Low control overhead and power cost are two key issues in wireless sensor networks to improve protocol efficiency. They decide the quality of service provided by the protocol. Ad-hoc On Demand Distance Vector protocol (AODV) is a preferred routing protocol in wireless sensor networks. The routing overhead of AODV is a drawback in power-constrained environment. This paper presents an enhanced routing algorithm RE-AODV with a local route enhancement model for AODV which reduces the routing overhead and improves the efficiency. The Hello packet broadcast mechanism of the standard AODV is enhanced to save time-and-again discarding and rediscovering the routes. The theoretical substantiation and the performance evaluation using the TOSSIM simulator are presented. The results show that the new algorithm is efficient with reduced control overhead and end-to-end delay.

RE-AODV: An enhanced routing algorithm for QoS support in wireless ad-hoc sensor networks

/pdf/comparative-study-on-diamond-search-algorithm-for-motion-58kvj6gfke.pdf

Comparative Study on Diamond Search Algorithm for Motion Estimation

In order to fulfill the requirement of limited channel bandwidth and of growing video demand like streaming media delivery on internet, and digital library, video compression is necessary. In video compression, temporal redundancy between adjacent frames is removed with block based motion estimation algorithms. Video represents a sequence of frames captured from camera. Scene is a series of consecutive frames captured from narrative point of view. In this paper we present an effective scene change detection method for an uncompressed video. We have divided frames in to blocks and applied a canny edge detector in consecutive frames. Count no of pixels (ones) in each block and compare it with consecutive frames. If scene change happens then number of pixels per block will change, based on that change we can detect scene change in consecutive frame. Here we have presented a hybrid approach, in which we have used scene change detection along with block based motion estimation algorithms (BME) to compress video.

Hybrid approach for video compression based on scene change detection

This paper reviews the energy efficiency of several popular block-matching motion estimation algorithms that can be used in wireless video sensor network applications. Full search motion estimation provides the best image quality but requires high computing power. Therefore, only fast search algorithms are considered for deployment in wireless video sensor networks, which generally operate in remote, battery-constrained areas. However, the image quality of fast search algorithms also needs to be considered in the comparison. In this paper, those block-matching algorithms are compared using two criteria: 1) computing cost/energy consumption, and 2) image quality. The purpose of this review is to select the most energy efficient algorithm that retains image quality and can be applied to wireless video sensor network video compression applications.

Review of energy efficient block-matching motion estimation algorithms for wireless video sensor networks

https://www.ijfis.org/journal/download_pdf.php?doi=10.5391/IJFIS.2022.22.4.366

MB-FL: Macro-Block Fuzzy Logic for Video Compression in Multimedia Applications

Motion Estimation is an important step in video compression wherein block matching algorithms are used for computing Motion Vectors (MV). Diamond Search (DS) is one of the most efficient block matching motion estimation (BMME) algorithms. A revised diamond search algorithm, which modifies the two search patterns of DS, is proposed in this paper. The MDSS algorithm on comparison with the existing search algorithms is advantageous as it minimizes the number of search points used, while maintaining the video quality. Moreover it tries to accelerate the search process compared with the diamond search algorithm.

Modified diamond-square search technique for efficient motion estimation

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Modified diamond-square search technique for efficient motion estimation