Disjoint Multipath QoS (quality of service) Routing algorithm is aimed at selecting multiple paths for a flow in a peer to peer network, which are mutually disjoint w.r.t. bottleneck links. The Widest Disjoint Paths (WDP) algorithm [3][4] assumes a static set of available paths for each source-destination pair a priori, from which disjoint paths w.r.t. bottleneck links are selected. The Shortest Widest Path (SWP) algorithm [9] dynamically determines one path for each source-destination pair, which is shortest among widest ones. The proposed Disjoint Multipath QoS Routing algorithm dynamically finds paths mutually disjoint w.r.t. bottleneck links, which are shortest among widest ones. Thus, the algorithm generalizes both WDP and SWP algorithms.In many important multimedia applications such as video over IP in telehealth application, the application-and network-layer must collaborate in order to provide some necessary QoS guarantee. The network-layer should provide certain level of QoS measures, based on which the application-layer is able to compensate for deficiency of achieved QoS level. Those QoS measures may include end-to-end bandwidth, delay and packet loss rate, etc. The Disjoint Multipath QoS Routing algorithm is designed to achieve certain QoS level the application-layer can easily work with. In this paper, we only deal with the network-layer part and will focus on a scenario of one source and one destination. Simulation results and performance analysis demonstrate that the algorithm converges, offers lower end-to-end packet loss rate and higher throughput in comparison with SWP and Dijkstra Shortest Path algorithm as network traffic grows.
Abstract. Widest Disjoint Paths (WDP) algorithm is a promising multipath routing algorithm aimed at selecting good paths for routing a flow between a source-destination pair, where their bottleneck links are mutually disjoint. Nevertheless, the complexity of WDP algorithm is relatively high due to the fact that the good path selection process considers all available paths. To reduce its complexity, This paper proposes a modified WDP algorithm, which uses only a subset of available paths based on shortest widest paths, thereby limiting the number of candidate paths considered. As a result, the number of iterations in the good path selection process is significantly reduced. Performance analysis shows the modified scheme is more efficient than the original algorithm in a large network. Simulation results demonstrate that, in comparison with the original WDP algorithm, the modified WDP algorithm leads to lower latency and faster packets transferring process as the number of available paths increases.
Understanding the regional propensity differences of atherosclerosis (AS) development is hindered by the lack of animal models suitable for the study of the disease process. In this paper, we used 3S-ASCVD dogs, an ideal large animal human-like models for AS, to interrogate the heterogeneity of AS-prone and AS-resistant arteries; and at the single-cell level, identify the dominant cells involved in AS development. Here we present data from 3S-ASCVD dogs which reliably mimic human AS pathophysiology, predilection for lesion sites, and endpoint events. Our analysis combined bulk RNA-seq with single-cell RNA-seq to depict the transcriptomic profiles and cellular atlas of AS-prone and AS-resistant arteries in 3S-ASCVD dogs. Our results revealed the integral role of smooth muscle cells (SMCs) in regional propensity for AS. Notably, TNC + SMCs were major contributors to AS development in 3S-ASCVD dogs, indicating enhanced extracellular matrix remodeling and transition to myofibroblasts during the AS process. Moreover, TNC + SMCs were also present in human AS-prone carotid plaques, suggesting a potential origin of myofibroblasts and supporting the relevance of our findings. Our study provides a promising large animal model for pre-clinical studies of ASCVD and add novel insights surrounding the regional propensity of AS development in humans, which may lead to interventions that delay or prevent lesion progression and adverse clinical events.
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