Jingxin Wu

A comparative analysis of data center network architectures

Advances in data intensive computing and high performance computing facilitate rapid scaling of data center networks, resulting in a growing body of research exploring new network architectures that enhance scalability, cost effectiveness and performance. Understanding the tradeoffs between these different network architectures could not only help data center operators improve deployments, but also assist system designers to optimize applications running on top of them. In this paper, we present a comparative analysis of several well known data center network architectures using important metrics, and present our results on different network topologies. We show the tradeoffs between these topologies and present implications on practical data center implementations.

Comparison of OXC Node Architectures for WDM and Flex-Grid Optical Networks

Large scale optical cross-connects (OXCs) are required due to the increasing traffic demands. Currently, wavelength-selective switches (WSS) are utilized to create the OXCs. However, the port count of commercially available WSSs is limited. To achieve high port counts in OXCs, the existing WSS-based approach is to cascade WSSs, which results in a square order increment in the number of required WSSs. To save the hardware costs in terms of number of WSSs, two novel OXC architectures utilizing the waveband switching technique have been proposed. In this paper, we conduct a detailed comparison among the conventional cascading architecture and the two new architectures. We propose algorithms to accommodate dynamic traffic demands for all architectures and compare the blocking rates. The results show that the blocking rates of the novel architectures are very small and close to that of the cascading architecture, while the novel architectures have much less node complexity in terms of hardware requirement.

Co-scheduling computational and networking resources in elastic optical networks

Todays applications such as cloud computing and e-science involve the processing of complex jobs consisting of several inter-dependent tasks executing on heterogeneous clusters of computing resources, which are interconnected by high-speed optical networks. The emerging technology of flexible grid through the use of Optical Orthogonal Frequency-Division Multiplexing (OOFDM) allows fiber bandwidth to be more suitably matched up with application requirements, thereby making the network more elastic. This is done by partitioning the bandwidth into hundreds or even thousands of OFDM subcarriers that may be allocated to services. An important problem in such applications is the joint scheduling (or co-scheduling) of computational and network resources. In this paper, we formulate a problem of co-scheduling computational and networking resources to multiple jobs in elastic optical networks. We consider both static and dynamic versions of the problem; in the static case, our objective is to minimize the makespan of all the jobs, while minimizing the job blocking is the aim when jobs arrive dynamically. We formulate an integer-linear program for the static version of the problem. Two efficient heuristics are then proposed and compared. Simulation results are presented to demonstrate the effectiveness of the proposed approaches.

A Dual Delay Timer Strategy for Optimizing Server Farm Energy

Server farms are becoming increasingly energy-hungry with the growing popularity of web-based applications and services. Servers consume nearly 60% of peak power even when operating at relatively low utilization levels of around 30%. Unfortunately, most server farms are generally provisioned to accommodate the peak load, and wasteful energy is often spent on unnecessarily keeping the servers active. Recent work on utilizing processor sleep states has mitigated the energy problem, but more opportunities to optimize energy remain to be explored. In this paper, we explore techniques that make smart use of processor deep sleep states through augmenting them with dual delay timers for more effective energy management in the multi-server environment. We find that our exploratory studies on smarter use of processor sleep states with dual delay timers show good promise in achieving higher energy savings on different kinds of synthetic and real workloads. Our experimental results show that our techniques achieve up to 71% savings in energy over naive energy management without the use of low-power sleep states, and up to 31% energy savings over a relatively smarter energy management mechanism with just a single delay timer to enter the sleep state. We also show that the normalized latency of jobs on a server farm with our dual delay timer strategy is almost similar to the one that is always ready to accept incoming jobs.

WASP: Workload Adaptive Energy-Latency Optimization in Server Farms Using Server Low-Power States

With the growing energy demands from server farms, it becomes necessary to understand the tradeoffs between energy consumption and application performance. Typically, server farms are provisioned for peak load even when they are mostly operating at low utilization levels. This results in wasteful energy consumption. At the same time, application workloads have Quality of Service (QoS) constraints that need to be satisfied. Optimizing server farm energy consumption with QoS constraints is a challenging task since the workload can have variabilities in job sizes, job arrival patterns and system utilization levels. In this paper, we present WASP, where we explore techniques that make smart use of the processor and system low-power states, and orchestrate their use with workload adaptivity for more effective energy management. We perform an extensive study of Energy-Latency tradeoffs with simulations, and evaluate WASP on a testbed with a cluster of servers. Our experiments on real systems show that WASP achieves up to 57% energy reduction over a naive policy that uses a shallow processor sleep state when there are no jobs to execute, and 39% over a delay timer based approach while maintaining the 90th percentile job service latency to be under 2x job execution time.

