Proximity-driven social interactions and their impact on the throughput scaling of wireless networks

We present an analytical framework to investigate the interplay between a communication graph and an overlay of social  relationships.  We focus on geographical distance as the key element that interrelates the concept of routing in a communication network with the dynamics of interpersonal relations on the corresponding social graph. We identify  classes of social relationships that let the ensuing system  scale---i.e., accommodate a large number of users given only finite amount of resources. We establish that geographically concentrated communication patterns are indispensable to network scalability. We  further examine the impact of such proximity-driven interaction patterns on the throughput scaling of wireless networks, and show that, when social communications are geographically localized, the maximum per-node throughput scales approximately as $1/\log n$, which is significantly better than the well-known bound of $1/\sqrt{n \log n}$ for the uniform communication model

Mobility Pattern Recognition in Mobile Ad-Hoc Networks

ABSTRACT A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a self-configuring network without using any existing infrastructure. Network nodes in a mobile Ad-hoc network move in some motion patterns called mobility models. The mobility models play a very important role in determining the protocol performance in MANET. Thus, it is essential to study and analyze various mobility models and their effect on MANET protocols. If we can recognize the mobility pattern of motion of mobile nodes in our environment we can customize our network protocols to deal with that existing mobility model. In this paper we introduce a new method for classification and pattern recognition of mobility traces into mobility models in mobile Adhoc networks. This method uses a simple learning based classification method to recognize the existing mobility model in raw mobility traces which was collected from real motion of mobile Ad-hoc nodes or mobility traces generated by mobility simulators. Our simulation results prove ability of our proposed method to accurately classify given unknown mobility traces into various mobility models

A new approach to switch fabrics based on mini-router grids and output queueing

A number of switch fabric architectures based on mini-router grids (MRG) have been proposed as a replacement of buses for system-on-chip communication, as well as a replacement of crossbars for network routers. The rationale for using MRGs in switch fabrics is that they provide high delivery ratios, low latencies, high degree of parallelism and pipelining, load balancing properties, and sub-quadratic cost growth for their implementation. The traditional approaches to switch fabrics are based on input queuing (IQ) or virtual output queueing (VOQ), because output queuing (OQ) solutions to date are unscalable and expensive due to the speedup problem. However, we show that the speedup problem introduced by OQ can be bounded by 3 by using MRGs.We present the design of a switch fabric based on OQ MRGs that offers high delivery ratios, smaller queue sizes, and QoS guarantees. Queueing and scheduling are distributed over the MRs, where each MR is a pipestage, thus allowing MRGs to provide high throughput by nature. We present the first in-depth analytical model of switch fabric architectures based on OQ MRG, and support our model with register-transfer level (RTL) simulations in SystemC. The analytical and simulation results are shown to have close correlation over a range of design parameters and evaluation metrics

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Proximity-driven Social Interactions and Their Impact on the Throughput Scaling of Wireless Networks

We present an analytical framework to investigate the interplay between a communication graph and an overlay of social  relationships.  We focus on geographical distance as the key element that interrelates the concept of routing in a communication network with the dynamics of interpersonal relations on the corresponding social graph. We identify  classes of social relationships that let the ensuing system  scale---i.e., accommodate a large number of users given only finite amount of resources. We establish that geographically concentrated communication patterns are indispensable to network scalability. We  further examine the impact of such proximity-driven interaction patterns on the throughput scaling of wireless networks, and show that, when social communications are geographically localized, the maximum per-node throughput scales approximately as $1/\log n$, which is significantly better than the well-known bound of $1/\sqrt{n \log n}$ for the uniform communication model

CSIR: Cellular scheduling with Interest-driven Routing

CSIR (Cellular Scheduling with Interest-driven Routing) is proposed for the effective dissemination of real-time and elastic traffic in wireless ad-hoc networks. CSIR is a novel cross-layer framework consisting of five components: flow-based priority queuing of packets, distributed interest-based routing, distributed transmission scheduling, a neighbor protocol, and bandwidth reservations. Nodes are scheduled for transmission in coordination with the routes established and the end-to-end delay and bandwidth requirements of the flows. Most of the signaling overhead for active flows is confined to the nodes that are required to maintain them. Results from detailed simulations indicate that, compared to a protocol stack consisting of IEEE 802.11e for channel access, AODV and OLSR for unicast routing, and ODMRP for multicast routing, CSIR attains much better performance in terms of packet delivery and end-to-end delay for elastic and real-time unicast and multicast traffic

Understanding Optimal Caching and Opportunistic Caching at “The Edge” of Information-Centric Networks

A formal framework is presented for the characterization of cache allocation models in Information-Centric Networks (ICN). The framework is used to compare the performance of optimal caching everywhere in an ICN with opportunistic caching of content only near its consumers. This comparison is made using the independent reference model adopted in all prior studies, as well as a new model that captures non-stationary reference locality in space and time. The results obtained analytically and from simulations show that optimal caching throughout an ICN and opportunistic caching at the edge routers of an ICN perform comparably the same. In addition, caching content opportunistically only near its consumers is shown to outperform the traditional on-path caching approach assumed in most ICN architectures in an unstructured network with arbitrary topology represented as a random geometric graph