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Titre : Mobility modeling by swarm intelligence for WSN with mobile base station Type de document : texte imprimé Auteurs : Mouadna,sarra ; Djamila Mechta, Directeur de thèse Editeur : Setif:UFA Année de publication : 2016 Importance : 1 vol (59f.) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Réseaux
Systèmes Distribués
optimisation
bio inspiré
swarm
capteurs sans filsIndex. décimale : 004 Informatique Résumé : General Conclusion
Sink mobility is one of the most comprehensive trends for data gathering in sensor
networks .This way of information gathering has a prominent role in balancing the energy
consumption among sensor networks, culling the hotspots problem and thereby prolong the
network lifetime to a great extent.
A mobile sink protocol must take into account the characteristics of a sensor node as the
limitation of the energy source, the distance to each CH and latency to prolong the lifetime
of sensors in this network (WSN).
To achieve this goal, we proposed our protocol AFSA-MS based on mobile sink and using
bio-inspired method, the principal objective of our protocol is to find a quasi-optimal
position of sink that should be closer to the GHs that cover larger area (a large number of
sensors), as they trigger more sensors to report events and hence generate more data to be
transmitted to the sink node. The contributions of this work are summarized in the
following points
Changing the cluster‟s formation:
 Division of the network into a rectangular grids with the same size
 Determination of GH using two conditions (selects the node with high level of
energy and the nearest to the center of its grid to minimize the energy
consumption).
 Move the sink using the AFSA method with some of its different behaviors.
To validate the improvements made by our protocol, we used the network simulator NS2.
After a comparative study between LEACH-C and AFSA-MS, the simulation results
showed that AFSA-MS has better managing energy which maximize the network lifetime
compared to LEACH-C protocol and ensure a maximum delivered data to the sink, the
only weakness point of AFSA-MS is in the network lifetime in terms of First Node Die
(FND).
As a future work we will try to improve our proposed algorithm to find better results, by
trying to ameliorate the network lifetime in case of (FND) and the choice of the optimal
position (the perfect position) that the sink should move to it, to minimize the energy
consumed and extend more the network lifetime.Note de contenu : TABLE OF CONTENTS
General Introduction ...........................................................................................................1
CHAPTER 01 STATE OF THE ART...................................................................................3
SWARM INTELLIGENCE & SINK‟S MOBILITY IN WSN ................................................3
1.1 Introduction: ............................................................................................................4
1.2 Advantages of mobility in WSNs:...................................................................................4
1.3 Mobile sink (Base Station) in WSN: ...............................................................................5
1.3.1Types of mobility in WSN:.............................................................................................5
1.4 Moving strategies for mobile sink in WSN: ...............................................................5
1.4.1 Mobile Sink based Routing Protocol (MSRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network.............5
1.4.2 Bundling mobile base station and wireless energy transfer :Modeling and optimization …………………….6
1.4.3 WSN lifetime optimization through controlled sink mobility and packet buffering ....7
1.4.4 Efficient data collection in WSN using mobile sink:.................................................7
1.4.5 An Energy Aware Routing Design to Maximize Lifetime of a Wireless Sensor Network with a Mobile Base Station............9
1.4.6 Optimizing LEACH clustering algorithm with mobile Sink and rendezvous nodes..10
1.4.7 Controlled sink mobility for prolonging wireless sensor networks lifetime .............12
1.4.8 Mobile Data Collection in Wireless Sensor Networks Using Bounded Relay Hop ..13
1.5 Swarm intelligence and mobility in WSN: ....................................................................14
1.5.1 Genetic algorithm based length reduction of Mobile BS paths in WSNs:................14
1.5.2 Bio inspired method Digital Hormone Model (DHM) with mobile sink nodes in WSNs…………...........................16
1.5.3 Prolonging lifetime of wireless sensor networks with mobile base station using particle swarm optimization..................18
1.5.4 Ant Colony Optimization Algorithm for Lifetime Maximization in Wireless Sensor Network with Mobile Sink ..................19
1.5.5 A data gathering algorithm for a mobile sink in large scale sensor networks.........21
1.5.6 An artificial bee colony algorithm for data collection path planning in sparse wireless sensor networks................22
1.6 Conclusion:............................................................................................................24
CHAPTER 02 PROPOSED PROTOCOL AFSA-MS....................................................25
2.1 Introduction: .......................................................................................................26
