Unmanned aerial vehicles (UAVs) have gained popularity for diverse applications and services in both the military and civilian domains. For cooperation and collaboration among UAVs, they can be wirelessly interconnected in an ad hoc manner, resulting in a UAV network. UAV networks have unique features and characteristics that are different from mobile ad hoc networks and vehicular ad hoc networks. The dynamic behavior of rapid mobility and topology changes in UAV networks makes the design of a routing protocol quite challenging. In this paper, we review the routing protocols for UAV networks, in which the topology-based, position-based, hierarchical, deterministic, stochastic, and social-network-based routing protocols are extensively surveyed. The routing protocols are then compared qualitatively in terms of their major features, characteristics, and performance. Open issues and research challenges are also discussed in the perspective of design and implementation.

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Routing Protocols for Unmanned Aerial Vehicle Networks: A Survey

In the past few years, there has been much research on the application of swarm intelligence to the problem of adaptive routing in telecommunications networks. A large number of algorithms have been proposed for different types of networks, including wired networks and wireless ad hoc networks. In this paper, we give an overview of this research area. We address both the principles underlying the research and the practical applications that have been proposed. We start by giving a detailed description of the challenges in this problem domain, and we investigate how swarm intelligence can be used to address them. We identify typical building blocks of swarm intelligence systems and we show how they are used to solve routing problems. Then, we present Ant Colony Routing, a general framework in which most swarm intelligence routing algorithms can be placed. After that, we give an extensive overview of existing algorithms, discussing for each of them their contributions and their relative place in this research area. We conclude with an overview of future research directions that we consider important for the further development of this field.

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Principles and applications of swarm intelligence for adaptive routing in telecommunications networks

Network optimizations in the Internet of Things: A review

The necessity of image fusion is growing in recently in image processing applications due to the tremendous amount of acquisition systems. Fusion of images is defined as an alignment of noteworthy Information from diverse sensors using various mathematical models to generate a single compound image. The fusion of images is used for integrating the complementary multi-temporal, multi-view and multi-sensor Information into a single image with improved image quality and by keeping the integrity of important features. It is considered as a vital pre-processing phase for several applications such as robot vision, aerial, satellite imaging, medical imaging, and a robot or vehicle guidance. In this paper, various state-of-art image fusion methods of diverse levels with their pros and cons, various spatial and transform based method with quality metrics and their applications in different domains have been discussed. Finally, this review has concluded various future directions for different applications of image fusion.

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Image Fusion Techniques: A Survey

Mobile Ad-Hoc Networks (MANETs) are autonomous and decentralized wireless systems. Mobile Ad hoc Network is a collection of mobile nodes in which the wireless links are frequently broken down due to mobility and dynamic infrastructure. Routing is a significant issue and challenge in ad hoc networks. Many Routing protocols have been proposed so far to improve the routing performance and reliability. This research paper describes the characteristics of ad hoc routing protocols Ad-hoc On Demand Distance Vector Routing (AODV), Optimized link State Routing (OLSR), Temporally Ordered Routing Algorithm (TORA), Dynamic Source Routing (DSR), Destination-Sequenced Distance-Vector Routing (DSDV) based on the performance metrics like packet delivery fraction, Average delay, Normalized Routing load, Throughput and Jitter under low mobility and low traffic network as well as under high mobility and high traffic network. Results show that AODV has maximum throughput under low traffic and DSDV has maximum throughput under high traffic. As network becomes dense OLSR, DSR and DSDV perform well in terms of Throughput than AODV and TORA. TORA performs well in dense networks in terms of packet delivery fraction but at the same time Normalized Routing load of TORA is maximum among all the protocols in both the networks. DSDV has least Normalized Routing load in both low and high traffic. OLSR and DSDV give the least Jitter and Average Delay in both networks.

