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A mobile ad-hoc network is an autonomous system of mobile routers that are self-organizing and completely decentralized with no requirements for dedicated infrastructure support. However, such infrastructure in terms of base stations is available in many popular areas already. These base stations often offer high-speed data connectivity to a wired network. In this paper, we describe an approach where a combination of infrastructure and ad hoc communication can be used to better manage the data needs of a mobile wireless device. In our approach, base stations track user mobility and determine data usage patterns of users passing by. Based on this, future data needs of a mobile device can be predicted. Base stations can collaborate (over the wired network) to identify other mobile devices with spare capacity whose routes intersect that of a needy device and use these carriers to transport data. When such a carrier meets the needy device, they can form ad hoc per-to-peer communities to transfer the carried data. We also present the motivation, architecture and design of NUMI, our framework for supporting combined infrastructure and ad hoc peer-to-peer computing and prototype application built on top of this framework.

We propose and evaluate a scalable position-publish and an accompanying routing protocol which is efficient despite operating with imperfect information regarding the destination's location. The traffic generated by our position-publish protocol fits within the transport capacity of large mobile ad hoc networks (MANETs) with constant communication bandwidth allocated for routing overhead, even as the network size increases. The routing protocol guarantees, with high probability, routes whose lengths are within a constant "stretch" factor of the shortest path from source to destination. The key idea underlying the scalability of the publish protocol is for each potential destination node to send location updates (with frequency decaying with distance) to a subset of network nodes, structured as annular regions around it (the natural approach of updating circular regions in distance-dependent fashion does not scale). The routing protocol must therefore account for the fact that the source and/or relay nodes may not have estimates of the destination's location (or may have stale estimates). Spatial and temporal scaling of protocol parameters are chosen so as to guarantee scalability, route reliability and route stretch, and these analytical design prescriptions are verified using simulations.

We propose and evaluate a scalable position-publish and an accompanying routing protocol which is efficient despite operating with imperfect information regarding the destination's location. The traffic generated by our position-publish protocol fits within the transport capacity of large mobile ad hoc networks (MANETs) with constant communication bandwidth allocated for routing overhead, even as the network size increases. The routing protocol guarantees, with high probability, routes whose lengths are within a constant "stretch" factor of the shortest path from source to destination. The key idea underlying the scalability of the publish protocol is for each potential destination node to send location updates (with frequency decaying with distance) to a subset of network nodes, structured as annular regions around it (the natural approach of updating circular regions in distance-dependent fashion does not scale). The routing protocol must therefore account for the fact that the source and/or relay nodes may not have estimates of the destination's location (or may have stale estimates). Spatial and temporal scaling of protocol parameters are chosen so as to guarantee scalability, route reliability and route stretch, and these analytical design prescriptions are verified using simulations.

In the context of this project, we worked on the development of a cross-layer resource management system over single hop and multihop Direct-Sequence Code Division Multiple Access (DS-CDMA) Visual Sensor Networks (VSNs). The target was the optimal determination and allocation of the source and channel coding rates and the power levels among the nodes of the considered network. For the efficient allocation of the nodes' transmission parameters, we applied various distortion-related criteria, drawing inspiration from game theory as well, and investigated fairness and efficiency under different perspectives for each of them. Computational intelligence optimization algorithms and reinforcement learning techniques were applied in order to solve the resulting optimization problems. All the solutions provided by the examined schemes were Pareto-optimal and thus, the choice about the most fair and efficient scheme is problem-dependent. Some of the approaches that were taken into account for further improving the end-to-end video distortion of a wireless multiple-access VSN included the time scheduling of transmitting nodes for interference mitigation, the optimal Instantaneous Decoding Refresh (IDR) frame placement during encoding, the content-based node prioritization, and the weighted bi-objective optimization for measuring the trade-off between video quality and consumed transmission power. The evaluation of all proposed approaches showed that enhanced end-to-end video quality can be achieved, by keeping power consumption at reasonable levels, when compared to the case of assigning equal values to the transmission parameters of all nodes constituting the network.

In the context of this project, we worked on the development of a cross-layer resource management system over single hop and multihop Direct-Sequence Code Division Multiple Access (DS-CDMA) Visual Sensor Networks (VSNs). The target was the optimal determination and allocation of the source and channel coding rates and the power levels among the nodes of the considered network. For the efficient allocation of the nodes' transmission parameters, we applied various distortion-related criteria, drawing inspiration from game theory as well, and investigated fairness and efficiency under different perspectives for each of them. Computational intelligence optimization algorithms and reinforcement learning techniques were applied in order to solve the resulting optimization problems. All the solutions provided by the examined schemes were Pareto-optimal and thus, the choice about the most fair and efficient scheme is problem-dependent. Some of the approaches that were taken into account for further improving the end-to-end video distortion of a wireless multiple-access VSN included the time scheduling of transmitting nodes for interference mitigation, the optimal Instantaneous Decoding Refresh (IDR) frame placement during encoding, the content-based node prioritization, and the weighted bi-objective optimization for measuring the trade-off between video quality and consumed transmission power. The evaluation of all proposed approaches showed that enhanced end-to-end video quality can be achieved, by keeping power consumption at reasonable levels, when compared to the case of assigning equal values to the transmission parameters of all nodes constituting the network.

In the context of this project, we worked on the development of a cross-layer resource management system over single hop and multihop Direct-Sequence Code Division Multiple Access (DS-CDMA) Visual Sensor Networks (VSNs). The target was the optimal determination and allocation of the source and channel coding rates and the power levels among the nodes of the considered network. For the efficient allocation of the nodes' transmission parameters, we applied various distortion-related criteria, drawing inspiration from game theory as well, and investigated fairness and efficiency under different perspectives for each of them. Computational intelligence optimization algorithms and reinforcement learning techniques were applied in order to solve the resulting optimization problems. All the solutions provided by the examined schemes were Pareto-optimal and thus, the choice about the most fair and efficient scheme is problem-dependent. Some of the approaches that were taken into account for further improving the end-to-end video distortion of a wireless multiple-access VSN included the time scheduling of transmitting nodes for interference mitigation, the optimal Instantaneous Decoding Refresh (IDR) frame placement during encoding, the content-based node prioritization, and the weighted bi-objective optimization for measuring the trade-off between video quality and consumed transmission power. The evaluation of all proposed approaches showed that enhanced end-to-end video quality can be achieved, by keeping power consumption at reasonable levels, when compared to the case of assigning equal values to the transmission parameters of all nodes constituting the network.

Overview: *Objective *Wireless Ad Hoc Networks Characteristics *Cross-Layer Design Factors and Feedback Stack *Cross-layer optimization and adaptation improves performance in the user plane -Fast-handoff for mobile using triggers (MOSAIC/CERDEC, LTS, AJCN/DARPA/CERDEC) -Adaptive application based on signaling (AJCN/DARPA/CERDEC) *Cross-layer optimization improves performance in the network management plane -Cross layer Issues in domain auto-configuration (ARL CTA C&N) *Conclusions.