Egress Links Research Articles

Roulette Wheel Balancing Algorithm With Dynamic Flowlet Switching for Multipath Datacenter Networks

Load balance is an important issue in datacenter networks. The flowlet-based algorithms can balance the traffic with fine granularity and does not suffer the packet mis-sequencing problem. But their performances are rather limited or require extra communication overhead. In this paper, we propose a local load-aware algorithm called Dynamic Roulette Wheel (DRW). In DRW, the roulette wheel is adopted to select a new path for the flowlet according to the local load. Each source of multipath balances the traffic to all its egress links without the communication overhead. Moreover, the granularity of flowlet can be dynamically tuned from a single packet to the whole flow. Finally, the Capacity Aggregation (CA) mechanism is designed for the case of link or switch failure. We prove in theory that DRW can achieve the optimal global load balancing. The simulation results also show that DRW provides almost the best delay performance and the least packet out-of-order proportion overall among all existing flowlet switching algorithms.

Mode choice behavior for access and egress connection to transit services

In the aims to investigate the potential market of Transportation Network Companies (TNCs) to serve as first/last mile connection for transit services, this study investigated the influential factors that affect transit users’ choices of access and egress modes, including TNC or taxi, drive alone (park and ride), carpool (kiss and ride, carpool or shuttle), Micromobility modes (bike-sharing, scooters), walking, and wheelchair. The data for this study comes from a transit on-board survey conducted in Spring 2017 for the Orlando metropolitan area. Moreover, the Smart Location Database was also integrated to investigate how land use characteristics may contribute to users' choice for access and egress modes. Separate multinomial logit models were developed to investigate the mode choice for access and egress links, respectively. Various personal, trip, and land use characteristics showed significant impacts. Particularly, trips going to airports or universities/colleges had much higher probabilities of using TNC for access and egress purposes, while sports events and medical visits were less likely to be connected through TNC services. Visitors were also less likely to start their trips with TNCs. A longer distance between the origin and the transit service showed positive impacts on the use of TNC services. Higher household income also showed a positive influence on TNC usage. In view of land use characteristics, higher employment and household entropy, and high diversity at the origin reduced the probability of using motorized modes, including TNCs, for access purposes. On the destination side, high regional diversity seemed to encourage the use of TNCs and drive alone modes for egress purposes.

Performance Trade-Offs for Wavelength Striping Optical Switching Using a Novel Star Architecture

This work describes various performance trade-offs that arise from the use of a technique for optical switching under various network topologies. Such switching operation can be summarized as follows: (a) user data are divided into fixed-length fragments, (b) each fragment is assigned to a different wavelength, and (c) all wavelengths are simultaneously switched to the egress links. This concept of dividing user data into several wavelengths to be simultaneously switched is called wavelength striping and its purpose is to reduce latency and increase throughput for short distance interconnects. We depart from previous work where a building block implementing this basic switching function has been built around semiconductor optical amplifiers (SOAs). In this paper, we investigate diverse trade-offs that arise from the use of this switching approach in different network topologies. One of the main issues addressed in this paper is the relation between cascadability and bit error rate (BER). In this case, our results indicate that a switch fabric can cascade up to five stages without exceeding a BER of 10−9 and without incurring in power budget problems. We also show that the performance degradation, introduced by cascading SOAs, can be compensated with a star interconnect architecture that is introduced. Other issues addressed in this paper are the effect of scalability on cost and the effect of latency on TCP performance and reliability.

Host IQGAP1 and Ebola Virus VP40 Interactions Facilitate Virus-Like Particle Egress

We have identified host IQGAP1 as an interacting partner for Ebola virus (EBOV) VP40, and its expression is required for EBOV VP40 virus-like particle (VLP) budding. IQGAP1 is involved in actin cytoskeletal remodeling during cell migration and formation of filopodia. The physical interaction and the functional requirement for IQGAP1 in EBOV VP40 VLP egress link virus budding to the cytoskeletal remodeling machinery. Consequently, this interaction represents a novel target for development of therapeutics to block budding and transmission of filoviruses.

Hardware implementation study of several new egress link scheduling algorithms

The provision of Quality of Service (QoS) in interconnection networks is required for new multimedia and time-sensitive applications, which are very important for recent utility computing data centers (UCDCs) using high performance networks. These interconnection networks support switch-based principles and establish high demands in terms of bandwidth, time-delay, and delivery over short distances. A key component for networks with QoS support is the egress link scheduling algorithm. Apart from providing a good performance in terms of, for example, good end-to-end delay (also called latency) and fair bandwidth allocation, an ideal scheduling algorithm implemented in a high-performance network with QoS support should satisfy another important property which is to have a low computational and implementation complexity. In this paper, we propose specific implementations (taking into account the characteristics of current high performance networks) of several fair-queuing scheduling algorithms and compare their complexity in terms of silicon area and computation delay. In order to carry out this comparison, we have devised our own hardware comparison methodology. Following this methodology, we have performed our own hardware implementation for the different schedulers. We have modeled the schedulers using the Handel-C language and employed the DK design suite tool from Celoxica in order to obtain hardware estimates on silicon area and arbitration time.

