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As very large scale integration technology scales to deep submicron, design for interconnections becomes increasingly challenging. The traditional bus routing follows a sequential bit-by-bit order, and few works explicitly target interbit regularity for signal groups via multilayer topology selection. To overcome these limitations, we present $\mathsf {Streak}$ , an efficient framework that combines topology generation and wire synthesis with a global view of optimization and constrained metal layer track resource allocation. In the framework, an identification stage decomposes binding groups into a set of representative objects; with the generated backbones, equivalent topologies are accompanied by the bits in every object; then a formulation guides the routing considering wire congestion and design regularity. Furthermore, a bottom-up clustering methodology based on layer prediction targets to enhance the routability; a post-refinement stage is developed to match the source-to-sink distance deviation among bits in one group. Experimental results using industrial benchmarks demonstrate the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

Opportunistic routing is a promising technique that has been proposed for wireless mesh networks. It achieves significant performance gains under unstable wireless links since it can take advantage of the broadcast nature of the wireless medium. Many protocols of opportunistic routing have been proposed to increase transmission reliability and network throughput. Instead of using a dedicated next hop, opportunistic routing can consider multiple downstream nodes as potential forwarders. The decision of which nodes being chosen to forward packets is made by the coordination schema. Although the coordination helps opportunistic routing to deliver opportunistic gains, it requires a batch-based schedule to minimize the cost, which may prevent spatial channel reuse and thus under utilize wireless media. In this paper, we explain the fundamental idea of opportunistic routing and propose a discrete-time Markov chain as a general model to map the transmission process. It demonstrates how to map batch-based packet transmissions in the network with state transitions in a Markov chain. Our model considers the pipelined data transfer and evaluates opportunistic routing under different wireless networks in terms of the expected number of transmissions and time slots. It shows both the pros and cons of opportunistic routing and thus helps in the design of future protocols of opportunistic routing. [ABSTRACT FROM AUTHOR]

The end-to-end throughput of multi-hop communication in wireless ad hoc networks is affected by the conflict between forwarding nodes. It has been shown that sending more packets than maximum achievable end-to-end throughput not only fails to increase throughput but also decreases throughput owing to high contention and collision. Accordingly, it is of crucial importance for a source node to know the maximum end-to-end throughput. The end-to-end throughput depends on multiple factors, such as physical layer limitations, medium access control (MAC) protocol properties, routing policy, and nodes’ distribution. There have been many studies on analytical modeling of end-to-end throughput but none of them has taken routing policy and nodes’ distribution as well as MAC layer altogether into account. In this paper, the end-to-end throughput with perfect MAC layer is obtained based on routing policy and nodes’ distribution in 1-D and 2-D networks. Then, imperfections of IEEE 802.11 protocol are added to the model to obtain precise value. An exhaustive simulation is also made to validate the proposed models using ns-2 simulator. Results show that if the distribution to the next hop for a particular routing policy is known, our methodology can obtain the maximum end-to-end throughput precisely. [ABSTRACT FROM AUTHOR]

Pareto optimality is capable of striking the optimal tradeoff amongst the diverse conflicting quality-of-service requirements of routing in wireless multihop networks. However, this comes at the cost of increased complexity owing to searching through the extended multiobjective search-space. We will demonstrate that the powerful quantum-assisted dynamic programming optimization framework is capable of circumventing this problem. In this context, the so-called evolutionary quantum Pareto optimization (EQPO) algorithm has been proposed, which is capable of identifying most of the optimal routes at a near-polynomial complexity versus the number of nodes. As a benefit, we improve both the EQPO algorithms by introducing a back-tracing process. We also demonstrate that the improved algorithm, namely the back-tracing-aided EQPO algorithm, imposes a negligible complexity overhead, while substantially improving our performance metrics, namely the relative frequency of finding all Pareto-optimal solutions and the probability that the Pareto-optimal solutions are, indeed, a part of the optimal Pareto front. [ABSTRACT FROM AUTHOR]

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]

