Communication/computation trade-offs in wireless sensor networks: Comparing network-level and node-level strategies

2014 ◽  
Author(s):  
Huseyin Ugur Yildiz ◽  
Kemal Bicakci ◽  
Bulent Tavli
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Node Level ◽  
Trade Offs

scholarly journals Improved Version of Secure Watermarking LEACH: R-Watermarking LEACH

2019 ◽  
Vol 8 (6) ◽  
pp. 4030-4034
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Member ◽  
Node Level ◽  
Head Level

As wireless sensor networks (WSN) deployment are broadly spreading in various fields. Therefore security becomes a vital issue. Most of the researcher's attention is only on utility of sensor network and possibility of sensor network rather than security. In our work we do focus on security for that we consider privacy and integrity the main issues of sensor networks related to security. In WSNs, various schemes have previously introduced by various researchers to manage security, but few algorithm have been considered the privacy and integrity at both sensor nodes cluster member and CH nodes. In our work we have present a secure algorithm to control integrity and privacy at both node level and cluster head level in WSN. In our protocol we have control the integrity by watermarking technique and privacy is managed using encryption technique.

MONet

2017 ◽  
Vol 13 (4) ◽  
pp. 345-369
Author(s):  
Kamel Barka ◽  
Azeddine Bilami ◽  
Samir Gourdache
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Power Efficiency ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Trade Offs

Purpose The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet). Design/methodology/approach In MONet, the middleware level of each network node autonomously adjusts its routing parameters according to dynamic network conditions and seeks optimal trade-offs among performance objectives for a balance of its global performance. MONet controls the cooperation between agents (network nodes) while varying transmission paths to reduce and distribute power consumption equitably on all the sensor nodes of network. MONet-runtime uses a modified TinyDDS middleware platform. Findings Simulation results confirm that MONet allows power efficiency to WSN nodes while adapting their sleep periods and self-heal false-positive sensor data. Originality/value The framework implementation is lightweight and efficient enough to run on resource-limited nodes such as sensor nodes.

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