Providing QoS with the Deficit Table Scheduler

A key component for networks with Quality of Service (QoS) support is the egress link scheduling algorithm. An ideal scheduling algorithm implemented in a high-performance network with QoS support should satisfy two main properties: good end-to-end delay and implementation simplicity. Table-based schedulers try to offer a simple implementation and good latency bounds. Some of the latest proposals of network technologies, like Advanced Switching and InfiniBand, include in their specifications one of these schedulers. However, these table-based schedulers do not work properly with variable packet sizes, as is usually the case in current network technologies. We have proposed a new table-based scheduler, which we have called Deficit Table (DTable) scheduler, that works properly with variable packet sizes. Moreover, we have proposed a methodology to configure this table-based scheduler in such a way that it permits us to decouple the bounding between the bandwidth and latency assignments. In this paper, we thoroughly review the provision of QoS with the DTable scheduler and our configuration methodology, and evaluate the performance of our proposals in a multimedia scenario. Simulation results show that our proposals are able to provide a similar latency performance than more complex scheduling algorithms. Moreover, we show the advantages of our decoupling configuration methodology over the usual ways of configuring this kind of table-based schedulers.

A critique of recently proposed buffer-sizing strategies

Internet router buffers are used to accommodate packets that arrive in bursts and to maintain high utilization of the egress link. Such buffers can lead to large queueing delays. Recently, several papers have suggested that it may, under general circumstances, be possible to achieve high utilisation with small network buffers. In this paper we review these recommendations. A number of issues are reported that question the utility of these recommendations.

Adaptive tuning of drop-tail buffers for reducing queueing delays

Internet router buffers are used to accommodate packets that arrive in bursts and to maintain high utilization of the egress link. Such buffers can lead to large queuing delays. We propose a simple algorithm, active drop-tail (ADT), which regulates the queue size, based on prevailing traffic conditions, to a minimum size that still allows for a desired (high) level of utilization. Packet level ns2 simulations are provided to show that adaptive drop-tail achieves significantly smaller queues than current approaches at the expense of 1-2% of the link utilization.

Adaptive tuning of drop-tail buffers for reducing queueing delays

Internet router buffers are used to accommodate packets that arrive in bursts and to maintain high utilization of the egress link. Such buffers can lead to large queuing delays. We propose a simple algorithm, active drop-tail (ADT), which regulates the queue size, based on prevailing traffic conditions, to a minimum size that still allows for a desired (high) level of utilization. Packet level ns2 simulations are provided to show that adaptive drop-tail achieves significantly smaller queues than current approaches at the expense of 1-2% of the link utilization.

Optimized routing for providing ethernet LAN services

Ethernet's-move into metropolitan and wide area networks is driving a rapidly growing market opportunity. Current Ethernet services come in two basic flavors, Ethernet line and LAN, providing point-to-point and multipoint connectivity, respectively. The LAN services, although more cost effective, are lagging behind in deployments due to associated QoS and bandwidth provisioning issues. The Ethernet service provider needs to provision the network to meet current and future traffic demands, where the traffic is unpredictable and bursty. The goal is to minimize. overprovisioning and complexity. To add to the challenge, Ethernet routing is based on simple self-learning and relies on spanning tree routing. In this article we propose an Ethernet-specific load balanced routing mechanism, which is robust to dynamic traffic demand. It significantly reduces overprovisioning, is simple and static, and requires only bandwidth profiles associated with service level agreements at the ingress and egress links. Our simulation results show that our scheme provides performance improvements over a recently proposed approach for switched Ethernet as well as a related load balancing approach for Ethernet over MPLS networks.

Resource management with hoses: point-to-cloud services for virtual private networks

As IP technologies providing both tremendous capacity and the ability to establish dynamic security associations between endpoints emerge, virtual private networks (VPNs) are going through dramatic growth. The number of endpoints per VPN is growing and the communication pattern between endpoints is becoming increasingly hard to predict. Consequently, users are demanding dependable, dynamic connectivity between endpoints, with the network expected to accommodate any traffic matrix, as long as the traffic to the endpoints does not overwhelm the capacity of the respective ingress and egress links. We propose a new service interface, termed a hose, to provide the appropriate performance abstraction. A hose is characterized by the aggregate traffic to and from one endpoint in the VPN to a set of other endpoints in the VPN, and by an associated performance guarantee. Hoses provide important advantages to a VPN customer: (1) flexibility to send traffic to a set of endpoints without having to specify the detailed traffic matrix, and (2) reduction in the size of access links through multiplexing gains obtained from the natural aggregation of the flows between endpoints. As compared with the conventional point-to-point (or customer pipe) model for managing quality of service (QoS), hoses provide reduction in the state information a customer must maintain. On the other hand, hoses would appear to increase the complexity of the already difficult problem of resource management to support QoS. To manage network resources in the face of this increased uncertainty, we consider both conventional statistical multiplexing techniques, and a new resizing technique based on online measurements. To study these performance issues, we run trace-driven simulations, using traffic derived from AT&T's voice network and from a large corporate data network. From the customer's perspective, we find that aggregation of traffic at the hose level provides significant multiplexing gains. From the provider's perspective, we find that the statistical multiplexing and resizing techniques deal effectively with uncertainties about the traffic, providing significant gains over the conventional alternative of a mesh of statically sized customer pipes between endpoints.

