scholarly journals MIDAS: A Data Aggregation Scheduling Scheme for Variable Aggregation Rate WSNs

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Jun Long ◽  
An He ◽  
Jinhuan Zhang ◽  
Hao Zhang
Keyword(s):  
Network Lifetime ◽  
Data Aggregation ◽  
Time Slot ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Rate Model ◽  
Aggregation Rate ◽  
Slot Scheduling ◽  
Data Aggregation Scheduling ◽  
Variable Aggregation

Data aggregation scheduling for variable aggregation rate model has wide application and should take network lifetime and energy efficiency into consideration. In this paper, the time-slot scheduling problem for the variable aggregation rate model is presented, and a time-slot scheduling integrating consideration of minimizing the energy consumption named Makeup Integer based Data Aggregation Scheduling (MIDAS) is proposed. The proposed MIDAS scheme integrates two core phases, namely, data aggregation set construction and aggregation set based scheduling algorithm. The key idea of MIDAS is to minimize the number of receiving and sending data packets in hotspot and to reduce the number of aggregated packets in network for better scheduling performance in network lifetime. Furthermore, it is also essential to increase energy utilization efficiency of the nodes in the middle layer by exploiting the remaining energy of peripheral nodes. A series of experiments are simulated to demonstrate that the proposed scheme has significantly increased the network lifetime and the energy utilization efficiency under the different aggregation rates and different network scales. Comparing with the SDAS, the lifetime can be increased by as much as 25%. The energy utilization efficiency can be improved by as much as 30%.

scholarly journals A Survey on Various Clustering Algorithms in WSN for Optimal Energy Utilisation

2021 ◽  
pp. 712-720
Author(s):  
Madhuri N. Khuspare ◽  
Dr. Awani S. Khobragade
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Clustering Algorithms ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Sensor ◽  
Related Data

Wireless sensor networks comprise of an expansive number of distributed sensor gadgets, which are associated and composed through multi-hop steering. Because of the presence of related data and excess in measuring data, data messages can be joined and converged by performing data aggregation work in the steering procedure. To diminish energy utilization is a noteworthy enhancement target of data aggregation approaches, which can be accomplished by diminishing the mandatory correspondence load of steering. To improvise the network lifetime as much as possible in Wireless Sensor Networks (WSNs) the ways for data move are picked in a way that the aggregate energy used along the way is limited. To help high adaptability and better data aggregation, sensor nodes are routinely collected into disjoint, non-covering subsets called clusters. Clusters make various leveled WSNs which consolidate proficient use of constrained assets of sensor nodes and in this manner broadens network lifetime. The objective of this paper is to demonstrate a forefront survey on clustering calculations announced in the writing of WSNs. This paper presents different energy effective clustering calculations in WSNs. From the hypothetical level, an energy show is proposed to approve the advantages of data aggregation on energy utilization. The key parameters which may affect the aggregation execution are additionally examined.

scholarly journals Delay-Aware Reverse Approach for Data Aggregation Scheduling in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4511 ◽  
Author(s):  
Dung T. Nguyen ◽  
Duc-Tai Le ◽  
Moonseong Kim ◽  
Hyunseung Choo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Time Slot ◽  
Wireless Sensor ◽  
Node Degree ◽  
Dense Networks ◽  
Number Of Children ◽  
Minimum Latency ◽  
Data Aggregation Scheduling

Many time-sensitive applications require data to be aggregated from wireless sensor networks with minimum latency. However, the minimum latency aggregation scheduling problem has not been optimally solved due to its NP-hardness. Most existing ideas rely on local information (e.g., node degree, number of children) to organize the schedule order, hence results in solutions that might be far from optimal. In this work, we propose RADAS: a delay-aware Reverse Approach for Data Aggregation Scheduling that determines the transmissions sequence of sensors in a reverse order. Specifically, RADAS iteratively finds the transmissions starting from the last time slot, in which the last sender delivers data to the sink, down to the first time slot, when the data aggregation begins. In each time slot, RADAS intends to maximize the number of concurrent transmissions, while giving higher priority to the sender with potentially higher aggregation delay. Scheduling such high-priority sender first would benefit the maximum selections in subsequent time slots and eventually shorten the schedule length. Simulation results show that our proposed algorithm dominates the existing state-of-the-art schemes, especially in large and dense networks, and offers up to 30% delay reduction.

Resource Efficient Deployment and Data Aggregation in Pervasive IoT Applications (Smart Agriculture)

2020 ◽  
Vol 13 ◽  
Author(s):  
Saniya Zahoor ◽  
Roohie Naaz
Keyword(s):  
Network Lifetime ◽  
Data Aggregation ◽  
Heterogeneous Network ◽  
Processing Time ◽  
Energy Utilization ◽  
Node Deployment ◽  
Iot Applications ◽  
Use Of Resources ◽  
Aggregation Techniques ◽  
Smart Agriculture

