Prediction-Based Joint Energy Optimization for Virtualized Data Centers

This paper proposes an adaptive virtual machine (VM) assignment scheme for multi-tenant data center networks. In multi-tenant data centers, tenants submit their resource requirements and the data centers provide VMs which are assigned to physical servers. These VMs communicate with each other to execute distributed processing. The amount of traffic communicated by VMs is very large and this is one of big issues in data center networks. In order to reduce the amount of traffic injected into data center networks, we need an appropriate VM assignment strategy which considers traffic between VMs. Furthermore, VMs are dynamically assigned to and removed from physical servers according to resource requirements of tenants, and thus we should consider such dynamic behavior. The proposed scheme provides an VM assignment strategy which reduces the amount of traffic injected into data center networks, taking into account dynamic behavior of the data center networks. Through simulation experiments, we demonstrate that the proposed scheme reduces the network load efficiently.

Given the current expansion of cloud computing, the expected advent of the Internet of Things, and the requirements of future fifth‐generation network infrastructures, significantly larger pools of computational and storage resources will soon be required. This emphasizes the need for more scalable data centers that are capable of providing such an amount of resources in a cost‐effective way. A quick look into today's commercial data centers shows that they tend to rely on variations of well‐defined leaf‐spine/Clos data center network (DCN) topologies, offering low latency, ultrahigh bisectional bandwidth, and enhanced reliability against concurrent failures. However, DCNs are typically restricted by the use of the Transmission Control Protocol/Internet Protocol (TCP/IP) suite, thus suffering limited routing scalability. In this work, we study the benefits that replacing TCP/IP with the recursive internetwork architecture (RINA) can bring into commercial DCNs, focusing on forwarding and routing scalability. We quantitatively evaluate the benefits that RINA solutions can yield against those based on TCP/IP and highlight how, by deploying RINA, topological routing solutions can improve even more the efficiency of the network. To this goal, we propose a rule‐and‐exception forwarding policy tailored to the characteristics of several DCN variants, enabling fast forwarding decisions with merely neighbors' information. Upon failures, few exceptions are necessary, whose computation can also profit from the known topology. Extensive numerical results show that the proposed policy requirements depend mainly on the number of neighbors and concurrent failures in the DCN rather than its size, dramatically reducing the amount of forwarding and routing information stored at DCN nodes.

CoMap: An efficient virtual network re-mapping strategy based on coalitional matching theory

Within today's large-scale data centers, the inter-node communication is often the major bottleneck. This fact recently blooms the data center network (DCN) research. Since building a real data center is cost prohibitive, most of DCN studies rely on simulations. Unfortunately, state-of-the-art network simulators have limited support for real world applications, which prevents researchers from first-hand investigation. To address this issue, we developed a unified and cross-layer simulation framework, namely the DCNSim. By leveraging the two widely deployed simulators, DCNSim introduces computer architecture solutions into DCN research. With DCNSim, one could run packet-level network simulation driven by commercial applications while varying computer and network parameters, such as CPU frequency, memory access latency, network topology and protocols. With extensive validations, we show that DCNSim could accurately capture performance trends caused by changing computer and network parameters. Finally, we argue that future DCN researches should consider computer architecture factors via several case studies.

OMUX: Optical Multicast and Unicast-capable interconnection network for data centers

