Research on Energy-Saving Strategy for Wireless Sensor Networks

2010 ◽  
Vol 159 ◽  
pp. 733-738 ◽  
Author(s):  
Yuan Yuan Li
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Saving ◽  
Technology Use ◽  
Topology Control ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Single Node ◽  
Save Energy

The wireless sensor networks have been extensively deployed and researched. One of the major issues in wireless sensor networks is the energy consumption program. In this paper, we analyzed the development status of wireless sensor networks and the problems,while proposed the network structure and energy model,then we discussed the energy saving strategies for wireless sensor networks from four aspects:First analysis the component of WSN protocol stack and the energy consumption;Second,we study the energy-saving strategy for a single node from the computing subsystem and the communication subsystem,and we introduce a new long-sleeping status to save energy through using Flag mark.Third is the energy-saving optimization strategy based on communication protocol which mainly discuss from MAC and routing protocols.Last,we discuss the topology control strategy for energy-saving and point out the importance of topology control technology. Use these strategies, we can significantly reduce the energy consumption of wireless sensor networks and extend the network life-cycle.

An Energy-Balance Based Distributed Topology Control Algorithm for Wireless Sensor Networks

2012 ◽  
Vol 490-495 ◽  
pp. 1392-1396 ◽  
Author(s):  
Chu Hang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Topology Control ◽  
Control Algorithm ◽  
Path Loss ◽  
Network Connectivity ◽  
Premature Death ◽  
Residual Energy ◽  
Wireless Sensor

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.

An Efficient Sleeping Scheduling for Save Energy Consumption in Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 2288-2293
Author(s):  
Shu Guang Jia ◽  
Li Peng Lu ◽  
Ling Dong Su ◽  
Gui Lan Xing ◽  
Ming Yue Zhai
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grid ◽  
Round Robin ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Active Sensors ◽  
Save Energy ◽  
Battery Energy

Smart grid has become one hot topic at home and abroad in recent years. Wireless Sensor Networks (WSNs) has applied to lots of fields of smart grid, such as monitoring and controlling. We should ensure that there are enough active sensors to satisfy the service request. But, the sensor nodes have limited battery energy, so, how to reduce energy consumption in WSNs is a key challenging. Based on this problem, we propose a sleeping scheduling model. In this model, firstly, the sensor nodes round robin is used to let as little as possible active nodes while all the targets in the power grid are monitored; Secondly, for removing the redundant active nodes, the sensor nodes round robin is further optimized. Simulation result indicates that this sleep mechanism can save the energy consumption of every sensor node.

How much energy saving does topology control offer for wireless sensor networks? – A practical study

2007 ◽  
Vol 30 (14-15) ◽  
pp. 2867-2879 ◽  
Author(s):  
Ajit Warrier ◽  
Sangjoon Park ◽  
Jeongki Min ◽  
Injong Rhee
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Saving ◽  
Topology Control ◽  
Wireless Sensor

scholarly journals Maximizing Network Lifetime Operator for Wireless Sensor Networks

2013 ◽  
Vol 4 (2) ◽  
pp. 267-272
Author(s):  
Dr. Deepali Virmani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Topology Control ◽  
Performance Metrics ◽  
Minimum Energy ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Minimum Energy Consumption

Optimizing and enhancing network lifetime with minimum energy consumption is the major challenge in field of wireless sensor networks. Existing techniques for optimizing network lifetime are based on exploiting node redundancy, adaptive radio transmission power and topology control. Topology control protocols have a significant impact on network lifetime, available energy and connectivity. In this paper we categorize sensor nodes as strong and weak nodes based on their residual energy as well as operational lifetime and propose a Maximizing Network lifetime Operator (MLTO) that defines cluster based topology control mechanism to enhance network lifetime while guarantying the minimum energy consumption and minimum delay. Extensive simulations in Java-Simulator (J-Sim) show that our proposed operator outperforms the existing protocols in terms of various performance metrics life network lifetime, average delay and minimizes energy utilization.

