80 research outputs found

    Anycast on the Move: A Look at Mobile Anycast Performance

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    International audienceThe appeal and clear operational and economic benefits of anycast to service providers have motivated a number of recent experimental studies on its potential performance impact for end users. For CDNs on mobile networks, in particular, anycast provides a simpler alternative to existing routing systems challenged by a growing, complex, and commonly opaque cellular infrastructure. This paper presents the first analysis of anycast performance for mobile users. In particular, our evaluation focuses on two distinct anycast services, both providing part of the DNS Root zone and together covering all major geographical regions. Our results show that mobile clients tend to be routed to suboptimal replicas in terms of geographical distance, more frequently while on a cellular connection than on WiFi, with a significant impact on latency. We find that this is not simply an issue of lacking better alternatives, and that the problem is not specific to particular geographic areas or autonomous systems. We close with a first analysis of the root causes of this phenomenon and describe some of the major classes of anycast anomalies revealed during our study, additionally including a systematic approach to automatically detect such anomalies without any sort of training or annotated measurements. We release our datasets to the networking community

    VAPR: Void Aware Pressure Routing for Underwater Sensor Networks

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    Abstract-Underwater mobile sensor networks have recently been proposed as a way to explore and observe the ocean, providing 4D (space and time) monitoring of underwater environments. We consider a specialized geographic routing problem called pressure routing that directs a packet to any sonobuoy on the surface based on depth information available from on-board pressure gauges. The main challenge of pressure routing in sparse underwater networks has been the efficient handling of 3D voids. In this respect, it was recently proven that the greedy stateless perimeter routing method, very popular in 2D networks, cannot be extended to void recovery in 3D networks. Available heuristics for 3D void recovery require expensive flooding. In this paper, we propose a Void Aware Pressure Routing (VAPR) protocol that uses sequence number, hop count and depth information embedded in periodic beacons to set up next-hop direction and to build a directional trail to the closest sonobuoy. Using this trail, opportunistic directional forwarding can be efficiently performed even in the presence of voids. The contribution of this paper is two-fold: (1) a robust soft-state routing protocol that supports opportunistic directional forwarding; and (2) a new framework to attain loop freedom in static and mobile underwater networks to guarantee packet delivery. Extensive simulation results show that VAPR outperforms existing solutions

    Survey of Transportation of Adaptive Multimedia Streaming service in Internet

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    [DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; García-García, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

    Latency-driven replication for globally distributed systems

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    Steen, M.R. van [Promotor]Pierre, G.E.O. [Copromotor

    Routing Protocols for Underwater Acoustic Sensor Networks: A Survey from an Application Perspective

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    Underwater acoustic communications are different from terrestrial radio communications; acoustic channel is asymmetric and has large and variable end‐to‐end propagation delays, distance‐dependent limited bandwidth, high bit error rates, and multi‐path fading. Besides, nodes’ mobility and limited battery power also cause problems for networking protocol design. Among them, routing in underwater acoustic networks is a challenging task, and many protocols have been proposed. In this chapter, we first classify the routing protocols according to application scenarios, which are classified according to the number of sinks that an underwater acoustic sensor network (UASN) may use, namely single‐sink, multi‐sink, and no‐sink. We review some typical routing strategies proposed for these application scenarios, such as cross‐layer and reinforcement learning as well as opportunistic routing. Finally, some remaining key issues are highlighted

    Self-organized backpressure routing for the wireless mesh backhaul of small cells

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    The ever increasing demand for wireless data services has given a starring role to dense small cell (SC) deployments for mobile networks, as increasing frequency re-use by reducing cell size has historically been the most effective and simple way to increase capacity. Such densification entails challenges at the Transport Network Layer (TNL), which carries packets throughout the network, since hard-wired deployments of small cells prove to be cost-unfeasible and inflexible in some scenarios. The goal of this thesis is, precisely, to provide cost-effective and dynamic solutions for the TNL that drastically improve the performance of dense and semi-planned SC deployments. One approach to decrease costs and augment the dynamicity at the TNL is the creation of a wireless mesh backhaul amongst SCs to carry control and data plane traffic towards/from the core network. Unfortunately, these lowcost SC deployments preclude the use of current TNL routing approaches such as Multiprotocol Label Switching Traffic Profile (MPLS-TP), which was originally designed for hard-wired SC deployments. In particular, one of the main problems is that these schemes are unable to provide an even network resource consumption, which in wireless environments can lead to a substantial degradation of key network performance metrics for Mobile Network Operators. The equivalent of distributing load across resources in SC deployments is making better use of available paths, and so exploiting the capacity offered by the wireless mesh backhaul formed amongst SCs. To tackle such uneven consumption of network resources, this thesis presents the design, implementation, and extensive evaluation of a self-organized backpressure routing protocol explicitly designed for the wireless mesh backhaul formed amongst the wireless links of SCs. Whilst backpressure routing in theory promises throughput optimality, its implementation complexity introduces several concerns, such as scalability, large end-to-end latencies, and centralization of all the network state. To address these issues, we present a throughput suboptimal yet scalable, decentralized, low-overhead, and low-complexity backpressure routing scheme. More specifically, the contributions in this thesis can be summarized as follows: We formulate the routing problem for the wireless mesh backhaul from a stochastic network optimization perspective, and solve the network optimization problem using the Lyapunov-driftplus-penalty method. The Lyapunov drift refers to the difference of queue backlogs in the network between different time instants, whereas the penalty refers to the routing cost incurred by some network utility parameter to optimize. In our case, this parameter is based on minimizing the length of the path taken by packets to reach their intended destination. Rather than building routing tables, we leverage geolocation information as a key component to complement the minimization of the Lyapunov drift in a decentralized way. In fact, we observed that the combination of both components helps to mitigate backpressure limitations (e.g., scalability,centralization, and large end-to-end latencies). The drift-plus-penalty method uses a tunable optimization parameter that weight the relative importance of queue drift and routing cost. We find evidence that, in fact, this optimization parameter impacts the overall network performance. In light of this observation, we propose a self-organized controller based on locally available information and in the current packet being routed to tune such an optimization parameter under dynamic traffic demands. Thus, the goal of this heuristically built controller is to maintain the best trade-off between the Lyapunov drift and the penalty function to take into account the dynamic nature of semi-planned SC deployments. We propose low complexity heuristics to address problems that appear under different wireless mesh backhaul scenarios and conditions..
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