An Opportunistic Routing Protocol for Mobile Ad Hoc Networks Based on Stable Ideology

Ding, Yunzheng; Li, Yicheng; Xu, Yuan-chun; Zhou, Yongzheng; Zhang, Yilai

doi:10.1007/s11277-017-4506-7

Cited by 3 publications

(3 citation statements)

References 28 publications

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“…The mesh routers transmission range is typically higher than the client. It projects the traces of link asymmetry over the mesh access network model [7]. The MAC protocol is adopted in these network models to establish channel access coordination in the multi-hop environment [8].…”

Section: Introductionmentioning

confidence: 99%

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Krishnammal¹,

Kalaiarasan²,

Bharathi³

2023

Computer Systems Science and Engineering

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Link asymmetry in wireless mesh access networks (WMAN) of Mobile ad-hoc Networks (MANETs) is due mesh routers' transmission range. It is depicted as significant research challenges that pose during the design of network protocol in wireless networks. Based on the extensive review, it is noted that the substantial link percentage is symmetric, i.e., many links are unidirectional. It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message. Therefore, the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asymmetric links. It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation. Here, a novel Learningbased Dynamic Tree routing (LDTR) model is proposed to improve network performance and delay. For the evaluation of delay measures, asymmetric link, interference, probability of transmission failure is evaluated. The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity. This learning model is a productive way for resolving the routing issues over the network model during uncertainty. The asymmetric path is chosen to achieve exploitation and exploration iteratively. The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem. Here, the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model (DQN), asymmetric MAC model (AMAC), and cooperative asymmetric MAC model (CAMAC) model. The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others. The average energy consumption is 250 J, packet energy consumption is 6.5 J, PRR is 50 bits/sec, 95% PDR, average delay percentage is 20%.

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Section: Introductionmentioning

confidence: 99%

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Krishnammal¹,

Kalaiarasan²,

Bharathi³

2023

Computer Systems Science and Engineering

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“…The efficiency of a route depends on the cooperation of all intermediate nodes participating in data transmissions. These restrictions make the route selection problem particularly difficult; thus, researchers have developed several routing algorithms for mobile ad hoc networks MANETs [1].…”

Section: Introductionmentioning

confidence: 99%

FQ-AGO: Fuzzy Logic Q-Learning Based Asymmetric Link Aware and Geographic Opportunistic Routing Scheme for MANETs

2020

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The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implemented FQ-AGO on the ns-3 simulator and compared the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we considered various network metrics to compare the performance of the routing protocols. The simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay. FQ-AGO achieves up to 15%, 50%, and 45% higher throughput compared to DSDV, AODV, and GOR, respectively. Meanwhile, FQ-AGO reduces by 50% the end-to-end latency and the average number of hop-count.

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“…The Opportunistic Network (OppNet) is a kind of ad-hoc network [1] that can complete information forwarding in the intermittently connected network environment, through the contact opportunity brought by the mutual movement between nodes. The OppNet is originated from the mobile ad-hoc network (MANET) [2] and the delay tolerant network (DTN) [3]. The communication of OppNet is different from the traditional wireless network.…”

Section: Introductionmentioning

confidence: 99%

An Opportunistic Network Routing Algorithm Based on Cosine Similarity of Data Packets between Nodes

Lin

Chen

et al. 2018

Algorithms

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The mobility of nodes leads to dynamic changes in topology structure, which makes the traditional routing algorithms of a wireless network difficult to apply to the opportunistic network. In view of the problems existing in the process of information forwarding, this paper proposed a routing algorithm based on the cosine similarity of data packets between nodes (cosSim). The cosine distance, an algorithm for calculating the similarity between text data, is used to calculate the cosine similarity of data packets between nodes. The data packet set of nodes are expressed in the form of vectors, thereby facilitating the calculation of the similarity between the nodes. Through the definition of the upper and lower thresholds, the similarity between the nodes is filtered according to certain rules, and finally obtains a plurality of relatively reliable transmission paths. Simulation experiments show that compared with the traditional opportunistic network routing algorithm, such as the Spray and Wait (S&W) algorithm and Epidemic algorithm, the cosSim algorithm has a better transmission effect, which can not only improve the delivery ratio, but also reduce the network transmission delay and decline the routing overhead.

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An Opportunistic Routing Protocol for Mobile Ad Hoc Networks Based on Stable Ideology

Cited by 3 publications

References 28 publications

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

FQ-AGO: Fuzzy Logic Q-Learning Based Asymmetric Link Aware and Geographic Opportunistic Routing Scheme for MANETs

An Opportunistic Network Routing Algorithm Based on Cosine Similarity of Data Packets between Nodes

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