In wireless sensor networks, bandwidth is one of precious resources to multimedia applications. To get more bandwidth, multipath routing is one appropriate solution provided that inter-path interferences are minimized. In this paper, we address the problem of interfering paths in the context of wireless multimedia sensor networks and consider both intra-session as well as inter-session interferences. Our main objective is to provide necessary bandwidth to multimedia applications through non-interfering paths while increasing the network lifetime. To do so, we adopt an incremental approach where for a given session, only one path is built at once. Additional paths are built when required, typically in case of congestion or bandwidth shortage. Interference awareness and energy saving are achieved by switching a subset of sensor nodes in a passive state in which they do not take part in the routing process. Despite the routing overhead introduced by the incremental approach we adopt, our simulations show that this can be compensated by the overall achieved throughput and the amount of consumed energy per correctly received packet especially for relatively long sessions such as multimedia ones. This is mainly due to the fact that a small number of non-interfering paths allows for better performances than a large number of interfering ones.

International audienceWireless sensor networks hold a great potential in the deployment of several applications of a paramount importance in our daily life. Video sensors are able to improve a number of these applications where new approaches adapted to both wireless sensor networks and video transport specific characteristics are required. The aim of this work is to provide the necessary bandwidth and to alleviate the congestion problem to video streaming. In this paper, we investigate various load repartition strategies for congestion control mechanism on top of a multipath routing feature. Simulations are performed in order to get insight into the performances of our proposals

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Video applications are being a key component to enhance traditional wireless sensor networks (WSN) applications. As a result, sensor network researchers need adequate and easy to use tools to assess the performances of their proposals. The existing transmission evaluation tools either consider video sequences along with codecs that are unsuitable for WSNs or make use of low cost compression methods for still images without inter-frame coding required for efficient video transmission. In this paper, we present SenseVid, an open source video transmission and evaluation tool that considers WSN specific characteristics. Besides low energy intra-frame compression based on fast pruned discrete cosine transform (DCT), a low complexity inter-frame encoding is provided to allow efficient support of video flows. A configurable fine-grain energy model is provided where both video capture and encoding cost are accounted for on a per frame basis. Video traffic differentiation based on priority levels is also provided. SenseVid adopts the video traffic traces approach, allowing its use in any simulation or real testbed environment. Using SenseVid, the user is able to reconstruct the received video considering lost packets during its transmission as well as estimating the achieved quality of service (QoS) and quality of experience (QoE).

Grid computing is a promising way to aggregate geographically distant machines and to allow them to work together to solve large problems. After studying Grid network requirements, we observe that the network must take part of the Grid computing session to provide intelligent adaptative transport of Grid data streams. By proposing new intelligent dynamic services, active network can be the perfect companion to easily and efficiently deploy and maintain Grid environments and applications. This paper presents the Active Grid Architecture (A-Grid) which focus on active networks adaptation for supporting Grid environments and applications. We focus the benefit of active networking for the grid on three aspects: High performance and dynamic active services, Active Reliable Multicast, and Active Quality of Service.