Abstract

Part 6: New Testing Methods; International audience; In this paper, we focus on Mobile Ad-hoc Networks (MANETs) with non-uniform node density distribution such as Vehicular Ad-hoc Networks (VANETs) and Delay Tolerant Networks (DTNs), and propose a technique for protocol testing and performance evaluation. In such MANETs, node density varies depending on locations and time, and it dynamically changes every moment. In the proposed method, we designate node density distributions and their dynamic variations in a target area. Then, we construct a graph called TestEnvGraph where all node density distributions are treated as its nodes and they are connected by edges whose weights denote differences of two node density distributions. We specify a set of edges to be tested in the graph, formulate a problem for efficiently reproducing all the given node density distributions and their dynamic variations as a rural postman problem, find its solution and use it as the order of reproduction of designated node density distributions and their variations. Protocol testing is carried out by reproducing node density distributions in the derived order. We have designed and developed a method and its tool for mobility generation on MANETs, which can reproduce any designated node density distribution and its dynamic variations in a target area. From our experiments for a VANET protocol, we have shown that our method can give a similar trend in network throughput and packet loss rates compared with realistic trace based protocol testing. Document type: Part of book or chapter of book

Abstract

In order to meet a tremendous amount of data storage requirement in next-generation wireless networks, an increasing number of cloud data centers has been deployed around the world. The underlying core networks are expected to provide the ability to store data in a dynamic and scalable computing environment. The traditional Internet Protocol (IP) has shown to be restricted due to its static architecture, which accordingly motivates the development of Software-Defined Networks (SDNs). In the SDNs, Traffic Engineering (TE) is simpler and programmable with a controller without the requirement of reconfiguration for all network devices. However, the existing TE algorithm of the SDNs rejects a number of requested flows caused by their undetermined routing paths where only flow bandwidth is considered in path determination. This paper proposes a Quality-of-Service (QoS) based Flow Assignment algorithm which enables the computation of end-to-end path for traffic flows guaranteeing the QoS requirements including bandwidth, end-to-end delay and packet loss probability. Through the Open Source Hybrid IP/SDNs platform, the proposed algorithm is validated and shown to significantly reduce flow rejection rate of up to 50% compared to the conventional approach, and therefore can be used to implement an effective DiffServ mechanism for flow allocation in the SDNs. Document type: Part of book or chapter of book

Abstract

We show that the “fractal” behavior of Internet traffic can be efficiently and practically employed to significantly reduce packet-loss. Thanks to recent advances in the theory of self-similar processes, we define the probabilistic congestion of a link, based on an estimated computation of the packet-loss probability over that link. This congestion parameter allows valid predictions on the future behavior of the network, on which one can base efficient routing strategies. We show how to implement the computation of the probabilistic congestion, and we illustrate several applications for improving unicast and multicast protocols. Document type: Part of book or chapter of book

Abstract

Most prior work on congestion in datagram systems focuses on buffer management. We find it illuminating to consider the case of a packet switch with infinite storage. Such a packet switch can never run out of buffers. It can, however, still become congested. The meaning of congestion in an infinite-storage system is explored. We demonstrate the unexpected result that a datagram network with infinite storage, first-in, first-out queueing, at least two packet switches, and a finite packet lifetime will, under overload, drop all packets. By attacking the problem of congestion for the infinite-storage case, we discover new solutions applicable to switches with finite storage. Document type: Report

Abstract

Network operators have recently been developing multi-Gbps traffic monitoring tools that execute on commodity hardware and are part of the packet-processing pipelines realizing software dataplanes. These solutions allow sophisticated tasks to be performed on a per-packet basis, without relying on sampling or passive trace analysis, by leveraging the processing power available on servers. Although advances in packet capture have enabled intercepting packets from network cards at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive traffic monitoring approach that copes with emerging bottlenecks by timely detecting changes in the operational conditions and reconfiguring monitoring-related operations for subsets of traffic flows. Our solution performs responsive adaptations at the time scale of milliseconds and does not require a significant amount of resources. To demonstrate the capabilities of our approach we implemented it as part of a generic packet-processing pipeline and show that lossless traffic monitoring can be achieved for a wide range of conditions.