A mobile ad-hoc network (MANET) is a collection of mobile nodes which communicate over radio. These kind of networks are very flexible, thus they do not require any existing infrastructure or central administration. Therefore, mobile ad-hoc networks are suitable for temporary communication links. The biggest challenge in this kind of networks is to find a path between the communication end points, what is aggravated through the node mobility.In this paper we present a new on-demand routing algorithm for mobile, multi-hop ad-hoc networks. The protocol is based on swarm intelligence and especially on the ant colony based meta heuristic. These approaches try to map the solution capability of swarms to mathematical and engineering problems. The introduced routing protocol is highly adaptive, efficient and scalable. The main goal in the design of the protocol was to reduce the overhead for routing. We refer to the protocol as the Ant-Colony-Based Routing Algorithm (ARA).
Recently, HTTP has been widely used for the delivery of realtime multimedia content over the Internet, such as in video streaming applications. To combat the varying network resources of the Internet, rate adaptation is used to adapt the transmission rate to the varying network capacity. A key research problem of rate adaptation is to identify network congestion early enough and to probe the spare network capacity. In adaptive HTTP streaming, this problem becomes challenging because of the difficulties in differentiating between the short-term throughput variations, incurred by the TCP congestion control, and the throughput changes due to more persistent bandwidth changes.In this paper, we propose a novel rate adaptation algorithm for adaptive HTTP streaming that detects bandwidth changes using a smoothed HTTP throughput measured based on the segment fetch time (SFT). The smoothed HTTP throughput instead of the instantaneous TCP transmission rate is used to determine if the bitrate of the current media matches the end-to-end network bandwidth capacity. Based on the smoothed throughput measurement, this paper presents a receiver-driven rate adaptation method for HTTP/TCP streaming that deploys a step-wise increase/ aggressive decrease method to switch up/down between the different representations of the content that are encoded at different bitrates. Our rate adaptation method does not require any transport layer information such as round trip time (RTT) and packet loss rates which are available at the TCP layer. Simulation results show that the proposed rate adaptation algorithm quickly adapts to match the end-to-end network capacity and also effectively controls buffer underflow and overflow.
Abstract-A novel joint video encoding and statistical multiplexing (StatMux) method for broadcasting over digital video broadcasting for handhelds (DVB-H) channels is proposed to improve the quality of encoded video and to decrease the end-to-end delay in a broadcast system. The main parts of end-to-end delay in a DVB-H system result from a time-sliced transmission scheme that is used in DVB-H and from the bit rate variations of service bit streams. The time-sliced transmission scheme is utilized in DVB-H to reduce the power consumption of DVB-H receivers. Variable bit rate (VBR) video bit streams are used in DVB-H to improve the video quality and compression performance. The time-sliced transmission scheme has increased the channel switching delay, i.e., switching to a new audio-visual service, in DVB-H. The used VBR bit streams increase the required buffering delays in the whole system. The different parts of end-to-end delay in a DVB-H system can be affected by the used video encoding and multiplexing methods. Different scenarios for encoding and StatMux of video sources for DVB-H application are studied in this paper. Moreover, a new method for jointly encoding and StatMux of video sources is proposed that not only decreases the end-to-end delay but also improves the average quality of compressed video by dynamically distributing available bandwidth between the video sources according to their relative complexity. Performance of the proposed method is validated by simulation results.
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