Joint banding-node placement and resource allocation for multigranular elastic optical networks

The fine-grained grid of elastic optical networks (EONs) facilitates flexible bandwidth allocation and increased spectrum utilization efficiency and is seen as a promising solution to handle ever-increasing traffic demands. Despite this, fiber capacity exhaustion is imminent, and multifiber links are expected to be prevalent in future optical networks. A challenge this brings about is the high port count of optical cross-connects (OXCs). Conventional OXCs built using flex-grid wavelength selective switches do not scale well. To achieve scalability of OXCs, a flexible wavebanding OXC architecture (FLEX) has been proposed recently. FLEX reduces the complexity and cost of OXCs while sacrificing some performance in terms of limited switching flexibility. Taking the reduced switching capability into consideration, a cost-function pluggable auxiliary layered-graph framework has been proposed in our previous work to solve the routing, fiber, waveband, and spectrum assignment (RFBSA) problem in multifiber-based EONs with flexible wavebanding nodes. In this paper, we address the following problem. Given the total number of available WSSs for the network as a budget, we determine how many FLEX nodes to deploy and where to deploy them, and solve the RFBSA problem jointly to optimize the network performance. An integer linear programming formulation is proposed for a set of traffic requests. We also propose a heuristic algorithm to solve this joint problem efficiently. The results show that our algorithm achieves good network performance, which is indicated by the average maximum spectrum usage as well as considerably reducing hardware costs. We also evaluate our algorithm for dynamically arriving traffic requests in terms of demand blocking ratio.

Routing, fiber, band, and spectrum assignment (RFBSA) for multi-granular elastic optical networks

The dramatic growth of Internet traffic brings challenges for optical network designers. There have been a number of advances recently in increasing fiber bandwidth and spectrum utilization efficiency through elastic optical networking (EON). In EON, a flexible and more fine-grained grid than conventional approaches is employed, and this allows allocated fiber bandwidth to better match traffic demands. Despite these advances, imminent fiber capacity exhaustion means that multiple fibers per link will be inevitable. In an effort to reduce the complexity of optical crossconnects, a flexible wavebanding crossconnect has been proposed recently. Elastic networking and flexible wavebanding introduce a new problem, namely, the routing, fiber, waveband, and spectrum assignment (RFBSA) problem. In this work, we propose new cost functions that are pluggable into an auxiliary layered-graph framework to solve the RFBSA problem with different objectives. We focus on minimizing the maximum spectrum usage for a set of traffic demands, and show that our approach outperforms traditional approaches.

Joint Banding-Node Placement and Resource Allocation for Multi-Granular Elastic Optical Networks

The fine-grained grid of elastic optical networks (EONs) facilitates flexible bandwidth allocation and increased spectrum utilization efficiency and is seen as a promising solution to handle ever-increasing traffic demands. Despite this, fiber capacity exhaustion is imminent, and multifiber links are expected to be prevalent in future optical networks. A challenge this brings about is the high port count of optical cross-connects (OXCs). Conventional OXCs built using flex-grid wavelength selective switches do not scale well. To achieve scalability of OXCs, a flexible wavebanding OXC architecture (FLEX) has been proposed recently. FLEX reduces the complexity and cost of OXCs while sacrificing some performance in terms of limited switching flexibility. Taking the reduced switching capability into consideration, a cost-function pluggable auxiliary layered-graph framework has been proposed in our previous work to solve the routing, fiber, waveband, and spectrum assignment (RFBSA) problem in multifiber-based EONs with flexible wavebanding nodes. In this paper, we address the following problem. Given the total number of available WSSs for the network as a budget, we determine how many FLEX nodes to deploy and where to deploy them, and solve the RFBSA problem jointly to optimize the network performance. An integer linear programming formulation is proposed for a set of traffic requests. We also propose a heuristic algorithm to solve this joint problem efficiently. The results show that our algorithm achieves good network performance, which is indicated by the average maximum spectrum usage as well as considerably reducing hardware costs. We also evaluate our algorithm for dynamically arriving traffic requests in terms of demand blocking ratio.

Evaluation and performance modeling of two OXC architectures

This paper presents an evaluation of two Optical Cross-Connect (OXC) node architectures with multiple fibers per link — one, a conventional architecture, and the second, a hierarchical architecture that has lower complexity than the first architecture. Analytical models for computing the blocking probability of connection requests are proposed and validated. Heuristics for resource assignment are then proposed, and the performance of the two architectures are compared. The two architectures are then compared in terms of the cost of the OXC node and the power consumption. Our results show that the hierarchical architecture exhibits a good balance between performance, cost, and power consumption.

Optimal nonuniform wavebanding in WDM mesh networks

Grouping together a set of consecutive wavelengths in a WDM network and switching them together as a single waveband could achieve savings in switching costs of an optical cross-connect. This technique is known as waveband switching. While previous work has focused on either uniform band sizes considering a single node or ring networks, in this paper we focus on optimizing the number of wavebands and their sizes for mesh topologies. We formulate a problem of optimizing the number of wavebands in a mesh network for a given set of lightpaths. The objective of the Band Minimization is to minimize the number of nonuniform wavebands in the network while satisfying the traffic requests. We formulate an integer-linear program, and propose efficient heuristics. Simulation results are presented to demonstrate the effectiveness of the proposed approaches. Our results show that the number of switching elements can be reduced by a large amount using waveband switching compared to wavelength switching.