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Comparative Analysis of AODV, OLSR, TORA, DSR and DSDV Routing Protocols in Mobile Ad-Hoc Networks

Mobile Ad hoc Network (MANET) is a collection of mobile nodes in which the wireless links are frequently broken down due to mobility and dynamic infrastructure. Routing is a significant issue and challenge in ad hoc networks. Many routing protocols have been proposed like OLSR, AODV, DSR, ZRP, and TORA so far to improve the routing performance and reliability. This research paper describes the characteristics of ad hoc routing protocols OLSR, AODV and TORA based on the performance metrics like packet delivery ratio, end-to-end delay, routing overload by increasing number of nodes in the network. This comparative study proves that AODV, TORA performs well in dense networks than OLSR in terms of packet delivery ratio.

A study and comparison of OLSR, AODV and TORA routing protocols in ad hoc networks

Multimodal medical image fusion is a powerful tool for diagnosing diseases in medical field. The main objective is to capture the relevant information from input images into a single output image, which plays an important role in clinical applications. In this paper, an image fusion technique for the fusion of multimodal medical images is proposed based on Non-Subsampled Contourlet Transform. The proposed technique uses the Non-Subsampled Contourlet Transform (NSCT) to decompose the images into lowpass and highpass subbands. The lowpass and highpass subbands are fused by using mean based and variance based fusion rules. The reconstructed image is obtained by taking Inverse Non-Subsampled Contourlet Transform (INSCT) on fused subbands. The experimental results on six pairs of medical images are compared in terms of entropy, mean, standard deviation, QAB/F as performance parameters. It reveals that the proposed image fusion technique outperforms the existing image fusion techniques in terms of quantitative and qualitative outcomes of the images. The percentage improvement in entropy is 0% - 40%, mean is 3% - 42%, standard deviation is 1% - 42%, QAB/Fis 0.4% - 48% in proposed method comparing to conventional methods for six pairs of medical images.

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Multimodal Medical Image Fusion in Non-Subsampled Contourlet Transform Domain

Adaptive Image Enhancement using Hybrid Particle Swarm Optimization and Watershed Segmentation

The infrastructure less and the dynamic nature of mobile ad hoc networks (MANET) demands new set of networking strategies to be implemented in order to provide efficient end-to-end communication These, along with the diverse application of these networks in many different scenarios such as battlefield and disaster recovery, have seen MANETs being researched by many different organizations and institutes MANETs employ the traditional TCP/IP structure to provide end-to-end communication between nodes However, due to their mobility and the limited resource in wireless networks, each layer in the TCP/IP model requires redefinition or modifications to function efficiently in MANETs One interesting research area in MANET is routing Routing in the MANETs is a challenging task and has received a tremendous amount of attention from researches Due to the adaptive and dynamic nature, ant based routing algorithms are gaining more importance in routing This has led to development of many different ant based routing protocols for MANETs It is quite difficult to determine which protocols may perform best under a number of different network scenarios, such as increasing node density and traffic In this paper, we have provided an overview of a wide range of ant based routing protocols proposed in the literature

Review of ant based routing protocols for MANET

Problem statement: A great deal of excitement has recently propelled Mobile Learning to the forefront of educational technology. The exponential growth of mobile technology in the recent years, increase in the availability of high-bandwidth network, advances in wireless technologies and popularity of handheld devices, have opened up new accessibility opportunities for education. Approach: Virtual class room using MANET had been proposed to enhance the m-Learning opportunities in a residential institution. Results: This environment transferred both large and small volume of data to the particular group members. Generally multicasting supports group oriented computing. Such a group oriented service required a suitable multicast routing protocol. Two standard multicast routing protocols were implemented and analyzed for tree (MAODV) and mesh (ODMRP) based approach. The performances of group learning module of VCR had been analyzed using MAODV and ODMRP routing protocols for parameters such as network traffic, the node speed and the network area. Conclusion/Recommendations: Our results showed that many scenarios in VCR environment, MAODV achieved a higher packet delivery ratio than ODMRP.

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B. Kalaavathi

Papers

A study and comparison of OLSR, AODV and TORA routing protocols in ad hoc networks

Multimodal Medical Image Fusion in Non-Subsampled Contourlet Transform Domain

Adaptive Image Enhancement using Hybrid Particle Swarm Optimization and Watershed Segmentation

Review of ant based routing protocols for MANET

A Performance Study of Reactive Multicast Routing Protocols in Virtual Class Room Using Mobile Ad Hoc Network