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We design throughput-optimal dynamic broadcast algorithms for multi-hop networks with arbitrary topologies. Most of the previous broadcast algorithms route packets along spanning trees. For large time-varying networks, computing and maintaining a set of spanning trees is not efficient, as the network-topology may change frequently. In this paper, we design a class of dynamic algorithms, which make simple packet-by-packet scheduling and routing decisions, and hence obviate the need for maintaining any global topological structures, such as spanning trees. Our algorithms may be conveniently understood as a non-trivial generalization of the familiar back-pressure algorithm for unicast traffic, which performs packet routing and scheduling based on queue lengths. However, in the broadcast setting, due to packet duplications, it is difficult to define appropriate queuing structures. We design and prove the optimality of a virtual queue-based algorithm, where virtual queues are defined for subsets of nodes. We then propose a multi-class broadcast policy, which combines the above scheduling algorithm with in-class-in-order packet forwarding, resulting in significant reduction in complexity. Finally, we evaluate the performance of the proposed algorithms via extensive numerical simulations. [ABSTRACT FROM PUBLISHER]

Legacy networks are often designed to operate with simple single-path routing, like the shortest path, which is known to be throughput suboptimal. On the other hand, previously proposed throughput optimal policies (i.e., backpressure) require every device in the network to make dynamic routing decisions. In this paper, we study an overlay architecture for dynamic routing, such that only a subset of devices (overlay nodes) need to make the dynamic routing decisions. We determine the essential collection of nodes that must bifurcate traffic for achieving the maximum multi-commodity network throughput. We apply our optimal node placement algorithm to several graphs and the results show that a small fraction of overlay nodes is sufficient for achieving maximum throughput. Finally, we propose a threshold-based policy (BP-T) and a heuristic policy (OBP), which dynamically control traffic bifurcations at overlay nodes. Policy BP-T is proved to maximize throughput for the case when underlay paths do no overlap. In all studied simulation scenarios, OBP not only achieves full throughput but also reduces delay in comparison to the throughput optimal backpressure routing. [ABSTRACT FROM PUBLISHER]

Network switches and routers need to serve packet writes and reads at rates that challenge the most advanced memory technologies. As a result, scaling the switching rates is commonly done by parallelizing the packet I/Os using multiple memory units. For improved read rates, packets can be coded upon write, thus giving more flexibility at read time to achieve higher utilization of the memory units. This paper presents a detailed study of coded network switches, and in particular, how to design them to maximize the throughput advantages over standard uncoded switches. Toward that objective, the paper contributes a variety of algorithmic and analytical tools to improve and evaluate the throughput performance. The most interesting finding of this paper is that the placement of packets in the switch memory is the key to both high performance and algorithmic efficiency. One particular placement policy we call “design placement” is shown to enjoy the best combination of throughput performance and implementation feasibility. [ABSTRACT FROM PUBLISHER]

This paper investigates the problem of finding optimal paths in single-source single-destination accumulative multi-hop networks. We consider a single source that communicates to a single destination assisted by several relays through multiple hops. At each hop, only one node transmits, while all the other nodes receive the transmitted signal, and store it after processing/decoding and mixing it with the signals received in previous hops. That is, we consider that terminals make use of advanced energy accumulation transmission/reception techniques, such as maximal ratio combining reception of repetition codes, or information accumulation with rateless codes. Accumulative techniques increase communication reliability, reduce energy consumption, and decrease latency. We investigate the properties that a routing metric must satisfy in these accumulative networks to guarantee that optimal paths can be computed with Dijkstra’s algorithm. We model the problem of routing in accumulative multi-hop networks, as the problem of routing in a hypergraph. We show that optimality properties in a traditional multi-hop network (monotonicity and isotonicity) are no longer useful and derive a new set of sufficient conditions for optimality. We illustrate these results by studying the minimum energy routing problem in static accumulative multi-hop networks for different forwarding strategies at relays. [ABSTRACT FROM PUBLISHER]

