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 fils
Index. 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.....................................................................................................................51
Côte titre :	MAI/0147
En ligne :	https://drive.google.com/file/d/1tWQRWtdeZ9rLfxf5cojdRogZVyc_qZOC/view?usp=shari [...]
Format de la ressource électronique :	pdf

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 fils
Index. 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.....................................................................................................................51
Côte titre :	MAI/0147
En ligne :	https://drive.google.com/file/d/1tWQRWtdeZ9rLfxf5cojdRogZVyc_qZOC/view?usp=shari [...]
Format de la ressource électronique :	pdf