Delay-tolerant networks (DTNs) are intermittently connected networks, such as mobile social networks formed by human-carried mobile devices. Routing in such mobile social DTNs is very challenging, as it must handle network partitioning, long delays, and dynamic topology. Recently, social-based approaches, which attempt to exploit social behaviors of DTN nodes to make better routing decision, have drawn tremendous interest in the DTN routing design. In this paper, we propose a novel social-based routing approach for mobile social DTNs, where a new metric, i.e., social energy, is introduced to quantify the ability of a node to forward packets to others, inspired by general laws in particle physics. Social energy is generated via node encounters and shared by the communities of encountering nodes. Similar to the radiation of energy in physics, the social energy of any node decays over time. Our proposed social-energy-based routing (SEBAR) protocol considers social energy of encountering nodes and is in favor of the node with a higher social energy in its or the destination's social community. Our simulations with real-life wireless traces demonstrate the efficiency and the effectiveness of the SEBAR method by comparing it with several existing DTN routing schemes. In addition, two variations of SEBAR with the aim of overhead reduction are also presented and evaluated. [ABSTRACT FROM AUTHOR]

Modern technologies provide wide and thick metal layers that must be wisely used to reduce the delay of critical interconnections. After global routing, incremental layer assignment can improve the circuit timing by properly selecting critical interconnect segments to be routed in the faster (but very limited) wires on upper layers. Existing techniques based on net-by-net iterative improvement may get stuck at locally-optimal solutions depending on net ordering. Recent techniques rule out such drawback through the simultaneous iterative improvement of all nets, but they unfortunately rely on objective functions that may guide the optimization off critical paths. As opposed to all reported techniques, which rely on simplified, overly pessimistic timing models, this paper proposes the decoupling of incremental layer assignment from the timing analysis and the exploitation of flow conservation conditions so as to enable the use of an external signoff timing engine. The novel technique was experimentally compared with two state-of-the art works, leading to 50% less timing violations under total negative slack metric and 35% less timing violations under worst negative slack metric with similar overhead in number of vias. [ABSTRACT FROM AUTHOR]

Triple patterning lithography (TPL) is one of the most promising lithography technology in sub-14-nm technology nodes, especially for complicated low metal layer manufacturing. To overcome the intracell routability problem and improve the cell regularity, recently middle-of-line (MOL) layers are employed in standard cell design. However, MOL layers may introduce a large amount of cross-row TPL conflicts for row-based design. Motivated by this challenge, in this paper we propose the first TPL aware detailed placement toward zero cross-row MOL conflict. In standard cell precoloring, Boolean-based look-up table is proposed to reduce solution space. In detailed placement stage, three powerful techniques, i.e., local reordered single row refinement, min-cost flow-based conflict removal, and local cell interleaving, are proposed to provide zero TPL conflict solution. The experimental results demonstrate the effectiveness of our proposed methodologies. [ABSTRACT FROM AUTHOR]

In this paper, we formulate an integer linear programming (ILP) to perform multicast routing and spectrum assignment (MRSA) in elastic optical networks, which serves jointly a set of multicast requests. In this formulation, all physical layer restrictions including modulation level assignment, maximum number of multicast capable nodes (MCNs), and maximum splitting degree (MSD) of MCNs, are considered. In addition, we modify the proposed joint ILP to serve multicast requests one-by-one, which is referred to as a separate ILP. Furthermore, we present three heuristic algorithms for MRSA, namely distance-based MRSA (DMRSA), congestion-based MRSA (CMRSA), and mixed CMRSA/DMRSA, which are applicable in both static and dynamic operation scenarios. In CMRSA and DMRSA, the link length and the amount of occupied spectrum are considered as the cost function of multicast routing, respectively; and in mixed CMRSA/DMRSA, a combination of normalized link length and normalized occupied spectrum is considered as the cost function. The comparison of ILPs and heuristic algorithms in static operation reveals that the joint ILP, as the benchmark, gives the optimum solution while has the most computational complexity. Furthermore, the separate ILP has lower complexity at the cost of consuming slightly more spectrum. Unless the DMRSA method, which has the worst performance, the gap between the other two heuristic algorithms and the ILPs is negligible. Furthermore, simulation results of dynamic operation scenarios reveal that mixed CMRSA/DMRSA outperforms other two heuristics algorithms in terms of blocking probability. [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]