Forwarding decisions in classical IP-based networks are predetermined by routing. This is necessary to avoid loops, inhibiting opportunities to implement an adaptive and intelligent forwarding plane. Consequently, content distribution efficiency is reduced due to a lack of inherent multi-path transmission. In Named Data Networking (NDN) instead, routing shall hold a supporting role to forwarding, providing sufficient potential to enhance content dissemination at the forwarding plane. In this paper, we design, implement, and evaluate a novel probability-based forwarding strategy, called Stochastic Adaptive Forwarding (SAF) for NDN. SAF imitates a self-adjusting water pipe system, intelligently guiding and distributing interests through network crossings circumventing link failures and bottlenecks. Just as real pipe systems, SAF employs overpressure valves enabling congested nodes to lower pressure autonomously. Through an implicit feedback mechanism, it is ensured that the fraction of the traffic forwarded via congested nodes decreases. By conducting simulations, we show that our approach outperforms existing forwarding strategies in terms of the interest satisfaction ratio in the majority of the evaluated scenarios. This is achieved by extensive utilization of NDN’s multipath and content-lookup capabilities without relying on the routing plane. SAF explores the local environment by redirecting requests that are likely to be dropped anyway. This enables SAF to identify new paths to the content origin or to cached replicas, circumventing link failures, and resource shortages without relying on routing updates. [ABSTRACT FROM AUTHOR]

This paper examines synchronization of computer clocks connected via a data network and proposes a skewless algorithm to synchronize them. Unlike existing solutions, which either estimate and compensate the frequency difference (skew) among clocks or introduce offset corrections that can generate jitter and possibly even backward jumps, our solution achieves synchronization without these problems. We first analyze the convergence property of the algorithm and provide explicit necessary and sufficient conditions on the parameters to guarantee synchronization. We then study the effect of noisy measurements (jitter) and frequency drift (wander) on the offsets and synchronization frequency, and further optimize the parameter values to minimize their variance. Our study reveals a few insights, for example, we show that our algorithm can converge even in the presence of timing loops and noise, provided that there is a well-defined leader. This marks a clear contrast with current standards such as NTP and PTP, where timing loops are specifically avoided. Furthermore, timing loops can even be beneficial in our scheme as it is demonstrated that highly connected subnetworks can collectively outperform individual clients when the time source has large jitter. The results are supported by experiments running on a cluster of IBM BladeCenter servers with Linux. [ABSTRACT FROM AUTHOR]

We study routing and scheduling algorithms for relay-assisted, multichannel downlink wireless networks [e.g., orthogonal frequency-division multiplexing (OFDM)-based cellular systems with relays]. Over such networks, while it is well understood that the BackPressure algorithm is stabilizing (i.e., queue lengths do not become arbitrarily large), its performance (e.g., delay, buffer usage) can be poor. In this paper, we study an alternative—the MaxWeight algorithm—variants of which are known to have good performance in a single-hop setting. In a general relay setting, however, MaxWeight is not even stabilizing (and thus can have very poor performance). In this paper, we study an iterative MaxWeight algorithm for routing and scheduling in downlink multichannel relay networks. We show that, surprisingly, the iterative MaxWeight algorithm can stabilize the system in several large-scale instantiations of this setting (e.g., general arrivals with full-duplex relays, bounded arrivals with half-duplex relays). Furthermore, using both many-channel large-deviations analysis and simulations, we show that iterative MaxWeight outperforms the BackPressure algorithm from a queue-length/delay perspective. [ABSTRACT FROM AUTHOR]

Today’s ever-growing networks call for routing schemes with sound theoretical scalability guarantees. In this context, a routing scheme is scalable if the amount of memory needed to implement it grows significantly slower than the network size. Unfortunately, theoretical scalability characterizations only exist for shortest path routing, but for general policy routing that current and future networks increasingly rely on, very little understanding is available. In this paper, we attempt to fill this gap. We define a general framework for policy routing, and we study the theoretical scaling properties of three fundamental policy models within this framework. Our most important contributions are the finding that, contrary to shortest path routing, there exist policies that inherently scale well, and a separation between the class of policies that admit compact routing tables and those that do not. Finally, we ask to what extent memory size can be decreased by allowing paths to contain a certain bounded number of policy violations and, surprisingly, we conclude that most unscalable policies remain unscalable under the relaxed model as well. [ABSTRACT FROM AUTHOR]

This paper investigates the rating of network paths, i.e., acquiring quantized measures of path properties such as round-trip time and available bandwidth. Compared to fine-grained measurements, coarse-grained ratings are appealing in that they are not only informative but also cheap to obtain. Motivated by this insight, we first address the scalable acquisition of path ratings by statistical inference. By observing similarities to recommender systems, we examine the applicability of solutions to a recommender system and show that our inference problem can be solved by a class of matrix factorization techniques. A technical contribution is an active and progressive inference framework that not only improves the accuracy by selectively measuring more informative paths, but also speeds up the convergence for available bandwidth by incorporating its measurement methodology. Then, we investigate the usability of rating-based network measurement and inference in applications. A case study is performed on whether locality awareness can be achieved for overlay networks of Pastry and BitTorrent using inferred ratings. We show that such coarse-grained knowledge can improve the performance of peer selection and that finer granularities do not always lead to larger improvements. [ABSTRACT FROM AUTHOR]

