Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces

Advanced Protocols for Peer-to-Peer Data Transmission in Wireless Gigabit Networks

This thesis tackles problems on IEEE 802.11 MAC layer, network layer and application layer, to further push the performance of wireless P2P applications in a holistic way. It contributes to the better understanding and utilization of two major IEEE 802.11 MAC features, frame aggregation and block acknowledgement, to the design and implementation of opportunistic networks on off-the-shelf hardware and proposes a document exchange protocol, including document recommendation. First, this thesis contributes a measurement study of the A-MPDU frame aggregation behavior of IEEE 802.11n in a real-world, multi-hop, indoor mesh testbed. Furthermore, this thesis presents MPDU payload adaptation (MPA) to utilize A-MPDU subframes to increase the overall throughput under bad channel conditions. MPA adapts the size of MAC protocol data units to channel conditions, to increase the throughput and lower the delay in error-prone channels. The results suggest that under erroneous conditions throughput can be maximized by limiting the MPDU size. As second major contribution, this thesis introduces Neighborhood-aware OPPortunistic networking on Smartphones (NOPPoS). NOPPoS creates an opportunistic, pocket-switched network using current generation, off-the-shelf mobile devices. As main novel feature, NOPPoS is highly responsive to node mobility due to periodic, low-energy scans of its environment, using Bluetooth Low Energy advertisements. The last major contribution is the Neighborhood Document Sharing (NDS) protocol. NDS enables users to discover and retrieve arbitrary documents shared by other users in their proximity, i.e. in the communication range of their IEEE 802.11 interface. However, IEEE 802.11 connections are only used on-demand during file transfers and indexing of files in the proximity of the user. Simulations show that NDS interconnects over 90 \% of all devices in communication range. Finally, NDS is extended by the content recommendation system User Preference-based Probability Spreading (UPPS), a graph-based approach. It integrates user-item scoring into a graph-based tag-aware item recommender system. UPPS utilizes novel formulas for affinity and similarity scoring, taking into account user-item preference in the mass diffusion of the recommender system. The presented results show that UPPS is a significant improvement to previous approaches

LEVERAGING PEER-TO-PEER ENERGY SHARING FOR RESOURCE OPTIMIZATION IN MOBILE SOCIAL NETWORKS

Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of the another member) for the efficient utilization of scarce energy resources in the network. However, due to uncertain mobility and communication opportunities in the network, resource optimization in these opportunistic networks is very challenging. In this dissertation, we study energy utilization in three different applications in Mobile Social Networks and target to improve the energy efficiency in the network by benefiting from P2P energy sharing among the nodes. More specifi- xi cally, we look at the problems of (i) optimal energy usage and sharing between friendly nodes in order to reduce the burden of wall-based charging, (ii) optimal content and energy sharing when energy is considered as an incentive for carrying the content for other nodes, and (iii) energy balancing among nodes for prolonging the network lifetime. We have proposed various novel protocols for the corresponding applications and have shown that they outperform the state-of-the-art solutions and improve the energy efficiency in MSNs while the application requirements are satisfied