10 research outputs found
IoT and WSN applications for modern agricultural advancements: emerging research and opportunities Advances in wireless technologies and telecommunication (AWTT) book series./ Proshikshya Mukherjee, Prasant Kumar Pattnaik, and Surya Narayan Panda, editors.
No full textIncludes bibliographical references and index."This book explores the development of effective data computing operations on agricultural advancement that are fully supported by the Internet of Things, cloud computing, and wireless sensor network systems"--Chapter 1. IoT-based precision agriculture system: a review -- Chapter 2. Applications of wireless sensor networks in healthcare -- Chapter 3. Strengthening agriculture through energy-efficient routing in wireless sensor networks using sink mobility -- Chapter 4. A novel power-monitoring strategy for localization in wireless sensor networks using antithetic sampling method -- Chapter 5. LEACH-VD: a hybrid and energy-saving approach for wireless cooperative sensor networks -- Chapter 6. An integrated GIS and knowledge-based automated decision support system for precision agriculture using IoT -- Chapter 7. Selecting location for agro-based industry using electre III method.1 online resource (xv, 145 pages
A Robust Approach with Text Analytics for Bengali Digit Recognition Using Machine Learning
No full text
LEACH–V: A Solution for Intra-Cluster Cooperative Communication in Wireless Sensor Network
No full textTEEN — V: A solution for intra-cluster cooperative communication in wireless sensor network
No full textSEP-V: A solution to energy efficient technique in intra-cluster cooperative communication for wireless sensor network
No full textTask scheduling algorithm based on multi criteria decision making method for cloud computing environment: TSABMCDMCCE
No full textThis Paper focuses on multi-criteria decision making techniques (MCDMs), especially analytical networking process (ANP) algorithm to design a model in order to minimize the task scheduling cost during implementation using a queuing model in a cloud environment and also deals with minimization of the waiting time of the task. The simulated results of the algorithm give better outcomes as compared to other existing algorithms by 15 percent
Recommended System for Cluster Head Selection in a Remote Sensor Cloud Environment Using the Fuzzy-Based Multi-Criteria Decision-Making Technique
No full textClustering is an energy-efficient routing algorithm in a sensor cloud environment (SCE). The clustering sensor nodes communicate with the base station via a cluster head (CH), which can be selected based on the remaining energy, the base station distance, or the distance from the neighboring nodes. If the CH is selected based on the remaining energy and the base station is far away from the cluster head, then it is not an energy-efficient selection technique. The same applies to other criteria. For CH selection, a single criterion is not sufficient. Moreover, the traditional clustering algorithm head nodes keep changing in every round. Therefore, the traditional algorithm energy consumption is less, and nodes die faster. In this paper, the fuzzy multi-criteria decision-making (F-MCDM) technique is used for CH selection and a threshold value is fixed for the CH selection. The fuzzy analytical hierarchy process (AHP) and the fuzzy analytical network process (ANP) are used for CH selection. The performance evaluation results exhibit a 5% improvement compared to the fuzzy AHP clustering method and 10% improvement compared to the traditional method in terms of stability, energy consumption, throughput, and control overhead