Aims: Internet of Things (IoT) is the evolution of the Internet designed to sense, collect, analyze and distribute the data via IoT devices that form its core component. An important aspect of pervasive IoT applications is its resourceconstrained devices. Most of the real-time Edge-IoT applications generate huge amount of data, which adds to the resource consumption in these devices. To save resources in such applications, efficient node deployment and data aggregation techniques can be used. This paper presents design and modeling of node deployment and data aggregation in Edge-IoT applications along with the homogeneous and heterogeneous network scenarios for smart agriculture. Objectives: To save resources in such applications, efficient node deployment and data aggregation techniques can be used. This paper presents design and modeling of node deployment and data aggregation in Edge-IoT applications along with the homogeneous and heterogeneous network scenarios for smart agriculture Methods: For heterogeneous scenarios, we propose a clustering approach, Superior Aggregator Resource Efficient Clustering (SAREC) to address the resource constraints in pervasive Edge-IoT applications. The comparison of homogeneous and heterogeneous networks is based on LEACH and SAREC protocols respectively. Results: The results show SAREC is 25% more efficient in energy utilization and network lifetime than LEACH. The results also show SAREC is more efficient in terms of storage and processing time as compared to LEACH. Conclusion: Node deployment is an important aspect in determining the architecture, which plays an important role in resource management in pervasive applications of IoT. The IoT nodes are distributed in a selected geographical location and the topology of the network is pre-decided to form an Edge-IoT network. In such environment, the nodes are deployed to sense, aggregate and analyze the data. This paper presents pervasive Edge-IoT network along with the mathematical modeling consisting of deployment and the aggregation models. An Edge-IoT network for smart agriculture has been deployed and analysis of resource utilization has been performed in homogeneous and heterogeneous scenarios of network. The resource limitations in pervasive IoT network motivated us to develop a SAREC approach for such EdgeIoT applications that optimizes the use of resources. The comparison of proposed SAREC protocol is done with respect to LEACH protocol on the basis of energy, network lifetime, number of alive nodes, storage and processing time. The results shows SAREC protocol is 25% more efficient in energy utilization and network lifetime than LEACH. It is also evident from the results that the SAREC is more efficient in terms of storage and processing time as compared to LEACH.

Regional integrated energy system schemes selection based on risk expectation and Mahalanobis-Taguchi system

2021 ◽  
pp. 1-18
Author(s):  
Jiahang Yuan ◽  
Yun Li ◽  
Xinggang Luo ◽  
Lingfei Li ◽  
Zhongliang Zhang ◽  
...  
Keyword(s):  
Energy Demand ◽  
Choquet Integral ◽  
Subjective Evaluation ◽  
Risk Attitude ◽  
Energy System ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Energy Structure ◽  
Fuzzy Measures ◽  
Integrated Energy System

Regional integrated energy system (RIES) provides a platform for coupling utilization of multi-energy and makes various energy demand from client possible. The suitable RIES composition scheme will upgrade energy structure and improve integrated energy utilization efficiency. Based on a RIES construction project in Jiangsu province, this paper proposes a new multi criteria decision-making (MCDM) method for the selection of RIES schemes. Because that subjective evaluation on RIES schemes benefit under criteria has uncertainty and hesitancy, intuitionistic trapezoidal fuzzy number (ITFN) which has the better capability to model ill-known quantities is presented. In consideration of risk attitude and interdependency of criteria, a new decision model with risk coefficients, Mahalanobis-Taguchi system and Choquet integral is proposed. Firstly, the decision matrices given by experts are normalized, and then are transformed to minimum expectation matrices according to different risk coefficients. Secondly, the weights of criteria from different experts are calculated by Mahalanobis-Taguchi system. Mobius transformation coefficients based on interaction degree are to calculate 2-order additive fuzzy measures, and then the comprehensive weights of criteria are obtained by fuzzy measures and Choquet integral. Thirdly, based on group decision consensus requirement, the weights of experts are obtained by the maximum entropy and grey correlation. Fourthly, the minimum expectation matrices are aggregated by the intuitionistic trapezoidal fuzzy Bonferroni mean operator. Thus, the ranking result according to the comparison rules using the minimum expectation and the maximum expectation is obtained. Finally, an illustrative example is taken in the present study to make the proposed method comprehensible.

Evaluation of Energy Efficiency for a CCHP System With Available Microturbine

2007 ◽  
Author(s):  
H. X. Liang ◽  
Q. W. Wang
Keyword(s):  
Gas Turbine ◽  
Waste Heat ◽  
Energy System ◽  
Primary Energy ◽  
Economic Benefits ◽  
Optimal Operation ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Energetic Efficiency ◽  
Efficiency Evaluation

This paper deals with the problem of energy utilization efficiency evaluation of a microturbine system for Combined Cooling, Heating and Power production (CCHP). The CCHP system integrates power generation, cooling and heating, which is a type of total energy system on the basis of energy cascade utilization principle, and has a large potential of energy saving and economical efficiency. A typical CCHP system has several options to fulfill energy requirements of its application, the electrical energy can be produced by a gas turbine, the heat can be generated by the waste heat of a gas turbine, and the cooling load can be satisfied by an absorption chiller driven by the waste heat of a gas turbine. The energy problem of the CCHP system is so large and complex that the existing engineering cannot provide satisfactory solutions. The decisive values for energetic efficiency evaluation of such systems are the primary energy generation cost. In this paper, in order to reveal internal essence of CCHP, we have analyzed typical CCHP systems and compared them with individual systems. The optimal operation of this system is dependent upon load conditions to be satisfied. The results indicate that CCHP brings 38.7 percent decrease in energy consumption comparing with the individual systems. A CCHP system saves fuel resources and has the assurance of economic benefits. Moreover, two basic CCHP models are presented for determining the optimum energy combination for the CCHP system with 100kW microturbine, and the more practical performances of various units are introduced, then Primary Energy Ratio (PER) and exergy efficiency (α) of various types and sizes systems are analyzed. Through exergy comparison performed for two kinds of CCHP systems, we have identified the essential principle for high performance of the CCHP system, and consequently pointed out the promising features for further development.

Nanowire-based zinc-doped tin oxide microtubes for enhanced solar energy utilization efficiency

2017 ◽  
Vol 43 (9) ◽  
pp. 6822-6830 ◽  
Author(s):  
Wutao Mao ◽  
Zhengdao Li ◽  
Keyan Bao ◽  
Kaijun Zhang ◽  
Weibo Wang ◽  
...  
Keyword(s):  
Solar Energy ◽  
Tin Oxide ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Solar Energy Utilization
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