Investigation of data dissemination techniques for opportunistic networks

An opportunistic network is an infrastructure-less peer to peer network, created between devices that are mobile and wireless enabled. The links between devices are dynamic and often short-lived. Therefore, disseminating data from a source to recipients with a quality of service guarantee and efficiency is a very challenging problem. Furthermore, the interactions between devices are based on opportunity and are dependent on the devices mobility, which have extreme diverse patterns. The aim of this thesis is to investigate dissemination of data in opportunistic networks. In particular two conflicting objectives are studied: minimising the overhead costs and maximising the information coverage over time. We also take into account the effects of mobility. Extensive computer simulation is developed to explore models for information dissemination and mobility. On top of existing mobility models (i.e. Random Walk, Random, Waypoint and Gauss Markov) a hybrid model is derived from the Random Waypoint and Gauss Markov mobility models. The effect on mobility model on dissemination performance is found to be highly significant. This is based on sensitivity analysis on mobility and node density. We first consider different baseline push techniques for data dissemination. We propose four different push techniques, namely Pure Push, Greedy, L-Push and Spray and Relay to analyse the impact of different push techniques to the information dissemination performances. The results present different trade-offs between objectives. As a strategy to manage overheads, we consider controlling to which nodes information is pushed to by establishing a social network between devices. A logical social network can be built between mobile devices if they repeatedly see each other, and can be defined in different ways. This is important because it shows how content may potentially flow to devices. We explore the effects of mobility for different definitions of the social network. This shows how different local criteria for defining links in a social network lead to different social structures. Finally we consider the effect of combining the social structure and intelligent push techniques to further improve the data dissemination performance in opportunistic networks. We discover that prioritising pushing over a social network is able to minimise the overhead costs but it introduces a dissemination delay.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Investigation of data dissemination techniques for opportunistic networks

An opportunistic network is an infrastructure-less peer to peer network, created between devices that are mobile and wireless enabled. The links between devices are dynamic and often short-lived. Therefore, disseminating data from a source to recipients with a quality of service guarantee and efficiency is a very challenging problem. Furthermore, the interactions between devices are based on opportunity and are dependent on the devices mobility, which have extreme diverse patterns. The aim of this thesis is to investigate dissemination of data in opportunistic networks. In particular two conflicting objectives are studied: minimising the overhead costs and maximising the information coverage over time. We also take into account the effects of mobility. Extensive computer simulation is developed to explore models for information dissemination and mobility. On top of existing mobility models (i.e. Random Walk, Random, Waypoint and Gauss Markov) a hybrid model is derived from the Random Waypoint and Gauss Markov mobility models. The effect on mobility model on dissemination performance is found to be highly significant. This is based on sensitivity analysis on mobility and node density. We first consider different baseline push techniques for data dissemination. We propose four different push techniques, namely Pure Push, Greedy, L-Push and Spray and Relay to analyse the impact of different push techniques to the information dissemination performances. The results present different trade-offs between objectives. As a strategy to manage overheads, we consider controlling to which nodes information is pushed to by establishing a social network between devices. A logical social network can be built between mobile devices if they repeatedly see each other, and can be defined in different ways. This is important because it shows how content may potentially flow to devices. We explore the effects of mobility for different definitions of the social network. This shows how different local criteria for defining links in a social network lead to different social structures. Finally we consider the effect of combining the social structure and intelligent push techniques to further improve the data dissemination performance in opportunistic networks. We discover that prioritising pushing over a social network is able to minimise the overhead costs but it introduces a dissemination delay.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Investigation of data dissemination techniques for opportunistic networks

An opportunistic network is an infrastructure-less peer to peer network, created between devices that are mobile and wireless enabled. The links between devices are dynamic and often short-lived. Therefore, disseminating data from a source to recipients with a quality of service guarantee and efficiency is a very challenging problem. Furthermore, the interactions between devices are based on opportunity and are dependent on the devices mobility, which have extreme diverse patterns. The aim of this thesis is to investigate dissemination of data in opportunistic networks. In particular two conflicting objectives are studied: minimising the overhead costs and maximising the information coverage over time. We also take into account the effects of mobility. Extensive computer simulation is developed to explore models for information dissemination and mobility. On top of existing mobility models (i.e. Random Walk, Random, Waypoint and Gauss Markov) a hybrid model is derived from the Random Waypoint and Gauss Markov mobility models. The effect on mobility model on dissemination performance is found to be highly significant. This is based on sensitivity analysis on mobility and node density. We first consider different baseline push techniques for data dissemination. We propose four different push techniques, namely Pure Push, Greedy, L-Push and Spray and Relay to analyse the impact of different push techniques to the information dissemination performances. The results present different trade-offs between objectives. As a strategy to manage overheads, we consider controlling to which nodes information is pushed to by establishing a social network between devices. A logical social network can be built between mobile devices if they repeatedly see each other, and can be defined in different ways. This is important because it shows how content may potentially flow to devices. We explore the effects of mobility for different definitions of the social network. This shows how different local criteria for defining links in a social network lead to different social structures. Finally we consider the effect of combining the social structure and intelligent push techniques to further improve the data dissemination performance in opportunistic networks. We discover that prioritising pushing over a social network is able to minimise the overhead costs but it introduces a dissemination delay