Towards Opportunistic Data Dissemination in Mobile Phone Sensor Networks

Recently, there has been a growing interest within the research community in developing opportunistic routing protocols. Many schemes have been proposed; however, they differ greatly in assumptions and in type of network for which they are evaluated. As a result, researchers have an ambiguous understanding of how these schemes compare against each other in their specific applications. To investigate the performance of existing opportunistic routing algorithms in realistic scenarios, we propose a heterogeneous architecture including fixed infrastructure, mobile infrastructure, and mobile nodes. The proposed architecture focuses on how to utilize the available, low cost short-range radios of mobile phones for data gathering and dissemination. We also propose a new realistic mobility model and metrics. Existing opportunistic routing protocols are simulated and evaluated with the proposed heterogeneous architecture, mobility models, and transmission interfaces. Results show that some protocols suffer long time-to-live (TTL), while others suffer short TTL. We show that heterogeneous sensor network architectures need heterogeneous routing algorithms, such as a combination of Epidemic and Spray and Wait

Modelling Data Dissemination in Opportunistic Networks

In opportunistic networks data dissemination is an impor- tant, although not widely explored, topic. Since oppor- tunistic networks topologies are very challenged and un- stable, data-centric approaches are an interesting direction to pursue. Data should be proactively and cooperatively disseminated from sources towards possibly interested re- ceivers, as sources and receivers might not be aware of each other, and never get in touch directly. In this paper we con- sider a utility-based cooperative data dissemination system in which the utility of data is defined based on the social relationships between users. Specifically, we study the per- formance of this system through an analytical model. Our model allows us to completely characterise the data dissem- ination process, as it describes both its stationary and tran- sient regimes. After validating the model, we study the sys- tem\u27s behaviour with respect to key parameters such as the definition of the data utility function, the initial data allo- cation on nodes, the number of users in the system, and the data popularity

Heterogeneous epidemic model for assessing data dissemination in opportunistic networks

In this paper we investigate a susceptible-infected-susceptible (SIS) epidemic model describing data dissemination in opportunistic networks with heterogeneous setting of transmission parameters. We obtained the estimation of the final epidemic size assuming that amount of data transferred between network nodes possesses a Pareto distribution, implying scale-free properties. In this context, more heterogeneity in susceptibility means the less severe epidemic progression, and, on the contrary, more heterogeneity in infectivity leads to more severe epidemics -- assuming that the other parameter (either heterogeneity or susceptibility) stays fixed. The results are general enough and can be useful in general epidemic theory for estimating the epidemic progression for diseases with no significant acquired immunity -- in the cases where Pareto distribution holds

Collaborative data dissemination in opportunistic vehicular networks

Future opportunistic vehicular networks offers viable means for collaborative data dissemination by high-capacity device-to-device communication. This is a highly challenging problem because a) mobile data items are heterogeneous in size and lifetime; b) mobile users have different interests to different data; and c) dissemination participants have limited storages. We study collaborative data dissemination under these realistic opportunistic vehicular network conditions and formulate the optimal data dissemination as a submodular function maximisation problem with multiple linear storage constraints. We then propose a heuristic algorithm to solve this challenging problem, and provide its theoretical performance bound. The effectiveness of our approach is demonstrated through simulation using real vehicular traces

Opportunistic data dissemination in mobile phone sensor networks

Situated communication technologies in emergencies are subject to decay or fail because of their inadequate services. With the advances in tiny-sensor technologies and ubiquity of smart phones, public awareness on urgent situations can be raised in more efficient and distributed ways. We center on opportunistic data dissemination schemes where the objective is to provide an operability among sensing, communication, and data spread. Such mobile networks do not require end-to-end routes or servers; however connectivity and scalability issues may last forever without determinism. We have started implementing context-aware services to understand the mobile phone carriers’ characteristics and routines in order to increase the quality of service in our collaboration and dissemination objectives. We are currently working on real implementation of mobile ad hoc networks and routing algorithms. Besides, we simulate an urban city network with different scenarios and objectives to analyze the open research challenges

Total order in opportunistic networks

Opportunistic network applications are usually assumed to work only with unordered immutable messages, like photos, videos, or music files, while applications that depend on ordered or mutable messages, like chat or shared contents editing applications, are ignored. In this paper, we examine how total ordering can be achieved in an opportunistic network. By leveraging on existing dissemination and causal order algorithms, we propose a commutative replicated data type algorithm on the basis of Logoot for achieving total order without using tombstones in opportunistic networks where message delivery is not guaranteed by the routing layer. Our algorithm is designed to use the nature of the opportunistic network to reduce the metadata size compared to the original Logoot, and even to achieve in some cases higher hit rates compared to the dissemination algorithms when no order is enforced. Finally, we present the results of the experiments for the new algorithm by using an opportunistic network emulator, mobility traces, and Wikipedia pages.Peer ReviewedPostprint (author's final draft

Towards Opportunistic Data Dissemination in Mobile Phone Sensor Networks

Recently, there has been a growing interest within the research community in developing opportunistic routing protocols. Many schemes have been proposed; however, they differ greatly in assumptions and in type of network for which they are evaluated. As a result, researchers have an ambiguous understanding of how these schemes compare against each other in their specific applications. To investigate the performance of existing opportunistic routing algorithms in realistic scenarios, we propose a heterogeneous architecture including fixed infrastructure, mobile infrastructure, and mobile nodes. The proposed architecture focuses on how to utilize the available, low cost short-range radios of mobile phones for data gathering and dissemination. We also propose a new realistic mobility model and metrics. Existing opportunistic routing protocols are simulated and evaluated with the proposed heterogeneous architecture, mobility models, and transmission interfaces. Results show that some protocols suffer long time-to-live (TTL), while others suffer short TTL. We show that heterogeneous sensor network architectures need heterogeneous routing algorithms, such as a combination of Epidemic and Spray and Wait

Data dissemination in partially cooperative opportunistic networks

Wireless communication between mobile users has become more popular than ever in the last decade, leading to increasing demand for network infrastructure. The growing popularity of smartphones among mobile users, leads an alternative infrastructure-less networking paradigm known as opportunistic networks. In opportunistic networks, mobile nodes such as smartphones use the mobility of devices in addition to wireless forwarding between intermediate nodes to facilitate communication without requiring a simultaneous path between source and destination. Without guaranteed connectivity, the strategy for data delivery is a key research challenge for such networks. In this research, we present the design and evaluation of the Repository-based Data Dissemination (RDD) system, a communication system which does not rely on cooperation from mobile nodes but instead employs a small number of well-placed standalone fixed devices (named repositories) to facilitate data dissemination. To find the optimal location for their repositories, RDD employs knowledge of the mobility characteristics of mobile users. To evaluate RDD, a new mobility model “Human mobility model” has been designed, which was able to closely mimic the users’ real mobility, and proven by conducting a series of experiments compared with real mobility traces. Using this model, the performance of the RDD is evaluated using custom simulation. In comparison with epidemic routing, the results show that RDD is able to drastically reduce resource consumption, expressed in terms of message redundancy, while preserving the performance in terms of data object delivery