scholarly journals Strategies to Extend the Network Life Time of MWSN with SelfOrganization Clustering

2015 ◽  
Vol 8 (2) ◽  
pp. 61-70
Author(s):  
Sun-Young Park
Keyword(s):  
Life Time ◽  
Network Life Time

scholarly journals The Improvement of LEACH Algorithm in Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 46 ◽  
Author(s):  
Shujuan Dong ◽  
Cong Li
Keyword(s):  
Routing Algorithm ◽  
Critical Evaluation ◽  
Life Time ◽  
Correlated Data ◽  
Sensor Nodes ◽  
Time Simulation ◽  
Leach Protocol ◽  
Frame Work ◽  
Network Life Time ◽  
Almost All

This paper covers a novel routing algorithm called Multi-Group based LEACH (MG-LEACH) that has been utilized the redundant deployed sensor nodes to improve the network life time. It has been suppressing the correlated data gathered by the sensor nodes by monitoring the similar event. Thus reduces not only the data transmission inside the clusters but also conserve the energy of deployed sensor nodes consequently improve the overall network lifetime. This is a simple idea that has been implemented over LEACH protocol however it is valid for almost all clustering based routing algorithms/protocols specially those variants based upon frame work of LEACH. The proposed routing algorithm has been simulated using MATLAB to verify the efficiency in enhancing network life time. A critical evaluation of routing algorithm is conducted to determine the relevance and applicability in increasing network life time. Simulation results confirmed that it has performed better than LEACH and enhanced network life time up to approximately 90%.

scholarly journals Study of Wireless Sensor Network Location Algorithm and Data Collection Protocol

2016 ◽  
Vol 12 (10) ◽  
pp. 70 ◽  
Author(s):  
Weimin Han ◽  
Shijun Li ◽  
Weidong Li
Keyword(s):  
Data Collection ◽  
Cluster Head ◽  
Life Time ◽  
Network Location ◽  
Specific Analysis ◽  
Collection Data ◽  
Location Algorithm ◽  
Network Life Time ◽  
Zone Division ◽  
Meaningful Event

<p style="margin: 0in 0in 10pt;"><span style="font-size: small;"><span style="font-family: Times New Roman;"><span style="-ms-layout-grid-mode: line;">It is deduced that the network life time is inversely proportional to the zone area of the collection data that each sink is responsible for. That is to say, when the zone area in the charge of a sink is smaller, the average load of nodes distributed in this area and the energy consumption are smaller, while the network life time is longer. MSGP protocol is proposed, with several round cluster head candidate zones, fixed member zones and public zones being delimited to make approximately uniform clustering. The cluster head is responsible for collecting a meaningful event in the cluster, making data fusion and then forwarding it to sink. Multi-sinks move according to the zone division rules and the rule of free movement. Specific analysis is made from three aspects of data direction, single round data collection of sink, and network life time</span>.</span></span></p>

Study on Improving the Network Life Time Maximazation for Wireless Sensor Network using Cross Layer Approach

2016 ◽  
Vol 6 (6) ◽  
pp. 3080 ◽  
Author(s):  
Rajiv R Bhandari ◽  
K Rajasekhar
Keyword(s):  
Energy Consumption ◽  
Scheduling Algorithm ◽  
Routing Algorithm ◽  
Life Time ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cross Layer ◽  
Main Task ◽  
Network Life Time

<p>In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer &amp; Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.</p>

scholarly journals A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network

2019 ◽  
Vol 15 (6) ◽  
pp. 155014771985823 ◽  
Author(s):  
Mohammad Z Masoud ◽  
Yousef Jaradat ◽  
Ismael Jannoud ◽  
Mustafa A Al Sibahee
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Life Time ◽  
Wireless Sensor ◽  
Sink Node ◽  
Hybrid Clustering ◽  
Detection Process ◽  
Network Life Time ◽  
Hole Detection

In this work, a new hybrid clustering routing protocol is proposed to prolong network life time through detecting holes and edges nodes. The detection process attempts to generate a connected graph without any isolated nodes or clusters that have no connection with the sink node. To this end, soft clustering/estimation maximization with graph metrics, PageRank, node degree, and local cluster coefficient, has been utilized. Holes and edges detection process is performed by the sink node to reduce energy consumption of wireless sensor network nodes. The clustering process is dynamic among sensor nodes. Hybrid clustering routing protocol–hole detection converts the network into a number of rings to overcome transmission distances. We compared hybrid clustering routing protocol–hole detection with four different protocols. The accuracy of detection reached 98%. Moreover, network life time has prolonged 10%. Finally, hybrid clustering routing protocol–hole detection has eliminated the disconnectivity in the network for more than 80% of network life time.

Network Life Time Prolonged Routing by Distributed Load Balancing

2013 ◽  
Vol 003 (002) ◽  
pp. 75-78
Author(s):  
T. Parameswaran ◽  
◽  
C. Palanisamy ◽  
C.Maria Nancy ◽  
◽  
...  
Keyword(s):  
Load Balancing ◽  
Life Time ◽  
Distributed Load ◽  
Network Life Time
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