This paper proposes a new push-based peer-to-peer (P2P) communication method to optimally transmit scalable video packets over lossy networks. In our scheme, a rate allocation optimization is performed at the sender node. Different from previous sender/receiver driven schemes, our scheme does not need to update buffer maps or request packets periodically, which reduces the amount of redundant packets and yields to less traffic of video data over the Internet. The proposed optimized rate allocation algorithm calculates in advance the number of needed packets according to the cumulative uplink rate between senders and the receiver, and the loss rate of the link. After calculation, each sender sends the hierarchical network coded packets to receivers based on the estimated bandwidth and resource share allocation. With this method, the waste of bandwidth, and the delay caused by the communications among peers can both be reduced.

3-D tele-immersion (3DTI) enables participants in remote locations to share, in real time, an activity. It offers users interactive and immersive experiences, but it challenges current media-streaming solutions. Work in the past has mainly focused on the efficient delivery of image-based 3-D videos and on realistic rendering and reconstruction of geometry-based 3-D objects. The contribution of this paper is a real-time streaming component for 3DTI with dynamic reconstructed geometry. This component includes both a novel fast compression method and a rateless packet protection scheme specifically designed towards the requirements imposed by real time transmission of live-reconstructed mesh geometry. Tests on a large dataset show an encoding speed-up up to ten times at comparable compression ratio and quality, when compared with the high-end MPEG-4 SC3DMC mesh encoders. The implemented rateless code ensures complete packet loss protection of the triangle mesh object and a delivery delay within interactive bounds. Contrary to most linear fountain codes, the designed codec enables real-time progressive decoding allowing partial decoding each time a packet is received. This approach is compared with transmission over TCP in packet loss rates and latencies, typical in managed WAN and MAN networks, and heavily outperforms it in terms of end-to-end delay. The streaming component has been integrated into a larger 3DTI environment that includes state of the art 3-D reconstruction and rendering modules. This resulted in a prototype that can capture, compress transmit, and render triangle mesh geometry in real-time in realistic internet conditions as shown in experiments. Compared with alternative methods, lower interactive end-to-end delay and frame rates over three times higher are achieved.

3D Tele-immersion enables participants in remote locations to share, in real-time, an activity. It offers users natural interactivity and immersive experiences, but it challenges current networking solutions. Work in the past has mainly focused on the efficient delivery of image-based 3D videos and on the realistic rendering and reconstruction of geometry-based 3D objects. The contribution of this paper is a complete media pipeline that allows for geometry-based 3D tele-immersion. Unlike previous approaches, that stream videos or video plus depth estimate, our streaming module can transmit the live-reconstructed 3D representations (triangle meshes). Based on a set of comparative experiments, this paper details the architecture and describes a novel component that can efficiently stream geometry in real-time. This component includes both a novel fast local compression algorithm and a rateless packet protection scheme geared towards the requirements imposed by real-time transmission of live-capture mesh geometry. Tests on a large dataset show an encoding and decoding speed-up of over 10 times at similar compression and quality rates, when compared to the high-end MPEG-4 SC3DMC mesh encoder. The implemented rateless code ensures complete packet loss protection of the triangle mesh object and avoids delay introduced by retransmissions. This approach is compared to a streaming mechanism over TCP and outperforms it at packet loss rates over 2% and/or latencies over 9 ms in terms of end-to-end transmission delay. As reported in this paper, the component has been successfully integrated into a larger tele-immersive environment that includes beyond state of the art 3D reconstruction and rendering modules. This resulted in a prototype that can capture, compress transmit and render triangle mesh geometry in real-time over the internet.

In cognitive radios (CR) secondary users (SU) transmit alongside primary users (PU). In order to avoid interference SU perform spectrum sensing and adaptive transmission. Ultra-wideband sensing is of primary importance to sense and access opportunistically several bands at a time. The state of the art for opportunistic wideband sensing is given by Multiband Joint Detection (MJD). Constraints on interference and utilization have to be imposed to solve the multiband optimization with convex maximization. In this paper we propose an alternative optimization technique based on the genetic algorithms. The genetic programming performs direct search of the optimal solution one step before the aforementioned mathematical limitations. By operating directly on the objective of the optimization we show that the wideband sensing problem can be solved consistently with the problem formulation and without limitations.

In cognitive radios (CR) secondary users (SU) transmit alongside primary users (PU). In order to avoid interference SU perform spectrum sensing and adaptive transmission. Reliable detection of existing transmissions in wide geographical regions need to perform collaborative sensing. The state of the art for efficient collaborative sensing is given by linear statistics combination. Complex mathematical reformulations and limitations have been suggested to solve the combination optimization, due to its non convex nature. In this paper we propose an alternative optimization technique based on genetic algorithms. The genetic programming performs direct search of the optimal solution one step before the reformulations needed previously. We demonstrate that, by operating directly on the objective of the optimization, the collaborative sensing solution is found consistently with the problem formulation.