2.2 Leach-c protocol:..........................................................................................................26
2.3 The LEACH-C implementation phases: ........................................................................26
2.4 Description of the proposed protocol.............................................................................27
2.4.1 The Network Model:.............................................................................................27
2.5 Conception of the proposed protocol:............................................................................28
2.5.1 Division of the network into Grids: .......................................................................29
2.5.2 Election phase of Grid-Head (GH): .......................................................................30
2.5.3 Construction of the TDMA-Schedule: ...................................................................31
2.5.4 Movement of the sink: ..........................................................................................31
2.6 Conclusion :........................................................................................................38
CHAPTER 03 SIMULATION AND RESULTS...................................................................40
3.1 Introduction ..............................................................................................................40
3.2 The development environment ......................................................................................40
3.3 Simulation parameters ..................................................................................................40
3.4 Performance Metrics:....................................................................................................41
3.5 Simulation with 100 nodes:...........................................................................................41
3.5.1 Comparison in terms of energy consumed:....................................................................42
3.5.2 Comparison in terms of the amount of data received by the sink: ..................................43
3.5.3 Comparison in terms of network lifetime: .....................................................................44
3.6 Simulation with 200 nodes:...........................................................................................45
3.6.1 Comparison in terms of energy consumed:....................................................................46
3.6.2 Comparison in terms of the amount of data received by the sink: ..................................47
3.6.3 Comparison in terms of network lifetime: .....................................................................48
3.7 Conclusion:............................................................................................................49
General Conclusion...........................................................................................................50
Bibliography.....................................................................................................................51Côte titre : MAI/0147 En ligne : https://drive.google.com/file/d/1tWQRWtdeZ9rLfxf5cojdRogZVyc_qZOC/view?usp=shari [...] Format de la ressource électronique : Mobility modeling by swarm intelligence for WSN with mobile base station [texte imprimé] / Mouadna,sarra ; Djamila Mechta, Directeur de thèse . - [S.l.] : Setif:UFA, 2016 . - 1 vol (59f.) ; 29 cm.
Langues : Anglais (eng)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Réseaux
Systèmes Distribués
optimisation
bio inspiré
swarm
capteurs sans filsIndex. décimale : 004 Informatique Résumé : General Conclusion
Sink mobility is one of the most comprehensive trends for data gathering in sensor
networks .This way of information gathering has a prominent role in balancing the energy
consumption among sensor networks, culling the hotspots problem and thereby prolong the
network lifetime to a great extent.
A mobile sink protocol must take into account the characteristics of a sensor node as the
limitation of the energy source, the distance to each CH and latency to prolong the lifetime
of sensors in this network (WSN).
To achieve this goal, we proposed our protocol AFSA-MS based on mobile sink and using
bio-inspired method, the principal objective of our protocol is to find a quasi-optimal
position of sink that should be closer to the GHs that cover larger area (a large number of
sensors), as they trigger more sensors to report events and hence generate more data to be
transmitted to the sink node. The contributions of this work are summarized in the
following points
Changing the cluster‟s formation:
 Division of the network into a rectangular grids with the same size
 Determination of GH using two conditions (selects the node with high level of
energy and the nearest to the center of its grid to minimize the energy
consumption).
 Move the sink using the AFSA method with some of its different behaviors.
To validate the improvements made by our protocol, we used the network simulator NS2.
After a comparative study between LEACH-C and AFSA-MS, the simulation results
showed that AFSA-MS has better managing energy which maximize the network lifetime
compared to LEACH-C protocol and ensure a maximum delivered data to the sink, the
only weakness point of AFSA-MS is in the network lifetime in terms of First Node Die
(FND).