Delay-tolerant networks (DTNs) are an emergent communication paradigm characterized by intermittent connectivity. The nodes in DTNs can take advantage of their contact opportunities to forward messages. However, in noncooperative DTNs, the nodes may be selfish and reluctant to cooperate with each other in message forwarding. In such DTNs, stimulating cooperation among the nodes will be indispensable. Recently, many incentive mechanisms have been proposed to motivate nodes to cooperate in message forwarding. However, most of them cannot guarantee systematic security. To resolve the drawback of the previous incentive mechanisms, we first propose a credit-based rewarding scheme called the earliest path singular rewarding (EPSR) scheme to motivate the nodes to truthfully forward the messages during every contact opportunity. Then, we propose another credit-based rewarding scheme called the earliest path cumulative rewarding (EPCR) scheme by further considering that a node may get more contact information on others. We prove that both the EPSR and EPCR schemes are incentive compatible, and the payment for each delivered message is upper bounded. Furthermore, the proposed schemes can prevent selfish nodes having malicious behaviors. We have conducted real-trace-based simulations to illustrate the effectiveness of the proposed EPSR and EPCR schemes. [ABSTRACT FROM AUTHOR]

In this paper, we first challenge the accuracy of the so-called innovative assumption that is widely adopted in delay performance analysis of network-coding-based epidemic routing (NCER) in delay-tolerant networks (DTNs). We demonstrate that this optimistic assumption severely underestimates data delivery delay and solves this problem successfully by introducing an extra encounter factor $\delta$. Based on this, we propose a coloring process (CP)-based analytical model to evaluate the delay performance of NCER. Numerical results show that our CP-based method outperforms traditional ordinary differential equation (ODE)-based methods on estimating the delay performance under different network sizes. Furthermore, to mitigate potential competition among multiple data streams from different nodes, we propose a feedback-based recovery protocol (FRP) that takes advantage of finite buffer space and significantly reduces the number of ineffective transmissions between nodes. As a result, FRP can achieve much better delay performance compared with existing protocols in prior work. [ABSTRACT FROM AUTHOR]

The evolution of vehicular network applications, from simple alert message exchange to more elaborate and sophisticated systems, boosts the need for content delivery solutions. A useful technique, in this case, is content replication, in which strategically selected vehicles replicate content and help in the delivery process. However, content replication is particularly challenging in vehicular networks, due to their special characteristics, such as highly dynamic topology, diverse density, and large-scale scenarios. Although there has been progress in routing and dissemination solutions for vehicular networks, few studies have concentrated on the content replication problem. To address this issue, we propose an origin–destination-based content replication (ODCRep) solution that focuses on balancing the number of replicas across the application area. Differently from existing solutions, ODCRep relies only on the origin–destination information and uses computationally efficient algorithms. Results from exhaustive simulations show that ODCRep can achieve high coverage, yet can also consume fewer resources than existing solutions. [ABSTRACT FROM PUBLISHER]

Node clustering is a potential solution to minimize the control signaling overhead of routing protocols in vehicular ad hoc networks (VANETs). High relative vehicle mobility and frequent network topology changes induce instability to node clusters. Node cluster instability inflicts new challenges in maintaining a long route between network nodes, thus increasing the routing overhead. As a result, cluster instability, which is foisted by vehicle mobility, is a crucial issue for cluster-based routing in VANETs. This paper presents a stochastic analysis of the impact of cluster instability on generic routing overhead. A stochastic cluster instability model is adopted to capture the time variations of the cluster structure in terms of the cluster membership change rate and the cluster-overlap state change rate. First, we derive the probability distribution of the intracluster routing overhead using the cluster membership change rate. Second, the intercluster routing overhead is modeled as a rooted tree, with the tree nodes representing the value of the overhead and the tree edges weighted by the probability of a cluster-overlap state change. Numerical results are presented to evaluate the proposed models, which demonstrate a close agreement between analytical and simulation results. [ABSTRACT FROM PUBLISHER]

