Ant Router: An efficient routing protocol for social opportunistic networks using ant routing

Sharma, Deepak; Singh, Simran Jeet; Gautam, Vishakha; Kumaram, Shubham; Sharma, Mehul; Pant, Shrid

doi:10.1049/iet-net.2019.0077

Cited by 9 publications

(3 citation statements)

References 30 publications

(22 reference statements)

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“…Kr. Sharma et al [26] proposed a routing protocol-Ant Router based on ant colony optimization algorithm, which stores the relevant information in the buffer of each node and then uses the "ant" algorithm to find a reasonable next hop of the data packet. It reaches the final destination through the shortest channel from the source.…”

Section: Related Workmentioning

confidence: 99%

Effective Data Optimization and Evaluation Based on Social Communication with AI-Assisted in Opportunistic Social Networks

Gou

Long

et al. 2022

Wireless Communications and Mobile Computing

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Billions of people around the world send and receive data over online networks daily. Sufficient and redundant data are transmitted over social platforms with AI-assisted in 5G networks. In opportunistic social networks, the main challenge faced by traditional methods is that numerous user nodes participate in data transmission, causing a lot of message copy redundancy and node cache consumption. As a result, the transmission delay of the algorithm is high, the node energy consumption is too large, and even information is lost. To solve these problems, this study establishes an artificial intelligence-based optimization multiple evaluation method. The main purpose of this method is to avoid information loss caused by data loss when reducing data noise, reasonably select communication nodes in opportunistic social network scenarios, optimize data transmission performance, and avoid network congestion. Moreover, our method can effectively identify and exclude potential malicious nodes, reducing the situation that packets are intercepted and discarded. The experiment confirms that the optimized transmission evaluation scheme can effectively reduce routing overheads and energy consumption of a user node, improve the delivery ratio of node data transmission, and ensure the reliability and security of data transmission.

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Section: Related Workmentioning

confidence: 99%

Effective Data Optimization and Evaluation Based on Social Communication with AI-Assisted in Opportunistic Social Networks

Gou

Long

et al. 2022

Wireless Communications and Mobile Computing

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“…Stimulated by the nature of real ants, Deepak et al 37 proposed efficient Ant Routing for the Social opportunistic networks, which uses the Ant Colony Optimisation approach to assist the nodes in identifying the efficient route from source to the destination node. In this ant routing approach, the nodes called search agents are of two kinds—Forward Ants (FA) and Backward Ants (BA).…”

Section: Related Workmentioning

confidence: 99%

AI‐enabled trust‐based routing protocol for social opportunistic IoT networks

Nigam

Sharma

Jain

et al. 2021

Trans Emerging Tel Tech

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The emergence of the new applications in the realm of Opportunistic IoT networks brings exceptional levels of complexity with it; hence, Artificial Intelligence‐based approaches are envisioned for the design and optimization owing to the versatility and adaptability it assists in resolving complex real‐time problems. In these networks, messages are transmitted through node cooperation because of the nodes' random movement and a lack of network infrastructure. As it is an open network, message forwarding is susceptible to intervention from anomalous nodes that may attribute maliciousness or selfishness, which may cause network transmission disorder and makes routing complex in Social Opportunistic IoT networks. By leveraging AI's capability, these networks can be redesigned to enable a more secure and efficient routing for the nodes. In order to suppress various harmful impacts in the network from anomalous nodes, this paper proposes an AI‐Enabled Trust‐Based Routing Protocol using NSGA‐II for Social Opportunistic IoT Networks (TBRP), which uses the concept of multi‐objective optimization. TBRP employs a new Four Tier Protocol trust scheme based on contextual parameters. This AI‐enabled multi‐objective optimization scheme modifies the conventional NSGA‐II for amelioration through an intelligent chromosome representation, improved crossover, and mutation paradigm. TBRP is evaluated against several routing protocols and with trust‐based protocols TCAFE and MT‐SMRP on various performance metrics using the INFOCOMM dataset. TBRP outperforms Firefly PRoPHET, AntRouter, GAER, and PRoPHET by 1.66%, 10.66%, 25.44%, and 58.57%, respectively, in terms of the delivery success ratio while varying the time for which simulation is run.

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“…In [16] works on Ant algorithm which is a heuristic probabilistic routing scheme works on the principle of finding a good and short routing path among source and destination node for message packet delivery. In this proposed scheme by researchers, it mainly focusses in making the network optimize so as to minimal the network resource consumption.…”

Section: -Congestion Level Of a Node [8]mentioning

confidence: 99%

Feature Extraction of Real-World Traces Using K Means Clustering In OppNet

Johari

Gautam

2021

Preprint

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Natural calamities leave people helpless by arising several situations such as network breakdown, zero communication, intermittent connectivity, dynamic network topology. In such situation an application of dynamic and intermittent routing scheme is essential to make further communication possible during likewise scenarios. An application of TCP/IP becomes futile in mentioned circumstances as it best works for static nodes and pre-defined network topology wherein source and destination nodes are first establishing the communication link with each other. An alternative measure of such hitches is to encounter an application of DTN protocol which possess all characteristics to withstand in such scenarios such as; dynamic network topology, intermittent connectivity, frequent path breaks, store – carry – forward fashion. In this paper we did thorough investigation of forest fire dataset (Uttarakhand) after exploring its implementation in ONE with Epidemic, Prophet, Spray and Wait, HBPR, GAER respectively. An extensive and thorough investigation for real world traces implementation has been done with OppNet routing protocols against mobility models namely; Shortest path map – based, Random Direction, Random Walk, Random Waypoint, Cluster Movement respectively for network performance metrics namely packet delivery ratio, packet overhead ratio and average latency ratio respectively with the application of K means clustering machine learning algorithm. With the help of this analysis, we explore the real-world traces characteristics and study the areas on which network performance can be improved.

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Ant Router: An efficient routing protocol for social opportunistic networks using ant routing

Cited by 9 publications

References 30 publications

Effective Data Optimization and Evaluation Based on Social Communication with AI-Assisted in Opportunistic Social Networks

Effective Data Optimization and Evaluation Based on Social Communication with AI-Assisted in Opportunistic Social Networks

AI‐enabled trust‐based routing protocol for social opportunistic IoT networks

Feature Extraction of Real-World Traces Using K Means Clustering In OppNet

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