Manageability and high availability are critical properties for IP networks. Unfortunately, with link-state routing protocols commonly used in such networks, topological changes lead to transient forwarding loops inducing service disruption. This reduces the frequency at which operators can adapt their network. Prior works proved that it is possible to avoid disruptions due to the planned reconfiguration of a link by progressively changing its weight, leading to a solution that does not require changing protocol specification. In this paper, we study the more general problem of gracefully modifying the logical state of multiple interfaces of a router, while minimizing the number of weight updates. Compared to single-link modifications, the router update problem is k-dimensional for a router having k neighbors. We also show that multidimensional updates may trigger new kinds of disruptions that make the problem more challenging than the single-link case. We then present and evaluate efficient algorithms that compute minimal sequences of weights enabling disruption-free router reconfigurations. Based on analysis of real IP network topologies, we show that both the size of such sequences and the computing time taken by our algorithms are limited. [ABSTRACT FROM AUTHOR]

Energy expenditure has become a significant fraction of data center operating costs. Recently, “geographical load balancing” has been proposed to reduce energy cost by exploiting the electricity price differences across regions. However, this reduction of cost can paradoxically increase total energy use. We explore whether the geographical diversity of Internet-scale systems can also provide environmental gains. Specifically, we explore whether geographical load balancing can encourage use of “green” renewable energy and reduce use of “brown” fossil fuel energy. We make two contributions. First, we derive three distributed algorithms for achieving optimal geographical load balancing. Second, we show that if the price of electricity is proportional to the instantaneous fraction of the total energy that is brown, then geographical load balancing significantly reduces brown energy use. However, the benefits depend strongly on dynamic energy pricing and the form of pricing used. [ABSTRACT FROM PUBLISHER]

In this paper, we present a methodology employing statistical analysis and stochastic geometry to study geometric routing schemes in wireless ad hoc networks. In particular, we analyze the network-layer performance of one such scheme, the random 1\over 2disk routing scheme, which is a localized geometric routing scheme in which each node chooses the next relay randomly among the nodes within its transmission range and in the general direction of the destination. The techniques developed in this paper enable us to establish the asymptotic connectivity and the convergence results for the mean and variance of the routing path lengths generated by geometric routing schemes in random wireless networks. In particular, we approximate the progress of the routing path toward the destination by a Markov process and determine the sufficient conditions that ensure the asymptotic connectivity for both dense and large-scale ad hoc networks deploying the random 1\over 2disk routing scheme. Furthermore, using this Markov characterization, we show that the expected length (hop count) of the path generated by the random 1\over 2disk routing scheme normalized by the length of the path generated by the ideal direct-line routing, converges to 3\pi /4 asymptotically. Moreover, we show that the variance-to-mean ratio of the routing path length converges to 9\pi ^2/64-1 asymptotically. Through simulation, we show that the aforementioned asymptotic statistics are in fact quite accurate even for finite granularity and size of the network. [ABSTRACT FROM PUBLISHER]

An information collection problem in a wireless network with random events is considered. Wireless devices report on each event using one of multiple reporting formats. Each format has a different quality and uses different data lengths. Delivering all data in the highest-quality format can overload system resources. The goal is to make intelligent format selection and routing decisions to maximize time-averaged information quality subject to network stability. Lyapunov optimization theory can be used to solve such a problem by repeatedly minimizing the linear terms of a quadratic drift-plus-penalty expression. To reduce delays, this paper proposes a novel extension of this technique that preserves the quadratic nature of the drift minimization while maintaining a fully separable structure. In addition, to avoid high queuing delay, paths are restricted to at most 2 hops. The resulting algorithm can push average information quality arbitrarily close to optimum, with a tradeoff in queue backlog. The algorithm compares favorably to the basic drift-plus-penalty scheme in terms of backlog and delay. [ABSTRACT FROM PUBLISHER]

