In this paper, we discuss the current situation with respect to simulation usage in P2P research, testing the available P2P simulators against a proposed set of requirements, and surveying over 280 papers to discover what simulators are already being used. We found that no simulator currently meets all our requirements, and that simulation results are generally reported in the literature in a fashion that precludes any reproduction of results. We hope that this paper will give rise to further discussion and knowledge sharing among those of the P2P and network simulation research communities, so that a simulator that meets the needs of rigorous P2P research can be developed
Abstract-Modern data centres provide large aggregate network capacity and multiple paths among servers. Traffic is very diverse; most of the data is produced by long, bandwidth hungry flows but the large majority of flows, which commonly come with strict deadlines regarding their completion time, are short. It has been shown that TCP is not efficient for any of these types of traffic in modern data centres. More recent protocols such MultiPath TCP (MPTCP) are very efficient for long flows, but are ill-suited for short flows.In this paper, we present AMPTCP, a novel transport protocol which, compared to TCP and MPTCP, reduces short flows' completion times, while providing excellent goodput to long flows. To do so, AMPTCP runs in two phases; initially, it randomly scatters packets in the network under a single congestion window exploiting all available paths. This is beneficial to latency-sensitive flows. After a specific amount of data is sent, AMPTCP switches to a regular MultiPath TCP mode. AMPTCP is incrementally deployable in existing data centres as it does not require any modifications outside the transport layer and behaves well when competing with legacy TCP and MPTCP flows. Our extensive experimental evaluation in simulated FatTree topologies shows that all design objectives for AMPTCP are met.
We describe a mechanism for scalable control of multicast continuous media streams. The mechanism uses a novel probing mechanism to solicit feedback information in a scalable manner and to estimate the number of receivers. In addition, it separates the congestion signal from the congestion control algorithm, so as to cope with heterogeneous networks. This mechanism has been implemented in the IVS video conference system using options within RTP to elicit information about the quality of the video delivered to the receivers. The H.261 coder of IVS then uses this information to adjust its output rate, the goal being to maximize the perceptual quality of the image received at the destinations while minimizing the bandwidth used by the video transmission. We find that our prototype control mechanism is well suited to the Internet environment. Furthermore, it prevents video sources from creating congestion in the Internet. Experiments are underway to investigate how the scalable proving mechanism can be used to facilitate multicast video distribution to large number of participants.
Abstract-Understanding which node failures in a network have more impact is an important problem. Current understanding, motivated by the scale free models of network growth, places emphasis on the degree of the node. This is not a satisfactory measure; the number of connections a node has does not capture how redundantly it is connected into the whole network. Conversely, the structural entropy of a graph captures the resilience of a network well, but is expensive to compute, and, being a global measure, does not attribute any specific value to a given node. This lack of locality prevents the use of global measures as a way of identifying critical nodes. In this paper we introduce local vertex measures of entropy which do not suffer from such drawbacks. In our theoretical analysis we establish the possibility that our local vertex measures approximate global entropy, with the advantage of locality and ease of computation. We establish properties that vertex entropy must have in order to be useful for identifying critical nodes. We have access to a proprietary event, topology and incident dataset from a large commercial network. Using this dataset, we demonstrate a strong correlation between vertex entropy and incident generation over events.
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