RMD-QOSM - The Resource Management in Diffserv QoS model

This document describes an NSIS QoS Model for networks that use the Resource Management in Diffserv (RMD) concept. RMD is a technique for adding admission control and preemption function to Differentiated Services (Diffserv) networks. The RMD QoS Model allows devices external to the RMD network to signal reservation requests to edge nodes in the RMD network. The RMD Ingress edge nodes classify the incoming flows into traffic classes and signals resource requests for the corresponding traffic class along the data path to the Egress edge nodes for each flow. Egress nodes reconstitute the original requests and continue forwarding them along the data path towards the final destination. In addition, RMD defines notification functions to indicate overload situations within the domain to the edge nodes

Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability

Internet-of-Things (IoT) envisions an intelligent infrastructure of networked smart devices offering task-specific monitoring and control services. The unique features of IoT include extreme heterogeneity, massive number of devices, and unpredictable dynamics partially due to human interaction. These call for foundational innovations in network design and management. Ideally, it should allow efficient adaptation to changing environments, and low-cost implementation scalable to massive number of devices, subject to stringent latency constraints. To this end, the overarching goal of this paper is to outline a unified framework for online learning and management policies in IoT through joint advances in communication, networking, learning, and optimization. From the network architecture vantage point, the unified framework leverages a promising fog architecture that enables smart devices to have proximity access to cloud functionalities at the network edge, along the cloud-to-things continuum. From the algorithmic perspective, key innovations target online approaches adaptive to different degrees of nonstationarity in IoT dynamics, and their scalable model-free implementation under limited feedback that motivates blind or bandit approaches. The proposed framework aspires to offer a stepping stone that leads to systematic designs and analysis of task-specific learning and management schemes for IoT, along with a host of new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive and Scalable Communication Network

Peer-to-Peer Communication Across Network Address Translators

Network Address Translation (NAT) causes well-known difficulties for peer-to-peer (P2P) communication, since the peers involved may not be reachable at any globally valid IP address. Several NAT traversal techniques are known, but their documentation is slim, and data about their robustness or relative merits is slimmer. This paper documents and analyzes one of the simplest but most robust and practical NAT traversal techniques, commonly known as "hole punching." Hole punching is moderately well-understood for UDP communication, but we show how it can be reliably used to set up peer-to-peer TCP streams as well. After gathering data on the reliability of this technique on a wide variety of deployed NATs, we find that about 82% of the NATs tested support hole punching for UDP, and about 64% support hole punching for TCP streams. As NAT vendors become increasingly conscious of the needs of important P2P applications such as Voice over IP and online gaming protocols, support for hole punching is likely to increase in the future.Comment: 8 figures, 1 tabl