Software-Defined Networking: Categories, Analysis, and Future Directions

Hussain, Mudassar; Shah, Nadir; Amin, Rashid; Alshamrani, Sultan S.; Alotaibi, Aziz; Raza, Syed Mohsan

doi:10.3390/s22155551

Cited by 29 publications

(11 citation statements)

References 193 publications

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“…This topology consists of a set of ingress nodes, intermediate nodes, and the egress node that connects the edge domain to the content producer, known as the server. The edge domain establishes out-of-band communication with the SDN-controller, referred to as the ‘HyperFlow controller’ ( Hussain et al, 2022 ), through implementing a C++ programming technique. The controller is integrated into the caching devices by transforming the NDN switches into OpenFlow switches, achieved by enabling the software package known as ‘OFSwitch version 1.3’ ( Unicamp, 2023 ).…”

Section: Resultsmentioning

confidence: 99%

Controller-driven vector autoregression model for predicting content popularity in programmable named data networking devices

Qaiser,

Hussain,

Ahad

et al. 2024

PeerJ Computer Science

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Named Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networking (SDN) controller to optimize the placement of highly popular content in NDN nodes. The optimization process considers critical networking factors, including network congestion, security, topology modification, and flowrules alterations, which are essential for shaping content caching strategies. The article presents a novel content caching framework, Popularity-aware Caching in Popular Programmable NDN nodes (PaCPn). Employing a multi-variant vector autoregression (VAR) model driven by an SDN controller, PaCPn periodically updates content popularity based on time-series data, including ‘request rates’ and ‘past popularity’. It also introduces a controller-driven heuristic algorithm that evaluates the proximity of caching points to consumers, considering factors such as ‘distance cost,’ ‘delivery time,’ and the specific ‘status of the requested content’. PaCPn utilizes customized DATA named packets to ensure the source stores content with a valid residual freshness period while preventing intermediate nodes from caching it. The experimental results demonstrate significant improvements achieved by the proposed technique PaCPn compared to existing schemes. Specifically, the technique enhances cache hit rates by 20% across various metrics, including cache size, Zipf parameter, and exchanged traffic within edge infrastructure. Moreover, it reduces content retrieval delays by 28%, considering metrics such as cache capacity, the number of consumers, and network throughput. This research advances NDN content caching and offers potential optimizations for edge infrastructures.

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Section: Resultsmentioning

confidence: 99%

Controller-driven vector autoregression model for predicting content popularity in programmable named data networking devices

Qaiser,

Hussain,

Ahad

et al. 2024

PeerJ Computer Science

Self Cite

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“…Assuming that vehicles select a slice for offloading, the transmitted power is set to a maximum value. One access point AP, the deadline τ i of the task is large enough, γ 1 , γ 2 represent the average number of vehicles distributed equally, and allocate wireless resource ρ l i,j and computing resources λ l i to vehicles, ρ l i,j = 1/γ 1 , λ l i = 1/γ 2 in Equation (15), and the energy consumption E l, * i can be expressed as:…”

Section: Optimization Objectivesmentioning

confidence: 99%

“…Most of the current offloading algorithms focus on leveraging Network Function Virtualization (NFV) and Software Defined Network (SDN) technologies to minimize the delay and energy consumption associated with task offloading [14,15]. However, these algorithms seldom consider the dependencies between tasks dependencies.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Selection Slicing-Based Offloading Algorithm for In-Vehicle Tasks in Mobile Edge Computing

et al. 2023

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With the surge in tasks for in-vehicle terminals, the resulting network congestion and time delay cannot meet the service needs of users. Offloading algorithms are introduced to handle vehicular tasks, which will greatly improve the above problems. In this paper, the dependencies of vehicular tasks are represented as directed acyclic graphs, and network slices are integrated within the edge server. The Dynamic Selection Slicing-based Offloading Algorithm for in-vehicle tasks in MEC (DSSO) is proposed. First, a computational offloading model for vehicular tasks is established based on available resources, wireless channel state, and vehicle loading level. Second, the solution of the model is transformed into a Markov decision process, and the combination of the DQN algorithm and Dueling Network from deep reinforcement learning is used to select the appropriate slices and dynamically update the optimal offloading strategy for in-vehicle tasks in the effective interval. Finally, an experimental environment is set up to compare the DSSO algorithm with LOCAL, MINCO, and DJROM, the results show that the system energy consumption of DSSO algorithm resources is reduced by 10.31%, the time latency is decreased by 22.75%, and the ratio of dropped tasks is decreased by 28.71%.

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“…There have been several proposals for reducing security assaults in SFC based on probes, flow statistics, hop-by-hop tag verification, etc. The probe-based process 12 injects probe packets into networks and verifies their integrity to validate the service path. Instead, the flow-statistic-based technique gathers and compares all the statistics from network components to identify statistical inconsistencies.…”

Section: Related Workmentioning

confidence: 99%

Developing an SDN security model (EnsureS) based on lightweight service path validation with batch hashing and tag verification

Pradeep,

Sharma,

Lilhore

et al. 2023

Sci Rep

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Software-defined networking (SDN) has significantly transformed the field of network management through the consolidation of control and provision of enhanced adaptability. However, this paradigm shift has concurrently presented novel security concerns. The preservation of service path integrity holds significant importance within SDN environments due to the potential for malevolent entities to exploit network flows, resulting in a range of security breaches. This research paper introduces a model called "EnsureS", which aims to enhance the security of SDN by proposing an efficient and secure service path validation approach. The proposed approach utilizes a Lightweight Service Path Validation using Batch Hashing and Tag Verification, focusing on improving service path validation's efficiency and security in SDN environments. The proposed EnsureS system utilizes two primary techniques in order to validate service pathways efficiently. Firstly, the method utilizes batch hashing in order to minimize computational overhead. The proposed EnsureS algorithm enhances performance by aggregating packets through batches rather than independently; the hashing process takes place on each one in the service pathway. Additionally, the implementation of tag verification enables network devices to efficiently verify the authenticity of packets by leveraging pre-established trust relationships. EnsureS provides a streamlined and effective approach for validating service paths in SDN environments by integrating these methodologies. In order to assess the efficacy of the Proposed EnsureS, a comprehensive series of investigations were conducted within a simulated SDN circumstance. The efficacy of Proposed EnsureS was then compared to that of established methods. The findings of our study indicate that the proposed EnsureS solution effectively minimizes computational overhead without compromising on the established security standards. The implementation successfully reduces the impact of different types of attacks, such as route alteration and packet spoofing, increasing SDN networks' general integrity.

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Software-Defined Networking: Categories, Analysis, and Future Directions

Cited by 29 publications

References 193 publications

Controller-driven vector autoregression model for predicting content popularity in programmable named data networking devices

Controller-driven vector autoregression model for predicting content popularity in programmable named data networking devices

Dynamic Selection Slicing-Based Offloading Algorithm for In-Vehicle Tasks in Mobile Edge Computing

Developing an SDN security model (EnsureS) based on lightweight service path validation with batch hashing and tag verification

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