Ant Colony Optimization-based Dynamic Routing in Software Defined Networks

Shreya, T; Mulla, Mohammed Moin; Shinde, Sumedha; Narayan, D. G.

doi:10.1109/icccnt49239.2020.9225287

Cited by 15 publications

(4 citation statements)

References 13 publications

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“…Similar to the preceding work, researchers have attempted to select an optimum path satisfying video QoS parameters for routing using an algorithm [79]. Some use ant colony optimization for routing in KDN to select the optimum path from multiple paths [80]. Recently, an integer programming problem for maximizing the ratio for energy saving in KDN that quantifies energy efficiency based on link utility intervals has shown good results as an energy-efficient routing scheme [81].…”

Section: Generating Knowledge Using Heuristic Model-based Methodsmentioning

confidence: 99%

A Comprehensive Survey on Knowledge-Defined Networking

Wijesekara

Gunawardena

2023

Telecom

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Traditional networking is hardware-based, having the control plane coupled with the data plane. Software-Defined Networking (SDN), which has a logically centralized control plane, has been introduced to increase the programmability and flexibility of networks. Knowledge-Defined Networking (KDN) is an advanced version of SDN that takes one step forward by decoupling the management plane from control logic and introducing a new plane, called a knowledge plane, decoupled from control logic for generating knowledge based on data collected from the network. KDN is the next-generation architecture for self-learning, self-organizing, and self-evolving networks with high automation and intelligence. Even though KDN was introduced about two decades ago, it had not gained much attention among researchers until recently. The reasons for delayed recognition could be due to the technology gap and difficulty in direct transformation from traditional networks to KDN. Communication networks around the globe have already begun to transform from SDNs into KDNs. Machine learning models are typically used to generate knowledge using the data collected from network devices and sensors, where the generated knowledge may be further composed to create knowledge ontologies that can be used in generating rules, where rules and/or knowledge can be provided to the control, management, and application planes for use in decision-making processes, for network monitoring and configuration, and for dynamic adjustment of network policies, respectively. Among the numerous advantages that KDN brings compared to SDN, enhanced automation and intelligence, higher flexibility, and improved security stand tall. However, KDN also has a set of challenges, such as reliance on large quantities of high-quality data, difficulty in integration with legacy networks, the high cost of upgrading to KDN, etc. In this survey, we first present an overview of the KDN architecture and then discuss each plane of the KDN in detail, such as sub-planes and interfaces, functions of each plane, existing standards and protocols, different models of the planes, etc., with respect to examples from the existing literature. Existing works are qualitatively reviewed and assessed by grouping them into categories and assessing the individual performance of the literature where possible. We further compare and contrast traditional networks and SDN against KDN. Finally, we discuss the benefits, challenges, design guidelines, and ongoing research of KDNs. Design guidelines and recommendations are provided so that identified challenges can be mitigated. Therefore, this survey is a comprehensive review of architecture, operation, applications, and existing works of knowledge-defined networks.

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Section: Generating Knowledge Using Heuristic Model-based Methodsmentioning

confidence: 99%

A Comprehensive Survey on Knowledge-Defined Networking

Wijesekara

Gunawardena

2023

Telecom

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“…The proposed ant colony optimization [23] [24] has been studied extensively in the literature. It is a subclass of swarm intelligence methods that searches for the best solution in discrete optimization problems.…”

Section: Related Workmentioning

confidence: 99%

Improving Data Delivery in Unreliable Networks Using Network Coding and Ant-Colony Optimization

Afolabi,

Umar,

Akinola

2024

Int. J. Interact. Mob. Technol.

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Wireless Sensor Networks (WSNs) comprise interconnected wireless nodes that receive and transmit data across applications and platforms. This paper addressed the problem of link failures in WSNs that potentially could lead to the loss of data packets while still in transit. This was achieved through the use of network coding which is known to address capacity bottleneck problems in WSNs. In particular, a technique called Ant Agent-Assisted Network Coding (AAANC) is proposed that employs the ant colony optimization technique in addition to network coding operations. The main aim of AAANC is to facilitate the successful delivery and decoding of coded data packets in the presence of link failures. AAANC employs a packet route selection technique that is inspired by the social behavior of natural ants. For natural ants, a strong pheromone trail along a path indicates a promising route to a food source, and this is analogous to a reliable communication link for routing data packets in this paper. Through simulations, AAANC was compared to diagonal pseudorandom network coding (DNC) and triangular pseudorandom network coding (TNC), and it proved to have a superior performance in terms of packet delivery ratio and number of decoded packets. Significant performance gain can be achieved if AAANC algorithm is made to dynamically adapt the ant colony and network coding parameters in response to traffic changes.

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“…Authors in [10] have measured the network traffic, traffic flow and a comparison between Dijkstra and two phase flow embedding heuristic algorithm is carried out. The traditional method of Ant colony optimization is carried out in [11] to achieve optimization from start state to sink in the supervision of remote controller POX. The analysis and techniques of service composition approaches in SDN is done in [12] with relevance to the other traditional approaches.…”

Section: Literature Surveymentioning

confidence: 99%

A Fast Failover Technique for Link Failures and Proactive controller based Fault Recovery Mechanism in Software Defined Networks

Kumar¹,

Sreen²

2022

Preprint

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In this work, a fast fault tolerant failure methodology is proposed to solve problems including single link and multi-link failure by including pre-established various alternate backup paths for each pair from origin to final destination. In addition, a Reliable fast failover technique for link faults and fault recovery mechanism using proactive controller Software defined Network (FF-FRM-SDN) is implemented by making use of openflow-enabled switches and applying a disjoint path selection methodology producing the best failure recovery mechanism and to achieve the high probability of successful transmission. To conclude, if any fault or failure is detected in SDN, the proposed recovery approach minimizes available packet loss by making use of alternate paths and proactively form flow rules by using flow rules to reduce the failure recovery time. From the simulation results obtained, the proposed FF_FRM_SDN method achieves considerably improved results w.r.t parameters like Packet loss Ratio, End-to-End delay (transmission delay) and Failure recovery time as compared with the other traditional SDN baseline approaches.

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Ant Colony Optimization-based Dynamic Routing in Software Defined Networks

Cited by 15 publications

References 13 publications

A Comprehensive Survey on Knowledge-Defined Networking

A Comprehensive Survey on Knowledge-Defined Networking

Improving Data Delivery in Unreliable Networks Using Network Coding and Ant-Colony Optimization

A Fast Failover Technique for Link Failures and Proactive controller based Fault Recovery Mechanism in Software Defined Networks

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