Successive interference cancelation (SIC) is a new physical-layer technique that enables the receiver to decode composite signals from multiple transmitters sequentially. The introduction of SIC improves the path bandwidth. In this paper, we focus on the design of a bandwidth-aware routing protocol with SIC, aiming at achieving high overall end-to-end throughput. We develop an SICable condition for a routing protocol to identify beneficial SIC opportunities that improve spatial reuse without impacting transmission quality. To further explore the benefits of SIC, we formulate the problem of SIC-aware path bandwidth computation as a linear program and design a distributed heuristic algorithm with polynomial complexity. A routing metric capturing the benefit of SIC in terms of bandwidth and network resource is proposed, by which our routing protocol can choose a path satisfying the bandwidth requirement of the current flow and reserving more network resource for the subsequent ones. Simulation results show that our routing protocol achieves significant gains in network throughput and SIC ratio compared with other routing protocols. [ABSTRACT FROM PUBLISHER]

Geographic routing protocols greatly reduce the requirements of topology storage and provide flexibility in the accommodation of the dynamic behavior of mobile ad hoc networks. This paper presents performance evaluations and comparisons of two geographic routing protocols and the popular AODV protocol. The tradeoffs among the average path reliabilities, average conditional delays, average conditional numbers of hops, and area spectral efficiencies and the effects of various parameters are illustrated for finite ad hoc networks with randomly placed mobiles. This paper uses a dual method of closed-form analysis and simple simulation that is applicable to most routing protocols and provides a much more realistic performance evaluation than has previously been possible. Some features included in the new analysis are shadowing, exclusion and guard zones, distance-dependent fading, and interference correlation. [ABSTRACT FROM PUBLISHER]

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]

Border Gateway Protocol (BGP) is vulnerable to routing attacks because of the lack of inherent verification mechanism. Several secure BGP schemes have been proposed to prevent routing attacks by leveraging cryptographic verification of BGP routing updates. In this paper, we present a new type of attacks, called TIGER, which aims to invalidate the “proven” security of these secure BGP schemes and allow ASes to announce forged routes even under full deployment of any existing secure BGP proposal. By launching TIGER attacks, malicious ASes can easily generate and announce forged routes which can be successfully verified by the existing secure BGP schemes. Furthermore, TIGER attacks can evade existing routing anomaly detection schemes by guaranteeing routing data-plane availability and consistency of control- and data-plane. Toward a new securing BGP scheme, we propose Anti-TIGER to detect and defend against TIGER attacks. Anti-TIGER enables robust TIGER detection by collaborations between ASes. In particular, we leverage Spread Spectrum Communication technique to watermark certain special probing packets, which manifest the existence of TIGER attacks. Anti-TIGER does not require any modifications in routing data-plane, therefore it is easy to deploy and incrementally deployable. We evaluate the effectiveness of TIGER and Anti-TIGER by experiments with real AS topologies of the Internet. Our experiment results show that TIGER attacks can successfully hijack a considerable number of prefixes. In the meanwhile, Anti-TIGER can achieve 100 percent detection ratio of TIGER attacks. [ABSTRACT FROM PUBLISHER]

In this paper, we design and evaluate the proposed geographic-based spray-and-relay (GSaR) routing scheme in delay/disruption-tolerant networks. To the best of our knowledge, GSaR is the first spray-based geographic routing scheme using historical geographic information for making a routing decision. Here, the term spray means that only a limited number of message copies are allowed for replication in the network. By estimating a movement range of destination via the historical geographic information, GSaR expedites the message being sprayed toward this range, meanwhile prevents that away from and postpones that out of this range. As such, the combination of them intends to fast and efficiently spray the limited number of message copies toward this range and effectively spray them within range, to reduce the delivery delay and increase the delivery ratio. Furthermore, GSaR exploits delegation forwarding to enhance the reliability of the routing decision and handle the local maximum problem, which is considered to be the challenges for applying the geographic routing scheme in sparse networks. We evaluate GSaR under three city scenarios abstracted from real world, with other routing schemes for comparison. Results show that GSaR is reliable for delivering messages before the expiration deadline and efficient for achieving low routing overhead ratio. Further observation indicates that GSaR is also efficient in terms of a low and fair energy consumption over the nodes in the network. [ABSTRACT FROM PUBLISHER]

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]

