Aug 2026· Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi· 0 citations· 36 references
TL;DR
A two-stage framework that combines graph-theoretic optimization with empirical device-level measurements to inform sustainable campus network design is developed and indicates that device-specific characteristics play a crucial role in determining actual energy efficiency.
Abstract
The digitalization of university campuses has intensified the need for reliable, energy-efficient, and sustainable network infrastructures. While Wi-Fi systems offer flexibility and ease of deployment, their long-term energy footprint often exceeds that of wired alternatives. Conversely, Ethernet networks, though more stable and efficient, require careful optimization to reduce installation costs and material use. This study develops a two-stage framework that combines graph-theoretic optimization with empirical device-level measurements to inform sustainable campus network design.In the first phase, the physical network layout was modeled as a Minimum Spanning Tree (MST) using the Manhattan distance metric to reflect realistic in-building cable routing. The MST was solved via Kruskal’s algorithm and validated through a mixed-integer programming model implemented in Gurobi, yielding a total cable length of 1,435.69 metres and a 63.4% reduction in total cable length—implying comparable savings in material and installation costs—compared with a naive layout. In the second phase, an experimental analysis examined the energy consumption of Wi-Fi, native Ethernet, and Ethernet-adapter connections across multiple devices. Although the paired t-tests revealed no statistically significant differences at the 95% confidence level, the results indicate that device-specific characteristics play a crucial role in determining actual energy efficiency.Overall, the findings underscore the importance of integrating optimization and empirical evaluation in sustainable network planning. The proposed framework not only supports cost-efficient infrastructure decisions but also contributes to the broader goal of reducing the carbon footprint of digital campuses.
This thesis provides an end-to-end mathematical and machine learning framework for designing dependable, low-latency, and scalable SDN infrastructures.
The proposed SPN model enables system architects to compare routing configurations, identify performance bottlenecks, and size infrastructure components without requiring physical deployment, and enables the identification of communication bottlenecks without requiring physical deployment.
José Miquéias Araújo, L. Lopes, Luiz Nelson Lima et al.· Journal of Internet Services...· 0 citations
The demand for Low-earth-orbit (LEO) satellite networking and routing is continuously growing. Container-based satellite network emulation becomes an important networking evaluation choice for LEO satellite network. While many container-based satellite network emulators optimize virtual network efficiency, they often overlook route installation latency—the duration of installing computed routes into kernel routing table. This latency represents a significant bottleneck for emulating large-scale LEO constellations, which are characterized by dynamic topologies and frequent, massive routing re-convergences. High routing installation latency not only reduces emulation efficiency but also compromises evaluation reliability and renders subsequent data transmission experiments infeasible. In this paper, we present a Lock-Free and Filtered Route Installation (LFRI) mechanism. LFRI filters out non-effective route installations, thereby shortening the installation procedure without changing the routing results. LFRI employs a lock-free installation mechanism that enables parallelized and efficient route installation. Experimental results demonstrate that, compared to the legacy Netlink installation, LFRI reduces the route installation latency by up to 99.9% in emulations of typical LEO satellite constellations, bringing it down to under ten milliseconds, within a performance level comparable to routing installation on physical machines. Meanwhile, in the case study evaluating path availability ratio and restoration time, LFRI yields more consistent and credible experimental data.
Wenhao Lu, Zhiyuan Wang, Shan Zhang et al.· Asia-Pacific Workshop on Net...· 0 citations
A novel cluster-based routing protocol that integrates a Fungal Growth Optimizer for adaptive cluster head (CH) selection and a Graph Neural Network for inter-cluster routing, which demonstrates FGOGNN’s potential for deployment in real-time WSN applications, where energy efficiency and dynamic adaptability are paramount.
Huang-shui Hu, Shuo Liu, Qier Kang et al.· Symmetry· 1 citation
Wireless Mesh Networks (WMNs) are a key enabling technology for dynamic, infrastructure-limited IoT environments. The routing protocol is the central design choice in any WMN deployment because throughput, end-to-end delay, energy consumption and delivery reliability are directly affected by it. A systematic, simulation-based evaluation of two widely studied WMN routing protocols is presented: the reactive Ad hoc On-Demand Distance Vector (AODV, RFC 3561) protocol and the proactive Destination-Sequenced Distance-Vector (DSDV) protocol. Simulations were conducted in OMNeT++ 6.3 with the INET 4.5 framework across five network densities $(N \in\{10,20,30,40,50\}$ nodes) in a $1000 ~\mathrm{m} \times 1000 ~\mathrm{m}$ IEEE 802.11g area with a many-to-one UDP traffic pattern representative of IoT data collection. A density-dependent crossover was revealed at approximately $N=20$: lower delay was achieved by DSDV in sparse networks, whereas higher throughput, higher delivery reliability and lower energy consumption were achieved by AODV at higher densities. At $N=50, \approx 35 \%$ higher throughput, zero routing failures and $\approx 8 \%$ lower energy consumption are delivered by AODV. It is indicated by the MAC-layer contention behavior that DSDV's high-density degradation is mainly driven by IEEE 802.11 channel saturation rather than by routing-algorithm deficiencies. Deployment guidelines derived from these findings are provided.
Alá F. Khalifeh, Abdulla Ababneh, Iacovos I. Ioannou· IEEE Jordan Conference on Ap...· 0 citations
This research Paper focuses on an Ultra-Dense Network (UDN) is a core enabling technology for 5G and 6G wireless systems, proposed to meet escalating capacity demands and support new high-rate, low-latency services. The fundamental principle is network densification, achieved by deploying a massive number of low-power Access Points (APs) and communication links per unit area, dramatically shortening the distance between transmitters and receivers to improve signal quality and spatial frequency reuse. Ultimately, the successful operation of UDNs relies heavily on advanced, AI-driven management systems to dynamically optimize resources, manage interference, and ensure seamless, high-performance connectivity in an inherently complex environment: Our key objectives are improving the Massive Capacity and Data Rates, Enhanced Coverage and Reliability, Ultra-Low Latency, Massive Connectivity Internet of Things (IoT) to maintaining the advanced resilient communication system all the time and every times.
P. Pradhan, Pramod D Gangejar· Journal of Ad-hoc Network an...· 0 citations
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