimed at two things. Firstly, it aims to understand the packet delivery parameters for convergecast communication pattern ideal for Zigbee based wireless sensor networks. Secondly, it aims to suggest enhancements through proposing a quasi based deployment pattern, that may help boost the performance to acceptable levels. We simulate and observe the packet based statistics at the mac layers employing different protocols like AODV, DSR. This paper is also an effort to suggest the use of Quasi based deployment strategy comparable to the existing random and deterministic methods. The inferences obtained are for zigbee networks encorporating both peer to peer (using a tree based topology) and star (using a graph based topology) WSN architectures. A quasi based deployment pattern offers scope for improvement of the reliability metrics which is the sole accountability of the mac layer, irrespective to the protocol employed at the higher levels or the backbone structure for communication. DOI:  http://dx.doi.org/10.11591/telkomnika.v15i1.8074

/pdf/evaluating-quasi-random-deployment-in-zigbee-based-wireless-47hit8bvq2.pdf

Evaluating Quasi Random Deployment in Zigbee Based Wireless Sensor Networks

Wireless ad hoc network is characterized by autonomous nodes communicating with each other by forming a multi hop radio network and maintaining connectivity in a decentralized manner. This paper presents a systematic approach to the interdependencies and the analogy of the various factors that affect and constrain the wireless sensor network. This article elaborates the quality of service parameters in terms of methods of deployment, coverage and connectivity which affect the lifetime of the network that have been addressed, till date by the different literatures. The analogy of the indispensable rudiments was discussed that are important factors to determine the varied quality of service achieved, yet have not been duly focused upon.

Quality of Service Metrics in Wireless Sensor Networks: A Survey

Analysis of scalability for routing protocols in wireless sensor networks

Optimal sink placement in backbone assisted wireless sensor networks

This paper presents development of a lifetime prolonging algorithm for underwater sensor networks. The challenges faced in monitoring underwater scenarios is different the usual radio model for calculating the dissipation losses as well as the transmission losses is not applicable. Hence the constraints on terrestria l WSN's cannot be totally adopted for lifetime computations. The proposed algorithm takes into account the balanced energy consumption by nodes, with varying parameters related to the sensing field like energy, attenuation, path loss component. The aim is to prolong the node lifetime and hence network lifetime. The simulation results of the proposed algorithm is compared with the existing algorithms and found to be superior in terms of the lifetime.

/pdf/lifetime-prolonging-algorithm-for-underwater-acoustic-sensor-3tn0mp0ly5.pdf

Itu Snigdh

Papers

Evaluating Quasi Random Deployment in Zigbee Based Wireless Sensor Networks

Quality of Service Metrics in Wireless Sensor Networks: A Survey

Analysis of scalability for routing protocols in wireless sensor networks

Optimal sink placement in backbone assisted wireless sensor networks

Lifetime Prolonging Algorithm for Underwater Acoustic Sensor Network