Content-Centric Networks (CCNs) are fundamental evolutionary technologies that promise to form the cornerstone of the future Internet. The information flow in these networks is based on named data requesting, in-network caching, and forwarding, which are unique and can be independent of IP routing. As a result, common IPbased network tools such as ping and traceroute can neither trace a forwarding path in CCNs nor feasibly evaluate CCN performance. We propose ?contrace,? a network tool for CCNs (particularly, CCNx implementation running on top of IP) that can be used to investigate the round-trip time (RTT) between content forwarder and consumer, the states of in-network cache per name prefix, and the forwarding path information per name prefix. We report a series of experiments conducted using contrace on a CCN topology created on a local testbed and the GEANT network topology emulated by the Mini-CCNx emulator. The results confirm that contrace is not only a useful tool for monitoring and operating a network, but also a helpful analysis tool for enhancing the design of CCNs. Further, contrace can report the number of received interests per cache or per chunk on the forwarding routers. This enables us to estimate the content popularity and design more effective cache control mechanisms in experimental networks. [ABSTRACT FROM PUBLISHER]

Delay- and Disruption Tolerant Networks (DTNs) are based on an overlay protocol and on the store-carry-forward paradigm. In practice, each DTN node can store information for a long time before forwarding it. DTNs are particularly suited to cope with the challenges imposed by the space environment. This paper is focused on routing in space DTNs, and in particular on contact graph routing (CGR) and its most representative enhancements, available in the literature, which are briefly surveyed in this work. Moreover, the applicability and the obtained performance of the DTN protocol stack and of the CGR have been evaluated by presenting results from real experimental experiences such as the Deep Impact Network experiment (employing the EPOXI space cruise), the JAXA jointly performed space link demonstrations with NASA (where the JAXA?s GEO relay satellite called Data Relay Test Satellite has been used), the Space Data Routers European Project, and the pilot operation of a DTN implementation on the International Space Station (ISS). [ABSTRACT FROM PUBLISHER]

In this contribution, we propose and study a bufferaided opportunistic routing (BOR) scheme, which combines the benefits of both opportunistic routing and multihop diversity (MHD) aided transmissions. It was conceived for a buffer-aided three-node network (B3NN) composed of a source node (SN), a buffer-aided relay node (RN) and a destination node (DN). In this network, there are three channels namely the SN-RN, RN-DN and SN-DN channels. The key motivation is that we are aiming for activating the specific channels requiring a recuded energy dissipation. In order to study this problem, a three-dimensional (3D) transmission activation probability space (TAPS) is proposed, which is divided into four regions representing each of the three channels plus an outage region. In a specific time slot (TS), the instantaneous channel fading values may be directly mapped to a specific point in this 3D channel space. The BOR scheme then relies on the position of this point to select the most appropriate channel for its transmission. Both the energy dissipation and the outage probability (OP) are investigated for transmission in this network. The results show that when the system is operated at a normalized throughput of 0.4 packet/TS, the energy dissipation was reduced by 24.8% to 77.6% compared to three different benchmark schemes. Alternatively, our technique is capable of reducing the OP by 89.6% when compared to conventional opportunistic routing. As in all buffer-aided system, the performance improved with the cost of higher packet delay, which is also studied. [ABSTRACT FROM PUBLISHER]

Soft wearable robots are good alternatives to rigid-frame exoskeletons because they are compact and lightweight. This article describes a soft wearable hand robot called the Exo-Glove that uses a soft tendon routing system and an underactuation adaptive mechanism. The proposed system can be used to develop other types of soft wearable robots. The glove part of the system is compact and weighs 194 g. The results conducted using a healthy subject showed sufficient performance for the execution of daily life activities, namely a pinch force of 20 N, a wrap grasp force of 40 N, and a maximum grasped object size of 76 mm. The use of an underactuation mechanism enabled the grasping of objects of various shapes without active control. A subject suffering from paralysis of the hands due to a spinal cord injury was able to use the glove to grasp objects of various shapes. [ABSTRACT FROM AUTHOR]