Bandwidth-hungry applications such as Cloud computing, video sharing and social networking drive the creation of more powerful Data Centers (DCs) to manage the large amount of packetized traffic. Data center network (DCN) topologies rely on thousands of servers that exchange data via the switching backbone. Cluster switches and routers are employed to provide interconnectivity between elements of the same DC and inter DCs and must be able to handle the continuously variable loads. Hence, robust and scalable switching modules are needed. Conventional DCNs adopt multistage switches that are crossbar or/and memory based. However, current multistage packet switch architectures, with their space-memory variants, are either too complex to implement, have poor performance, or not cost effective. In this paper, we propose a novel and highly scalable multistage packet- switch design based on Network-on-Chip (NoC) fabrics for DCNs. In particular, we describe a novel three-stage packet-switch fabric with a Round-Robin packets dispatching scheme where each central stage module is based on a multihop Unidirectional NoC (UDN), instead of a classic singlehop crossbar fabric. The proposed design, referred to as Clos-UDN, overcomes all the shortcomings of conventional multistage architectures. In particular, as we shall demonstrate, the proposed Clos-UDN architecture: (i) Obviates the need for a complex and costly input modules, by means of few, yet simple, input FIFO queues. (ii) Avoids the need for a complex and synchronized scheduling process over a high number of input- output modules and/or port pairs. (iii) Provides speedup, load balancing and path- diversity thanks to a dynamic dispatching scheme as well as the NoC based fabric nature. Extensive simulation studies are conducted to compare the proposed Clos-UDN switch to traditional multistage switches. Simulation results show that the Clos-UDN outperforms previous designs under a wide range of input traffic scenarios, making it highly appealing for ultra-high capacity DC networks.

The data center bridging (DCB) protocols enable Ethernet to become the leading unified fabric for a converged data center. As a part of DCB, priority flow control (PFC) is a control mechanism that provides the losslessness feature required by certain applications such as Fibre Channel over Ethernet. Quantized congestion notification (QCN) is also a DCB protocol and provides congestion control functionality to complement PFC. However, in today's practical data center networks, QCN is not feasible and PFC is not efficient against congestion. We propose a new link layer mechanism called congestion aware priority flow control (CaPFC) that equips PFC with better congestion control capability in the absence of QCN. Changes brought by CaPFC on top of PFC are lightweight. By conducting simulations in NS-3, we demonstrate that CaPFC handles persistent and flash congestion much better than PFC. For the short messaging traffic and the query traffic, which are sensitive to tail latencies, CaPFC consistently outperforms PFC in terms of tail flow completion time.

As bandwidth is shared in a best-effort way in today's data centers, traffic generated between a set of VMs (virtual machines) affect the traffic between another set of VMs (possibly belonging to another tenant) sharing the same physical links, leading to unpredictable performance of applications running on these VMs. This article addresses the problem of allocation of not only server resources (computational and storage) but also network bandwidth, to provide performance guarantees in multi-tenant data centers. Bandwidth being a critical shared-resource, we formulate the problem as an optimization problem that minimizes bandwidth demand between clusters of VMs of a tenant; and we prove it as NP-hard. We develop fast online heuristics as an integrated resource allocator (IRA) that decides on the admission of dynamically arriving requests, and allocates resources for the accepted ones. We also present a modified version of IRA, called B-IRA that bounds the cost of bandwidth allocation, while exploring smaller search space for solution. We demonstrate that, IRA accommodates significantly higher number of requests in comparison to a load-balancing resource allocator (LBRA) that does not consider reducing bandwidth between clusters of VMs. IRA also outperforms B-IRA when traffic demands of VMs in an input are not localized.

In today's modern cloud supported applications, the traffic relies on both congestion-responsive transport protocols like TCP and congestion-oblivious transport like UDP including all their variations. As bandwidth is not totally virtualized in today's data centers, the diverse responses of these protocols to congestion lead to inefficiencies and service disruption to some applications. In this paper we present HyGenICC, a simple, distributed and practical congestion control mechanism that puts congestion control back where it belongs, in the network layer, albeit, without modifying the network layer behaviour. To this end IP ECN marking in the switches to indicate congestion, combined with additional packet processing in the hypervisor enable HyGenICC to partition bandwidth among competing virtual machines (VMs) in datacenters effectively. To enable easy deployment in existing data center, HyGenICC design is subjected to several constraints such as: i) freedom of changes to the guest VMs' congestion control mechanism, and ii) reliance only on switch capabilities that are already available in today's commodity switches. We evaluate HyGenICC via extensive simulation in the ns2 network simulator.

