Abstract Small-scaled model tests under normal gravity are widely used to examine slope stabilities and failure mechanisms. Nevertheless, in practice, it is impossible to comply to all similarity principles, which could affect the modeled results in the prototype. This paper performs finite element analyses to investigate the behavior of uniform clay slopes as commonly performed in a 1g model test without following similarity principles. The numerical model is validated with previously published data. A parametric study is then carried out with varying slope scales, soil properties, etc. Based on extensive numerical modeling data, four formulas are established to correlate and interpolate the sliding surface and safety factor of a model slope in a 1g test. A framework is proposed to interpret 1g model-scale test results for applications in slope designs.
Cloud services such as multi-tenant content delivery networks (CDN) have become a trend because they can offer personalized business support for tenants. However, the business modes of different tenants are usually different. Thus, it is not appropriate to use a single buffering strategy on cloud servers because it cannot adapt to various access patterns of tenants. In this paper, we propose to develop adaptive buffer management for multi-tenant cloud services. Particularly, we present an adaptive buffer replacement policy called ARP (Adaptive Replacement Policy) for each tenant. ARP can automatically choose a recency-based or a frequency-based replacement policy according to the workload characteristics. Further, to solve the problem that ARP needs to manually set a parameter $p$ , we present an optimization for ARP, called ARP+, to automatically adjust the value of parameter $p$ according to the workload characteristics. We conduct experiments on multiple tailor-made workloads. The results show that both ARP and ARP+ outperform conventional buffering policies, including LRU, LFU, LIRS, and LRU-2. In addition, ARP+ can automatically adapt to the change of access patterns, which is more suitable for multi-tenant cloud scenarios.
RDMA is increasingly deployed in data center to meet the demands of ultra-low latency, high throughput and low CPU overhead. However, it is not easy to migrate existing applications from the TCP/IP stack to the RDMA. The developers usually need to carefully select communication primitives and manually tune the parameters for each single-purpose system. After operating the high-speed RDMA network, we identify multiple hidden costs which may cause degraded and/or unpredictable performance of RDMA-based applications. We demonstrate these hidden costs including the combination of complicated parameter settings, scalability of Reliable Connections, two-sided memory management and page alignment, resource contention among diverse traffics, etc. Furthermore, to address these problems, we introduce Nem, a suite that allows developers to maximize the benefit of RDMA by i) eliminating the resource contention at NIC cache through asynchronous resource sharing; ii) introducing hybrid page management based on messages sizes; iii) isolating flows of different traffic classes based hardware features. We implement the prototype of Nem and verify its effectiveness by rebuilding the RPC message service, which demonstrates the high throughput for large messages, low latency for small messages without compromising the low CPU utilization and good scalability performance for a large number of active connections.
There has always been a gap of perception between Internet Service Providers (ISPs) and their customers when considering the performance of network service. On one hand, ISPs invest to increase downstream speed of access network infrastructure. On the other hand, users cannot achieve perceived quality of experience (QoE). This paper addresses this problem by introducing a system, Conan, which enables content-aware flow scheduling to improve the QoE of users. Conan exploits to satisfy users' requirements in the access network (LAN), which is the performance bottleneck actually. By leveraging the technique of software defined networking (SDN), Conan are able to specify the expected network capacity for different applications. Automatic application identification is deployed at home gateway to improve the scalability, and flexible bandwidth allocation is realized at LAN for specified applications. Using video streaming service optimization as an example, we demonstrate that our system can automatically allocate bandwidth for video flows.