As a future work we will try to improve our proposed algorithm to find better results, by
trying to ameliorate the network lifetime in case of (FND) and the choice of the optimal
position (the perfect position) that the sink should move to it, to minimize the energy
consumed and extend more the network lifetime.Note de contenu : TABLE OF CONTENTS
General Introduction ...........................................................................................................1
CHAPTER 01 STATE OF THE ART...................................................................................3
SWARM INTELLIGENCE & SINK‟S MOBILITY IN WSN ................................................3
1.1 Introduction: ............................................................................................................4
1.2 Advantages of mobility in WSNs:...................................................................................4
1.3 Mobile sink (Base Station) in WSN: ...............................................................................5
1.3.1Types of mobility in WSN:.............................................................................................5
1.4 Moving strategies for mobile sink in WSN: ...............................................................5
1.4.1 Mobile Sink based Routing Protocol (MSRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network.............5
1.4.2 Bundling mobile base station and wireless energy transfer :Modeling and optimization …………………….6
1.4.3 WSN lifetime optimization through controlled sink mobility and packet buffering ....7
1.4.4 Efficient data collection in WSN using mobile sink:.................................................7
1.4.5 An Energy Aware Routing Design to Maximize Lifetime of a Wireless Sensor Network with a Mobile Base Station............9
1.4.6 Optimizing LEACH clustering algorithm with mobile Sink and rendezvous nodes..10
1.4.7 Controlled sink mobility for prolonging wireless sensor networks lifetime .............12
1.4.8 Mobile Data Collection in Wireless Sensor Networks Using Bounded Relay Hop ..13
1.5 Swarm intelligence and mobility in WSN: ....................................................................14
1.5.1 Genetic algorithm based length reduction of Mobile BS paths in WSNs:................14
1.5.2 Bio inspired method Digital Hormone Model (DHM) with mobile sink nodes in WSNs…………...........................16
1.5.3 Prolonging lifetime of wireless sensor networks with mobile base station using particle swarm optimization..................18
1.5.4 Ant Colony Optimization Algorithm for Lifetime Maximization in Wireless Sensor Network with Mobile Sink ..................19
1.5.5 A data gathering algorithm for a mobile sink in large scale sensor networks.........21
1.5.6 An artificial bee colony algorithm for data collection path planning in sparse wireless sensor networks................22
1.6 Conclusion:............................................................................................................24
CHAPTER 02 PROPOSED PROTOCOL AFSA-MS....................................................25
2.1 Introduction: .......................................................................................................26
2.2 Leach-c protocol:..........................................................................................................26
2.3 The LEACH-C implementation phases: ........................................................................26
2.4 Description of the proposed protocol.............................................................................27
2.4.1 The Network Model:.............................................................................................27
2.5 Conception of the proposed protocol:............................................................................28
2.5.1 Division of the network into Grids: .......................................................................29
2.5.2 Election phase of Grid-Head (GH): .......................................................................30
2.5.3 Construction of the TDMA-Schedule: ...................................................................31
2.5.4 Movement of the sink: ..........................................................................................31
2.6 Conclusion :........................................................................................................38
CHAPTER 03 SIMULATION AND RESULTS...................................................................40
3.1 Introduction ..............................................................................................................40
3.2 The development environment ......................................................................................40
3.3 Simulation parameters ..................................................................................................40
3.4 Performance Metrics:....................................................................................................41
3.5 Simulation with 100 nodes:...........................................................................................41
3.5.1 Comparison in terms of energy consumed:....................................................................42
3.5.2 Comparison in terms of the amount of data received by the sink: ..................................43
3.5.3 Comparison in terms of network lifetime: .....................................................................44
3.6 Simulation with 200 nodes:...........................................................................................45
3.6.1 Comparison in terms of energy consumed:....................................................................46
3.6.2 Comparison in terms of the amount of data received by the sink: ..................................47
3.6.3 Comparison in terms of network lifetime: .....................................................................48
3.7 Conclusion:............................................................................................................49
General Conclusion...........................................................................................................50
Bibliography.....................................................................................................................51Côte titre : MAI/0147 En ligne : https://drive.google.com/file/d/1tWQRWtdeZ9rLfxf5cojdRogZVyc_qZOC/view?usp=shari [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0147 MAI/0147 Mémoire Bibliothéque des sciences Anglais Disponible
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