Data centers often hold tens to hundreds of thousands of servers in order to offer cloud computing services at scale. Ethernet switching and IP routing have their own advantages and limitations in building data center networks. Recent research, such as PortLand and BCube, has proposed scalable data center network designs. A common feature of these designs is that their addressing and routing are customized to specific topologies. In this paper, we propose a generic addressing, routing and forwarding protocol for data center networks, which works on arbitrarily layered'' network topologies. We first form the network as a multi-rooted tree. Each network node (i.e., hosts and switches) is then assigned one or more locators, and each locator encodes a downward path from the roots to this node. Data center networks often have rich path diversity, so tracking all locators of a destination node will cause switches to have very large forwarding tables. We further use a new forwarding model to reduce the forwarding states. In addition, the multiple-locator mechanism brings built-in support for multi-path routing, load balancing and fault tolerance. Evaluations based on simulations and prototype experiments demonstrate that our proposal achieves our design goals.

Data centers are a key building block in the rapidly growing area of internet technology. A typical data center has tens of thousands of servers, and communication between them must be flexible and robust. Vortex light beams have orbital angular momentum and can provide a useful and flexible method for optical wireless communication in data centers. Vortex beams can be generated with orbital angular momentum but independent of polarization, and used in a multiplexed system. We propose a multiplexing vortex system to increase the communication capacity using optical wireless communication for data center networks. We then evaluate performance. This paper is intended for use as an engineering guideline for design of vortex multiplexing in data center applications.

Today's data center often employs virtualization to allow multiple enterprise applications to share a common hosting platform in order to improve resource and space utilization. It could be a greater challenge when the shared server becomes overloaded or enforces priority of the common resource among applications in such an environment. In this paper, we propose Apad, a feedback-based resource allocation system which can dynamically adjust the resource shares to multiple virtual machine nodes in order to meet performance target on shared virtualized infrastructure. To evaluate our system design, we built a test bed hosting several virtual machines which employed Xen Virtual Machine Monitor (VMM), and using Apache server along with its workload-generated tool. Our experiment results indicate that our system is able to detect and adapt to resource requirement that changes over time and allocate virtualized resources accordingly to achieve application-level Quality of Service (QoS).

Data centers (DCs), owing to the exponential growth of Internet services, have emerged as an irreplaceable and crucial infrastructure to power this ever-growing trend. A DC typically houses a large number of computing and storage nodes, interconnected by a specially designed network, namely, DC network (DCN). The DCN serves as a communication backbone and plays a pivotal role in optimizing DC operations. However, compared to the traditional network, the unique requirements in the DCN, for example, large scale, vast application diversity, high power density, and high reliability, pose significant challenges to its infrastructure and operations. We have observed from the premium publication venues (e.g., journals and system conferences) that increasing research efforts are being devoted to optimize the design and operations of the DCN. In this paper, we aim to present a systematic taxonomy and survey of recent research efforts on the DCN. Specifically, we propose to classify these research efforts into two areas: 1) DCN infrastructure and 2) DCN operations. For the former aspect, we review and compare the list of transmission technologies and network topologies used or proposed in the DCN infrastructure. For the latter aspect, we summarize the existing traffic control techniques in the DCN operations, and survey optimization methods to achieve diverse operational objectives, including high network utilization, fair bandwidth sharing, low service latency, low energy consumption, high resiliency, and etc., for efficient DC operations. We finally conclude this survey by envisioning a few open research opportunities in DCN infrastructure and operations.

The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

The problem of energy consumption in data centers has attracted many researchers interest recently. This paper proposes an optimal energy consumption Software Defined Network (SDN) data center model using the dynamic activation of hosts and switches. We model switches and hosts as queues and formulate a Mixed Integer Linear Programming (MILP) model to minimize energy consumption while guaranteeing Quality of Service (QoS) of data center. Our purpose is minimizing static power, port power, and memory power of data centers. Since the problem is NP-hard, we adopt Simulated Annealing algorithm to obtain the solution. Through numerical experiment, we could observe that our model is able to save reasonable energy compared to the full operation data center model.