A mobile ad hoc network consists of wireless hosts that may move often. Movement of hosts results in a change in routes, requiring some mechanism for determining new routes. Several routing protocols have already been proposed for ad hoc networks. This report suggests an approach to utilize location information (for instance, obtained using the global positioning system) to improve performance of routing protocols for ad hoc networks.

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Location-aided routing (LAR) in mobile ad hoc networks

Ad hoc networks are characterized by multi-hop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of two prominent on-demand routing protocols for mobile ad hoc networks - dynamic source routing (DSR) and ad hoc on-demand distance vector routing (AODV). A detailed simulation model with MAC and physical layer models is used to study inter-layer interactions and their performance implications. We demonstrate that even though DSR and AODV share a similar on-demand behavior the differences in the protocol mechanics can lead to significant performance differentials. The performance differentials are analyzed using varying network load, mobility and network size. Based on the observations, we make recommendations about how the performance of either protocol can be improved.

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Performance comparison of two on-demand routing protocols for ad hoc networks

We develop an on-demand multipath distance vector protocol for mobile ad hoc networks. Specifically, we propose multipath extensions to a well-studied single path routing protocol known as ad hoc on-demand distance vector (AODV). The resulting protocol is referred to as ad hoc on-demand multipath distance vector (AOMDV). The protocol computes multiple loop-free and link-disjoint paths. Loop-freedom is guaranteed by using a notion of "advertised hopcount". Link-disjointness of multiple paths is achieved by using a particular property of flooding. Performance comparison of AOMDV with AODV using ns-2 simulations shows that AOMDV is able to achieve a remarkable improvement in the end-to-end delay-often more than a factor of two, and is also able to reduce routing overheads by about 20%.

On-demand multipath distance vector routing in ad hoc networks

In this paper, we present a survey of various mobility models in both cellular networks and multi-hop networks We show that group motion occurs frequently in ad hoc networks, and introduce a novel group mobility model Reference Point Group Mobility (RPGM) to represent the relationship among mobile hosts RPGM can be readily applied to many existing applications Moreover, by proper choice of parameters, RPGM can be used to model several mobility models which were previously proposed One of the main themes of this paper is to investigate the impact of the mobility model on the performance of a specific network protocol or application To this end, we have applied our RPGM model to two different network protocol scenarios, clustering and routing, and have evaluated network performance under different mobility patterns and for different protocol implementations As expected, the results indicate that different mobility patterns affect the various protocols in different ways In particular, the ranking of routing algorithms is influenced by the choice of mobility pattern

A group mobility model for ad hoc wireless networks

Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of two prominent on-demand routing protocols for mobile ad hoc networks: dynamic source routing (DSR) and ad hoc on-demand distance vector routing (AODV). A detailed simulation model with MAC and physical layer models is used to study interlayer interactions and their performance implications. We demonstrate that even though DSR and AODV share similar on-demand behavior, the differences in the protocol mechanics can lead to significant performance differentials. The performance differentials are analyzed using varying network load, mobility, and network size. Based on the observations, we make recommendations about how the performance of either protocol can be improved.

We evaluate several routing protocols for mobile, wireless, ad hoc networks via packet level simulations. The protocol suite includes routing protocols specifically designed for ad hoc routing, as well as more traditional protocols, such as link state and distance vector used for dynamic networks. Performance is evaluated with respect to fraction of packets delivered, end-to-end delay and routing load for a given traffic and mobility model. It is observed that the new generation of on-demand routing protocols use a much lower routing load. However the traditional link state and distance vector protocols provide, in general, better packet delivery and delay performance.

Comparative performance evaluation of routing protocols for mobile, ad hoc networks

In this paper we evaluate several routing protocols for mobile, wireless, ad hoc networks via packetdlevel simulations. The ad hoc networks are multidhop wireless networks with dynamically changing network connectivity owing to mobility. The protocol suite includes several routing protocols specifically designed for ad hoc routing, as well as more traditional protocols, such as link state and distance vector, used for dynamic networks. Performance is evaluated with respect to fraction of packets delivered, enddtodend delay, and routing load for a given traffic and mobility model. Both small l30 nodesr and medium sized l60 nodesr networks are used. It is observed that the new generation of onddemand routing protocols use much lower routing load, especially with small number of peerdtodpeer conversations. However, the traditional link state and distance vector protocols provide, in general, better packet delivery and enddtodend delay performance.

Simulation-based performance evaluation of routing protocols for mobile ad hoc networks

Recent years have witnessed a growing interest in the use of U-Net and its improvement. It is one of the classic semantic segmentation networks with an encoder-decoder architecture and is widely used in medical image segmentation. In the series versions of U-Net, U-Net++ has been developed as an improved U-Net by designing an architecture with nested and dense skip connections, and U-Net 3+ has been developed as an improved U-Net++ by taking advantage of full-scale skip connections and deep supervision on full-scale aggregated feature maps. Each network architecture has its own advantages in the use of the encoder and decoder. In this paper, we propose an efficient and lightweight U-Net (ELU-Net) with deep skip connections. The deep skip connections include same- and large-scale skip connections from the encoder to fully extract the features of the encoder. In addition, the proposed ELU-Net with different loss functions is discussed to improve the effect of brain tumor learning including WT (whole tumor), TC (tumor core) and ET (enhance tumor) and a new loss function DFK is designed. The effectiveness of the proposed method is demonstrated for a brain tumor dataset used in the BraTs 2018 Challenge and liver dataset used in the ISBI LiTS 2017 Challenge.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09745574.pdf

Jiangtao Yan

Papers

Comparative performance evaluation of routing protocols for mobile, ad hoc networks

Simulation-based performance evaluation of routing protocols for mobile ad hoc networks

ELU-Net: An Efficient and Lightweight U-Net for Medical Image Segmentation