Deriving traffic demands for operational IP networks: methodology and experience

Engineering a large IP backbone network without an accurate network-wide view of the traffic demands is challenging. Shifts in user behavior, changes in routing policies, and failures of network elements can result in significant (and sudden) fluctuations in load. We present a model of traffic demands to support traffic engineering and performance debugging of large Internet service provider networks. By defining a traffic demand as a volume of load originating from an ingress link and destined to a set of egress links, we can capture and predict how routing affects the traffic traveling between domains. To infer the traffic demands, we propose a measurement methodology that combines flow-level measurements collected at all ingress links with reachability information about all egress links. We discuss how to cope with situations where practical considerations limit the amount and quality of the necessary data. Specifically, we show how to infer interdomain traffic demands using measurements collected at a smaller number of edge links-the peering links connecting to neighboring providers. We report on our experiences in deriving the traffic demands in the AT&T IP Backbone, by collecting, validating, and joining very large and diverse sets of usage, configuration, and routing data over extended periods of time. The paper concludes with a preliminary analysis of the observed dynamics of the traffic demands and a discussion of the practical implications for traffic engineering.

Deriving traffic demands for operational IP networks

Engineering a large IP backbone network without an accurate, network-wide view of the traffic demands is challenging. Shifts in user behavior, changes in routing policies, and failures of network elements can result in significant (and sudden) fluctuations in load. In this paper, we present a model of traffic demands to support traffic engineering and performance debugging of large Internet Service Provider networks. By defining a traffic demand as a volume of load originating from an ingress link and destined to a set of egress links, we can capture and predict how routing affects the traffic traveling between domains. To infer the traffic demands, we propose a measurement methodology that combines flow-level measurements collected at all ingress links with reachability information about all egress links. We discuss how to cope with situations where practical considerations limit the amount and quality of the necessary data. Specifically, we show how to infer interdomain traffic demands using measurements collected at a smaller number of edge links --- the peering links connecting to neighboring providers. We report on our experiences in deriving the traffic demands in the AT&T IP Backbone, by collecting, validating, and joining very large and diverse sets of usage, configuration, and routing data over extended periods of time. The paper concludes with a preliminary analysis of the observed dynamics of the traffic demands and a discussion of the practical implications for traffic engineering.

A flexible model for resource management in virtual private networks

As IP technologies providing both tremendous capacity and the ability to establish dynamic secure associations between endpoints emerge, Virtual Private Networks (VPNs) are going through dramatic growth. The number of endpoints per VPN is growing and the communication pattern between endpoints is becoming increasingly hard to forecast. Consequently, users are demanding dependable, dynamic connectivity between endpoints, with the network expected to accommodate any traffic matrix, as long as the traffic to the endpoints does not overwhelm the rates of the respective ingress and egress links. We propose a new service interface, termed a hose , to provide the appropriate performance abstraction. A hose is characterized by the aggregate traffic to and from one endpoint in the VPN to the set of other endpoints in the VPN, and by an associated performance guarantee.Hoses provide important advantages to a VPN customer: (i) flexibility to send traffic to a set of endpoints without having to specify the detailed traffic matrix, and (ii) reduction in the size of access links through multiplexing gains obtained from the natural aggregation of the flows between endpoints. As compared with the conventional point to point (or customer-pipe) model for managing QoS, hoses provide reduction in the state information a customer must maintain. On the other hand, hoses would appear to increase the complexity of the already difficult problem of resource management to support QoS. To manage network resources in the face of this increased uncertainty, we consider both conventional statistical multiplexing techniques, and a new resizing technique based on online measurements.To study these performance issues, we run trace driven simulations, using traffic derived from AT&T's voice network, and from a large corporate data network. From the customer's perspective, we find that aggregation of traffic at the hose level provides significant multiplexing gains. From the provider's perspective, we find that the statistical multiplexing and resizing techniques deal effectively with uncertainties about the traffic, providing significant gains over the conventional alternative of a mesh of statically sized customer-pipes between endpoints.

Pilot study of computer-based urban traffic management

The objectives of urban traffic management are to make more efficient use of existing transportation resources and provide for the movement of people in an efficient manner through the development of low-cost short-range management strategies. Implementation of such strategies can provide for reduced travel costs, savings of energy, reduced air pollution, and improved safety and convenience for the users of the facilities. It can also help to reduce necessary capital expenditure for new facilities to accommodate urban travel demands in the longer range. This paper presents a modelling framework for multimodal urban traffic management, explicitly modelling the divergent objectives of traffic managers and trip-makers. Facilities analyzed are arterial streets and freeways with their associated access and egress links. Modes considered are private automobiles, carpools, trucks, and buses. Decision parameters may include signal controls, ramp metering rates, priority lane assignments, variable-message signs, etc. Effects of modal performance on mode choice are also included in the analysis. Computational results are reported of a pilot application of the framework using heuristic solution techniques.