Academic literature on the topic 'Spine-leaf architecture'

Rawa Singkil region of Conservation Forest Management Area (KPHK) is a sanctuary for fauna teeming with an abundance of plant species. The species diversity is predominantly constituted of rattan and other non-timber forest products. This investigation seeks to compile a list of the various species of rattan found in the Rawa Singkil KPHK region. Therefore, this study was carried out in the Rawa Singkil region of KPHK were located in the Aceh Singkil Regency of Aceh Province, Indonesia. Spanning an area of 82,374 ha, this territory comprises nearly fifty percent peat ecosystem. A survey is utilized as the research strategy, with data acquisition conducted via sampling techniques. Moreover, the acquired data were subjected to descriptive analysis on the basis of morphological attributes, encompassing the following morphological characteristics: 1) the stem (including characteristics such as height, diameter, color, internode length, and thorn shape); 2) the leaf, including its length, ocrea, leaf count, leaf color, and leaf surface; 3) knee (color and outline of the knee); 4) thorn; (spine color, length of longest spines, position of spines, and length of shortest spines). Eight species of rattan were discovered in this region, i.e Plectocomia elongata Mart., Daemonorops mattanensis Becc, Daemonorops melanochaetes, Korthalsia echinometra Becc, and Calamus ornatus Blume

Data center networks have undergone dramatic transformation in response to shifting technological landscapes and business requirements. This article examines how traditional hierarchical network designs have given way to more efficient, scalable architectures as organizations adapt to cloud computing paradigms, AI workloads, and distributed systems. The analysis covers the foundational elements of modern data center networks, from physical topology selection to advanced fabric designs, security segmentation methodologies, and automation frameworks. By closely looking at spine-leaf architectures, external BGP routing protocols, EVPN-VXLAN overlays, and detailed segmentation strategies, the article offers a plan for updating infrastructure. The thorough method for designing networks tackles important issues like performance, security, scalability, and efficiency that organizations encounter when creating infrastructure that can handle more complex tasks while staying strong and flexible in fast-changing technology environments.

The integration of edge-to-cloud infrastructures in smart grid (SG) data center networks requires scalable, efficient, and secure architecture. Traditional server-based SG data center architectures face high computational loads and delays. To address this problem, a lightweight data center network (DCN) with low-cost, and fast-converging optimization is required. This paper introduces a container-based time synchronization model (CTSM) within a spine–leaf virtual private cloud (SL-VPC), deployed via AWS CloudFormation stack as a practical use case. The CTSM optimizes resource utilization, security, and traffic management while reducing computational overhead. The model was benchmarked against five DCN topologies—DCell, Mesh, Skywalk, Dahu, and Ficonn—using Mininet simulations and a software-defined CloudFormation stack on an Amazon EC2 HPC testbed under realistic SG traffic patterns. The results show that CTSM achieved near-100% reliability, with the highest received energy data (29.87%), lowest packetization delay (13.11%), and highest traffic availability (70.85%). Stateless container engines improved resource allocation, reducing administrative overhead and enhancing grid stability. Software-defined Network (SDN)-driven adaptive routing and load balancing further optimized performance under dynamic demand conditions. These findings position CTSM-SL-VPC as a secure, scalable, and efficient solution for next-generation smart grid automation.