Geographic greedy forwarding (GF) technique has been widely used by many algorithms for routing in sensor networks because of its high efficiency resulting from its local and memoryless nature. Hence, it ensures scalability which is a fundamental requirement for protocol applicability to large-scale sensor networks with limited resources. Nevertheless, GF suffers from a serious drawback when packets, based on geographic distance, cannot be delivered; i.e., the so-called “local minimum phenomenon”. This problem has been tackled in previous research works to guarantee packet delivery by routing around the boundaries of the hole, but at an excessive consumption of control overheads. In this paper, we propose a novel approach that exploits GF technique and guarantees at the same time packet delivery (handles the local minimum situations). Our approach is of a local nature that does not retain memories and performs better than the state-of-the-art approaches in terms of its ability to guarantee packet delivery and to derive efficient routing paths. We provide, in this paper, proof of its correctness (packet delivery guaranty) while showing, through simulations, its performance effectiveness in terms of reducing path lengths, average end-to-end delays, and overall energy consumption. [ABSTRACT FROM AUTHOR]

This article considers the routing issues for user-centric network applications. User-centric network routing is a challenging problem because there may not always exist a complete stable path from an information source to its destination. In this article, we provide a brief overview on the state-of-the-art user-centric network routing schemes and discuss their performance in terms of data delivery ratio and delivery latency. We also present a few open research issues that are critical to user-centric network applications. [ABSTRACT FROM PUBLISHER]

Multimedia applications are characterized as delay-sensitive and high-bandwidth stipulating traffic sources. Supporting such demanding applications on cognitive radio sensor networks (CRSNs) with energy and spectrum constraints is a highly daunting task. In this paper, we propose a spectrum-aware cluster-based energy-efficient multimedia (SCEEM) routing protocol for CRSNs that jointly overcomes the formidable limitations of energy and spectrum. Clustering is exploited to support the quality of service (QoS) and energy-efficient routing by limiting the participating nodes in route establishment. In SCEEM routing, the number of clusters is optimally determined to minimize the distortion in multimedia quality that occurs due to packet losses and latency. Moreover, the cluster-head selection is based on the energy and relative spectrum awareness such that noncontiguous available spectrum bands are clustered and scheduled to provide continuous transmission opportunity. Routing employs clustering with hybrid medium access by combining carrier-sense multiple access (CSMA) and time-division multiple access (TDMA). TDMA operates for intracluster transmission, whereas CSMA is used for intercluster routing. Thus, a cross-layer design of routing, i.e., of medium access control (MAC) and physical layers, provides efficient multimedia routing in CRSNs, which is revealed through simulation experiments. [ABSTRACT FROM PUBLISHER]

Hybrid networks constructed from cellular networks and delay- and disruption-tolerant networks (DTNs) are able to provide reliable communications to mobile nodes in base-station-starved areas regardless of node mobility or density. However, no routing scheme in DTNs has considered the adaptation to other networks, i.e., cellular networks. Thus, the reliability of message delivery is dependent on the position relationship between source nodes and base stations. In this paper, we propose an advanced routing scheme that controls the maximum number of replicas according to the distance between the source node and the nearest base station. Furthermore, we show how to decide the maximum number of replica messages for the distance from the base stations by analyzing the message delivery reliability of an existing DTN routing scheme. Additionally, we execute extensive computer simulations to evaluate the performance of our proposed routing scheme. Our results show that our proposed routing scheme keeps the required reliability regardless of the source node location. [ABSTRACT FROM PUBLISHER]

Disruption-tolerant networks (DTNs) are sparse mobile ad hoc networks where nodes connect with each other intermittently and end-to-end communication paths do not exist. Data routing in DTNs is challenging and has drawn much attention from research communities recently. Although many DTN routing strategies have been proposed in the past, they confront problems such as blind spots and dead ends and lack efficient implementation in a decentralized, large-scale, mobile, and dynamic environment. To overcome these difficulties, we introduce a new solution for DTNs that leverages the social properties and mobility characteristics of users. Our observation of the mobile trajectories of three data sets collected from real DTNs reveals that user movements appear locally and they tend to form communities correlated to geographic locations. Based on these findings, we propose a social- and mobile-aware routing strategy (SMART). It exploits a distributed community partitioning algorithm to divide the DTN into smaller communities regarding user locations and interaction routines. For intracommunity communications, a decayed routing metric convoluting social similarity and social centrality is calculated, which is used to decide forwarding node efficiently while avoiding the blind-spot and dead-end problems. To enable efficient intercommunity communications, we choose the fringe nodes that travel remotely as relays, and we propose the node-to-community utilities for routing decision across communities. We present empirical analysis to show that SMART reduces the occurrence of blind spots and dead ends to a level below 1%. The efficiency of SMART is evaluated by extensive trace-driven experiments, which illustrate that it outperforms other routing strategies in various real DTN traces. [ABSTRACT FROM PUBLISHER]