Regional failures, such as natural disaster or malicious attack, have become a major threat to the construction of future reliable communication network. The regional failures usually cause a large number of disconnected nodes simultaneously and influence the network for a long time. However, a routing scheme that is resilient to such geographically correlated failures is still unexplored. In this paper, we provide a comprehensive study of the disaster resilient routing dealing with the regional failure in operational IP backbone networks. It is notable that the path with minimal risk (i.e., minimal failure probability) is not necessarily the shortest path. The main challenge of finding such paths is that regional failure is unpredictable in terms of time, location, and the affected area. To this end, in combination with the computational geometry tool, we develop effective algorithms to find the minimal risk path between end node pairs to tolerate random regional failures. We show that in contrast to the conventional shortest path, a little longer path can be more effective to the disasters. After selecting such a path as the primary path, we turn to find a secondary backup path. In contrast to the conventional single link/node failure, a regional failure disrupts a large number of network components, simultaneously. As a result, how to find backup paths for re-establishment of the corrupted paths will raise a novel fairness issue. Specifically, during the backup path allocation, we focus on routing fairness to bound the worst-case user experience. A metric is proposed based on which an ILP is formulated. The extensive simulations validate that such an issue is non-negligible in face of regional failure scenarios.
All-optical switching has been considered as a natural choice to keep pace with growing fiber link capacity. One key research issue of all-optical switching is the design of optical buffers for packet contention resolution. One of the most general buffering schemes is optical priority queue, where every packet is associated with a unique priority upon its arrival and departs the queue in order of priority, and the packet with the lowest priority is always dropped when a new packet arrives but the buffer is full. In this paper, we focus on the feedback construction of an optical priority queue with a single $\boldsymbol{(M+2)\times (M+2)}$ optical crossbar Switch and $\boldsymbol{M}$ fiber Delay Lines (SDL) connecting $\boldsymbol{M}$ inputs and $\boldsymbol{M}$ outputs of the switch. We propose a novel construction of an optical priority queue with buffer $\boldsymbol{2^{\Theta(\sqrt{M})}}$, which improves substantially over all previous constructions that only have buffers of $\boldsymbol{O(M^c)}$ size for constant integer $\boldsymbol{c}$. The key ideas behind our construction include (i) the use of first in first out multiplexers, which admit efficient SDL constructions, for feeding back packets to the switch instead of fiber delay lines, and (ii) the use of a routing policy that is similar to self-routing, where each packet entering the switch is routed to some multiplexer mainly determined by the current ranking of its priority.
Cloud network serves a large number of tenants and a variety of applications. The continuously changing demands require a programmable data plane to achieve fast feature velocity. However, the years-long release cycle of traditional function-fixed switches can not meet this requirement. Emerging programmable switches provide the flexibility of packet processing without sacrificing hardware performance. Due to the trade-off between performance and flexibility, the current programmable switches make compromises in some aspects such as limited memory/computation resources, and lack of the capacity to realize complicated computation. The programmable switches can not satisfy the demand for network services and applications in production networks. We propose a framework that leverages host servers to extend the capability of network switches quickly, accelerates new feature deployment, and verifies new ideas in production networks. Specifically, to build the unified programmable data plane, we propose essential design and implementation challenges including a programming abstraction that allows automatically and effectively deploying network functions on switch and server clusters, allocating traffic to fully utilize the server resources, and supporting flexible scaling of the system. The quick deployment of self-defined functions in a realistic system has verified the feasibility and practicality of the proposed framework.
Software Defined Networking (SDN) is beneficial to many applications, such as intra-datacenter communication, inter-datacenter transportation, etc., due to its centralized control. However, this centralized control frequently makes the controller a bottleneck, due to the large amount of interactions between the controller and switches. In this paper, we characterize such interactions as control traffic, and propose RouteStitch to minimize such kind of traffic. RouteStitch exploits existing route entries in switches to build new paths. To this end, RouteStitch first builds a graph model to describe existing route entries. Then, on such a model, a novel minimum color-alternation routing problem is defined to minimize control traffic, after which an optimal algorithm is proposed on a fixed routing path. For general paths, an O(log 2 L)-competitive online algorithm is designed to build new paths in an online manner that preserves fundamental property of switch Ternary Content Addressable Memory (TCAM) capacity and allowed maximum hop length L. Extensive simulation results based on realistic topology show that RouteStitch has good performance in terms of reducing control traffic, by 40%.
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