scholarly journals Game Theory Based Construction Efficient Topology in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
M. J. Abbasi ◽  
Muhammad Shafie Bin Abd Latiff ◽  
Hassan Chizari ◽  
N. Fisal
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Topology Control ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Wireless Sensor ◽  
Noncooperative Game ◽  
Power Cost ◽  
Minimum Power

Topology control is one of the most important techniques used in wireless sensor networks; to some extent it can reduce energy consumption in which each node is capable of minimizing its transmission power level while preserving network connectivity. Reducing energy consumption has been addressed through different aspects till now. In this paper, we present a minimum spanning tree- (MST-) based algorithm, called noncooperative minimum spanning tree (NMST), for topology control in wireless multihop networks. In this algorithm, each node constructs its minimum power-cost spanning tree which is a tree and can connect the node with one hop away from its neighbor node in constructed topology. In addition we address the power-cost allocation problem when node acts selfishly. A class of strategies is proposed which construct minimum power-cost spanning tree such that the sum of the power-cost (as proxy of weight), at the same time, is a strong Nash equilibrium for a noncooperative game associated with the problem of efficient topology construction. Simulation results show that NMST can maximize the sensor network lifetimes.

scholarly journals An Efficient Data Collection Protocol Based on Multihop Routing and Single-Node Cooperation in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoqiang Zheng ◽  
Bing Li ◽  
Jishun Li ◽  
Huahong Ma ◽  
Baofeng Ji
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Data Transmission ◽  
Wireless Sensor ◽  
Single Node ◽  
Multihop Routing ◽  
Efficient Data ◽  
Efficient Data Collection

Considering the constrained resource and energy in wireless sensor networks, an efficient data collection protocol named ESCDD which adopts the multihop routing technology and the single-node selection cooperative communication is proposed to make the communication protocol more simple and easy to realize for the large-scale multihop wireless sensor networks. ESCDD uses the greedy strategy and the control information based on RTS/CTS to select forwarding nodes. Then, the hops in the multihop data transmission are reduced. Based on the power control in physical layer and the control frame called CoTS in MAC layer, ESCDD chooses a single cooperative node to perform cooperative transmission. The receiving node adopts maximal ratio combining (MRC) to recover original data. The energy consumption per hop is reduced. Furthermore, the total energy consumption in data collection process is shared by more nodes and the network lifetime is extended. Compared with GeRaF, EERNFS, and REEFG protocol, the simulation results show that ESCDD can effectively reduce the average delay of multihop data transmission, improve the successful delivery rate of data packets, significantly save the energy consumption of network nodes, and make the energy consumption more balanced.

Energy saving algorithm and simulation test in wireless sensor networks

2021 ◽  
pp. 1-12
Author(s):  
Lv Feng
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Saving ◽  
Mobile Sink ◽  
Base Station ◽  
Wireless Sensor ◽  
Data Forwarding ◽  
Multi Objective Programming ◽  
Saving Algorithm

In recent years, scientists have begun to introduce dynamic elements into wireless networks. With the introduction of mobile sink node, the phenomenon of “hot node” and “energy hole” can be effectively avoided, so as to realize more network connection and improve network flexibility. Therefore, it is imperative to design energy-saving algorithm with popular sink code. In this paper, a multi hop data forwarding algorithm is proposed for solar powered wireless sensor networks. The algorithm divides the monitoring area of the network and the communication area of the node. Through the sensor node, the next hop node is selected from the appropriate area, thus forming the path from the data source point to the base station. At the same time, in order to reduce the energy consumption and delay in the network, a multi-objective programming model of the next hop data forwarding node is established. The reasonable area of static and dynamic area is calculated by mathematical analysis. Finally, the paper calculates the network’s life cycle, energy consumption and transmission time, and compares the static sink with the network using only mobile sink.

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