An approach for cell routing using gridded design rules is proposed. It is technology-independent and parameterizable for different fabrics and design rules, including support for multiple-patterning lithography. The core contribution is a detailed-routing algorithm based on a Boolean formulation of the problem. The algorithm uses a novel encoding scheme, graph theory to support floating terminals, efficient heuristics to reduce the computational cost, and minimization of the number of unconnected pins in case the cell is unroutable. The versatility of the algorithm is demonstrated by routing single- and double-height cells. The efficiency is ascertained by synthesizing a library with 127 cells in about one hour and a half of CPU time. The layouts derived by the implemented tool have also been compared with the ones from a commercial library; thus, showing the competitiveness of the approach for gridded geometries. [ABSTRACT FROM PUBLISHER]

Most of the nodes in ad hoc networks rely on batteries, which requires energy saving. Hence, numerous energy-efficient routing algorithms have been proposed for solving this problem. In this paper, we exploit the benefits of cross-layer information exchange, such as the knowledge of the Frame Error Rate (FER) in the physical layer, the maximum number of retransmissions in the Medium Access Control (MAC) layer and the number of relays in the network layer. Energy-consumption-based Objective Functions (OF) are invoked for calculating the end-to-end energy consumption of each potentially available route for both Traditional Routing (TR) and for our novel Opportunistic Routing (OR), respectively. We also improve the TR and the OR with the aid of efficient Power Allocation (PA) for further reducing the energy consumption. For the TR, we take into account the dependencies amongst the links of a multi-hop route, which facilitates a more accurate performance evaluation than upon assuming the links that are independent. Moreover, two energy-efficient routing algorithms are designed based on Dijkstra's algorithm. The algorithms based on the energy OF provide the theoretical bounds, which are shown to be close to the bound found from exhaustive search, despite the significantly reduced complexity of the former. Finally, the end-to-end throughput and the end-to-end delay of this system are analyzed theoretically and a new technique of characterizing the delay distribution of OR is proposed. The simulation results show that our energy-efficient OR outperforms the TR and that their theoretical analysis accurately matches the simulation results. [ABSTRACT FROM PUBLISHER]

One of the purposes of network tomography is to infer the status of parameters (e.g., delay) for the links inside a network through end-to-end probing between (external) boundary nodes along predetermined routes. In this work, we apply concepts from compressed sensing and expander graphs to the delay estimation problem. We first show that a relative majority of network topologies are not expanders for existing expansion criteria. Motivated by this challenge, we then relax such criteria, enabling us to acquire simulation evidence that link delays can be estimated for 30% more networks. That is, our relaxation expands the list of identifiable networks with bounded estimation error by 30%. We conduct a simulation performance analysis of delay estimation and congestion detection on the basis of l_1 minimization, demonstrating that accurate estimation is feasible for an increasing proportion of networks. [ABSTRACT FROM PUBLISHER]

Energy saving in telecommunications networks has become a well established topic in the research community. We look at the electrical and optical layers of IP-over-WDM networks, and present a list of evaluation criteria for energy- aware adaptive routing solutions (EA-ARSs) from the perspective of a network operator. Furthermore, we briefly explain the adaptive routing solutions originating from the European Union?s TREND and the FP7 Network of Excellence, show saving of energy consumed by line cards in a reference scenario, and use the evaluation criteria to identify the next steps toward introduction of the EA-ARSs into real operation. [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]

The dynamicity of modern communication networks relays on the switching and routing infrastructure. The Cloud, the Internet of Things, the Big Data, the mobile data communications, the 4k video all demand an even more dynamic network provided by high performance switching and routing infrastructure. [ABSTRACT FROM PUBLISHER]