Opportunistic or delay-tolerant networks (DTNs) may be used to enable communication in case of failure or lack of infrastructure (disaster, censorship, remote areas) and to complement existing wireless technologies (cellular, WiFi). Wireless peers communicate when in contact, forming an impromptu network, whose connectivity graph is highly dynamic and only partly connected. In this harsh environment, communication algorithms are mostly local search heuristics, choosing a solution among the locally available ones. Furthermore, they are routinely evaluated through simulations only, as they are hard to model analytically. Even when more insight is sought from models, these usually assume homogeneous node meeting rates, thereby ignoring the attested heterogeneity and nontrivial structure of human mobility. We propose DTN-Meteo, a new unified analytical model that maps an important class of DTN optimization problems over heterogeneous mobility/contact models into a Markov chain traversal over the relevant solution space. (Heterogeneous) meeting probabilities between different pairs of nodes dictate the chain's transition probabilities and determine neighboring solutions. Local optimization algorithms can accept/reject candidate transitions (deterministically or randomly), thus “modulating” the above transition probabilities. We apply our model to two example problems: routing and content placement. We predict the performance of state-of-the-art algorithms (SimBet, BubbleRap) in various real and synthetic mobility scenarios and show that surprising precision can be achieved against simulations, despite the complexity of the problems and diversity of settings. To our best knowledge, this is the first analytical work that can accurately predict performance for utility-based algorithms and heterogeneous node contact rates. [ABSTRACT FROM PUBLISHER]

We consider utility maximization in networks where the sources do not employ flow control and may consequently overload the network. In the absence of flow control at the sources, some packets will inevitably have to be dropped when the network is in overload. To that end, we first develop a distributed, threshold-based packet-dropping policy that maximizes the weighted sum throughput. Next, we consider utility maximization and develop a receiver-based flow control scheme that, when combined with threshold-based packet dropping, achieves the optimal utility. The flow control scheme creates virtual queues at the receivers as a push-back mechanism to optimize the amount of data delivered to the destinations via back-pressure routing. A new feature of our scheme is that a utility function can be assigned to a collection of flows, generalizing the traditional approach of optimizing per-flow utilities. Our control policies use finite-buffer queues and are independent of arrival statistics. Their near-optimal performance is proved and further supported by simulation results. [ABSTRACT FROM PUBLISHER]

Traditional routing metrics designed for wireless networks are application-agnostic. In this paper, we consider a wireless network where the application flows consist of video traffic. From a user perspective, reducing the level of video distortion is critical. We ask the question “Should the routing policies change if the end-to-end video distortion is to be minimized?” Popular link-quality-based routing metrics (such as ETX) do not account for dependence (in terms of congestion) across the links of a path; as a result, they can cause video flows to converge onto a few paths and, thus, cause high video distortion. To account for the evolution of the video frame loss process, we construct an analytical framework to, first, understand and, second, assess the impact of the wireless network on video distortion. The framework allows us to formulate a routing policy for minimizing distortion, based on which we design a protocol for routing video traffic. We find via simulations and testbed experiments that our protocol is efficient in reducing video distortion and minimizing the user experience degradation. [ABSTRACT FROM PUBLISHER]

The three-stage Clos networks remain the most popular solution to many practical switching systems to date. The aim of this paper is to show that the modular structure of Clos networks is invariant with respect to the technological changes. Due to the wavelength routing property of arrayed-waveguide gratings (AWGs), non-blocking and contention-free wavelength-division-multiplexing (WDM) switches require that two calls carried by the same wavelength must be connected by separated links; otherwise, they must be carried by different wavelengths. Thus, in addition to the non-blocking condition, the challenge of the design of AWG-based multistage switching networks is to scale down the wavelength granularity and to reduce the conversion range of tunable wavelength converters (TWCs). We devise a logic scheme to partition the WDM switch network into wavelength autonomous cells and show that the wavelength scalability problem can be solved by recursively reusing similar, but smaller, set of wavelengths in different cells. Furthermore, we prove that the rearrangeably non-blocking (RNB) condition and route assignments in these AWG-based three-stage networks are consistent with that of classical Clos networks. Thus, the optimal AWG-based non-blocking Clos networks also can achieve 100% utilization when all input and output wavelength channels are busy. [ABSTRACT FROM PUBLISHER]

Presents corrections to the paper, ?Link-state routing with hop-by-hop forwarding can achieve optimal traffic engineering,? (Xu, D., et al)IEEE/ACM Trans. Netw., vol. 19, no. 6, pp. 1717?1730, Dec. 2011). [ABSTRACT FROM AUTHOR]