Data Aggregation and Data Gathering

2013 ◽  
pp. 61-78
Keyword(s):  
Data Aggregation ◽  
Data Gathering

Energy-Efficient Data-Aggregation Technique for Correlated Spatial and Temporal Data in Cluster-Based Sensor Networks

2020 ◽  
Vol 16 (2) ◽  
pp. 53-68
Author(s):  
Khushboo Jain ◽  
Anoop Kumar
Keyword(s):  
Sensor Networks ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Data Gathering ◽  
Base Station ◽  
Sensor Nodes ◽  
Temporal Data ◽  
Network Applications ◽  
Efficient Data ◽  
Aggregation Technique

Continuous-monitoring applications in sensor network applications require periodic data transmissions to the base-station (BS), which may lead to unnecessary energy depletion. The energy-efficient data aggregation solutions in sensor networks have evolved as one of the favorable fields for such applications. Former research works have recommended many spatial-temporal designs and prototypes for successfully minimizing the data-gathering overheads, but these are constrained to their relevance. This work has proposed a data aggregation technique for homogeneous application set-ups in sensor networks. For this, the authors have employed two ways of model generation for reducing correlated spatial-temporal data in cluster-based sensor networks: one at the Sensor nodes (SNs) and the other at the Cluster heads (CHs). Building on this idea, the authors propose two types of data filtration, first at the SNs for determining temporal redundancies (TRs) in data readings by both relative deviation (RD) and adaptive frame method (AFM) and second at the CHs for determining spatial redundancies (SRs) by both RD and AFM.

scholarly journals A Review on Secure Group Key Management Schemes for Data Gathering in Wireless Sensor Networks

2020 ◽  
Vol 10 (1) ◽  
pp. 5108-5112
Author(s):  
M. B. Apsara ◽  
P. Dayananda ◽  
C. N. Sowmyarani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Compression ◽  
Data Aggregation ◽  
Key Management ◽  
Data Gathering ◽  
Data Encryption ◽  
Wireless Sensor ◽  
Management Schemes ◽  
Encryption And Authentication

Wireless Sensor Networks (WSNs) is a fast-emerging technology which has become an integral part of the research. WSNs have various applications covering military, environment monitoring, health care, surveillance, national security, etc. Due to the inherent nature of wireless communication, such types of networks are more vulnerable to security attacks, and the authentication and confidentiality of wireless networks are much more critical. WSNs needs include efficient clustering methods, data aggregation methods, data compression methods, data encryption and authentication methods, and data gathering methods. WSNs are more vulnerable to attacks due to their ad hoc nature, so the design of a good key management scheme to provide security is necessary. In this paper, different methods of clustering, data aggregation, data compression, data encryption and authentication, and data gathering are analyzed. A survey is conducted on the key management schemes of WSNs.

scholarly journals EECDA: Energy Efficient Clustering and Data Aggregation Protocol for Heterogeneous Wireless Sensor Networks

2011 ◽  
Vol 6 (1) ◽  
pp. 113 ◽  
Author(s):  
Dilip Kumar ◽  
Trilok C. Aseri ◽  
R.B. Patel
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

In recent years, energy efficiency and data gathering is a major concern in many applications of Wireless Sensor Networks (WSNs). One of the important issues in WSNs is how to save the energy consumption for prolonging the network lifetime. For this purpose, many novel innovative techniques are required to improve the energy efficiency and lifetime of the network. In this paper, we propose a novel Energy Efficient Clustering and Data Aggregation (EECDA) protocol for the heterogeneous WSNs which combines the ideas of energy efficient cluster based routing and data aggregation to achieve a better performance in terms of lifetime and stability. EECDA protocol includes a novel cluster head election technique and a path would be selected with maximum sum of energy residues for data transmission instead of the path with minimum energy consumption. Simulation results show that EECDA balances the energy consumption and prolongs the network lifetime by a factor of 51%, 35% and 10% when compared with Low-Energy Adaptive Clustering Hierarchy (LEACH), Energy Efficient Hierarchical Clustering Algorithm (EEHCA) and Effective Data Gathering Algorithm (EDGA), respectively.

Data Aggregation and Data Gathering

2013 ◽  
pp. 41-58
Author(s):  
Lalit Awasthi ◽  
Siddhartha Chauhan
Keyword(s):  
Data Aggregation ◽  
Data Gathering

scholarly journals Working Capital Management in AVR Manufacturers Pvt Ltd, Chennai

2019 ◽  
Vol 8 (2S8) ◽  
pp. 143-147
Keyword(s):  
Trend Analysis ◽  
Data Aggregation ◽  
Data Gathering ◽  
Annual Reports ◽  
Ratio Analysis ◽  
Capital Management ◽  
Working Capital ◽  
Working Capital Management ◽  
Working Cycle ◽  
Points Of Interest

This endeavor deals with the "A Study on Working Capital Management with reference to AVR Manufacturers". Working Capital Management is stressed over the issues that develop while attempting to manage the present assets, the present liabilities and the cover relationship that exist between them. The target of Working Capital Management is to manage the affiliation's present assets and current liabilities in such way that the pleasing level of Working Capital is referenced. The present assets should be tremendous enough to cover its present liabilities in order to ensure a reasonable edge of the security. [1],[ 3],[5] The examination of Working Capital relies upon instruments like Trend Analysis, Ratio Analysis, Working Capital impact, working cycle, etc. Further the examination relies upon latest 5 years Annual Reports of AVR Manufacturers. Besides, even factors like contender's assessment, industry examination were not considered while setting up this errand. For this assessment the discretionary data gathering method is used. The data aggregation was away for examination of Working Capital organization of the association. There is a necessity for Working Capital as present points of interest for plan with the issue rising out of nonattendance of speedy affirmation of cash against items sold. Thusly satisfactory Working Capital is critical to help arrangements activity. This examination has a bit of the limitations like obliged data, confined period, compelled area and the term of the assessment is low. [2 ],[ 4],[6]

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