Reliable Asynchronous Image Transfer Protocol in Wireless Multimedia Sensor Networks

In the paper, we propose a reliable asynchronous image transfer protocol, RAIT. RAIT applies a double sliding window method to node-to-node transfer, with one sliding window for the receiving queue, which is used to prevent packet loss caused by communication failure between nodes, and another sliding window for the sending queue, which prevents packet loss caused by network congestion. The routing node prevents packet loss between nodes by preemptive scheduling of multiple packets for a given image. RAIT implements a double sliding window method by means of a cross-layer design between the RAIT layer, routing layer, and queue layer. We demonstrate that RAIT guarantees a higher reliability of image transmission compared to the existing protocols

Adaptive Compression of Slowly Varying Images Transmitted over Wireless Sensor Networks

In this article a scheme for image transmission over Wireless Sensor Networks (WSN) with an adaptive compression factor is introduced. The proposed control architecture affects the quality of the transmitted images according to: (a) the traffic load within the network and (b) the level of details contained in an image frame. Given an approximate transmission period, the adaptive compression mechanism applies Quad Tree Decomposition (QTD) with a varying decomposition compression factor based on a gradient adaptive approach. For the initialization of the proposed control scheme, the desired a priori maximum bound for the transmission time delay is being set, while a tradeoff among the quality of the decomposed image frame and the time needed for completing the transmission of the frame should be taken under consideration. Based on the proposed control mechanism, the quality of the slowly varying transmitted image frames is adaptively deviated based on the measured time delay in the transmission. The efficacy of the adaptive compression control scheme is validated through extended experimental results

Speedy Routing Recovery Protocol for Large Failure Tolerance in Wireless Sensor Networks

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols

Reliable multimedia transmission over wireless sensor network

Nowadays, video streaming application is widely used in wired as well as wireless environment. Extending this application into Wireless Sensor Networks (WSN) for IEEE 802.15.4 network has attracted lots of attention in the research community. Reliable data transmission is one of the most important requirements in WSN especially for multimedia application. Moreover, multimedia application requires high bandwidth and consumes large memory size in order to send video data that requires small end-to-end (ETE) delay. To overcome this problem, rate control serves as an important technique to control the bit rate of encoded video for transmission over a channel of limited bandwidth and low data rate which is 250kbps with small Maximum Transmission Unit (MTU) size of 127 bytes. Therefore, a rate control model called enhanced Video Motion Classification based (e-ViMoC) model using an optimal combination of parameter setting is proposed in this thesis. Another challenging task to maintain the video quality is the design of an enhanced transport protocol. Standard transport protocols cannot be directly applied in WSN specifically, but some modifications are required. Therefore, to achieve high reliability of video transmission, the advantages of User Datagram Protocol (UDP) features are applied to the proposed transport protocol called Lightweight Reliable Transport Protocol (LRTP) to tailor to the low data rate requirement of WSN. Besides, priority queue scheme is adopted to reduce the end-to-end delay while maintaining the reliability and energy efficiency. Evalvid simulation tool and exhaustive search method are used to determine optimal combination of quantization scale (q), frame rate (r) and Group of Picture (GOP) size (l) values to control the bit rate at the video encoder. The model of e-ViMoC is verified both with simulation and experimental work. The proposed transport protocol has been successfully studied and verified through simulation using Network Simulator 2 (NS-2). From the simulation results, the proposed e-ViMoC encoded video enhances the Packet Delivery Ratio (PDR) by 5.14%, reduces the energy consumed by 16.37%, improves the Peak Signal to Noise Ratio (PSNR) by 4.37% and reduces the ETE delay by 23.69% in average, compared to non-optimized encoded video. The tested experiment experiences slightly different result where the PDR is 6% lower than simulation results. Meanwhile, the combination of e-ViMoC and LRTP outperforms the standard transport protocol by average improvement of 142.9% for PDR, average reduction of 8.87% for energy consumption, average improvement of 4.1% for PSNR, and average reduction of 19.38% for ETE delay. Thus, the simulation results show that the combination of proposed e-ViMoC and LRTP provides better reliability performance in terms of the PDR while simultaneously improves the energy efficiency, the video quality and ETE delay