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Above the Clouds: A Berkeley View of Cloud Computing
, 2009
"... personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires pri ..."
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Cited by 955 (14 self)
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personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Acknowledgement The RAD Lab's existence is due to the generous support of the founding members Google, Microsoft, and Sun Microsystems and of the affiliate members Amazon Web Services, Cisco Systems, Facebook, Hewlett-
A View Of Cloud Computing
, 2010
"... Clearing the clouds away from the true potential and obstacles posed by this computing capability. ..."
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Cited by 628 (1 self)
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Clearing the clouds away from the true potential and obstacles posed by this computing capability.
Powernap: Eliminating server idle power
- In International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS
, 2009
"... Data center power consumption is growing to unprece-dented levels: the EPA estimates U.S. data centers will con-sume 100 billion kilowatt hours annually by 2011. Much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still con-sume 60 ..."
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Cited by 219 (4 self)
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Data center power consumption is growing to unprece-dented levels: the EPA estimates U.S. data centers will con-sume 100 billion kilowatt hours annually by 2011. Much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still con-sume 60 % of their peak power draw. Typical idle periods— though frequent—last seconds or less, confounding simple energy-conservation approaches. In this paper, we propose PowerNap, an energy-conservation approach where the entire system transitions rapidly be-tween a high-performance active state and a near-zero-power idle state in response to instantaneous load. Rather than requiring fine-grained power-performance states and complex load-proportional operation from each system com-ponent, PowerNap instead calls for minimizing idle power and transition time, which are simpler optimization goals. Based on the PowerNap concept, we develop requirements and outline mechanisms to eliminate idle power waste in en-terprise blade servers. Because PowerNap operates in low-efficiency regions of current blade center power supplies, we introduce the Redundant Array for Inexpensive Load Shar-ing (RAILS), a power provisioning approach that provides high conversion efficiency across the entire range of Power-Nap’s power demands. Using utilization traces collected from enterprise-scale commercial deployments, we demon-strate that, together, PowerNap and RAILS reduce average server power consumption by 74%.
FAWN: A Fast Array of Wimpy Nodes
, 2008
"... This paper introduces the FAWN—Fast Array of Wimpy Nodes—cluster architecture for providing fast, scalable, and power-efficient key-value storage. A FAWN links together a large number of tiny nodes built using embedded processors and small amounts (2–16GB) of flash memory into an ensemble capable of ..."
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Cited by 212 (26 self)
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This paper introduces the FAWN—Fast Array of Wimpy Nodes—cluster architecture for providing fast, scalable, and power-efficient key-value storage. A FAWN links together a large number of tiny nodes built using embedded processors and small amounts (2–16GB) of flash memory into an ensemble capable of handling 700 queries per second per node, while consuming fewer than 6 watts of power per node. We have designed and implemented a clustered key-value storage system, FAWN-DHT, that runs atop these node. Nodes in FAWN-DHT use a specialized log-like back-end hash-based database to ensure that the system can absorb the large write workload imposed by frequent node arrivals and departures. FAWN uses a two-level cache hierarchy to ensure that imbalanced workloads cannot create hot-spots on one or a few wimpy nodes that impair the system’s ability to service queries at its guaranteed rate. Our evaluation of a small-scale FAWN cluster and several candidate FAWN node systems suggest that FAWN can be a practical approach to building large-scale storage for seek-intensive workloads. Our further analysis indicates that a FAWN cluster is cost-competitive with other approaches (e.g., DRAM, multitudes of magnetic disks, solid-state disk) to providing high query rates, while consuming 3-10x less power. Acknowledgements: We thank the members and companies of the CyLab Corporate Partners and the PDL
The Cost of a Cloud: Research Problems in Data Center Networks
"... This article is an editorial note submitted to CCR. It has NOT been peer reviewed. The author takes full responsibility for this article’s technical content. Comments can be posted through CCR Online. The data centers used to create cloud services represent a significant investment in capital outlay ..."
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Cited by 205 (1 self)
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This article is an editorial note submitted to CCR. It has NOT been peer reviewed. The author takes full responsibility for this article’s technical content. Comments can be posted through CCR Online. The data centers used to create cloud services represent a significant investment in capital outlay and ongoing costs. Accordingly, we first examine the costs of cloud service data centers today. The cost breakdown reveals the importance of optimizing work completed per dollar invested. Unfortunately, the resources inside the data centers often operate at low utilization due to resource stranding and fragmentation. To attack this first problem, we propose (1) increasing network agility, and (2) providing appropriate incentives to shape resource consumption. Second, we note that cloud service providers are building out geo-distributed networks of data centers. Geo-diversity lowers latency to users and increases reliability in the presence of an outage taking out an entire site. However, without appropriate design and management, these geo-diverse data center networks can raise the cost of providing service. Moreover, leveraging geo-diversity requires services be designed to benefit from it. To attack this problem, we propose (1) joint optimization of network and data center resources, and (2) new systems and mechanisms for geo-distributing state.
Devoflow: Scaling flow management for high-performance networks
- In ACM SIGCOMM
, 2011
"... OpenFlow is a great concept, but its original design imposes excessive overheads. It can simplify network and traffic management in enterprise and data center environments, because it enables flow-level control over Ethernet switching and provides global visibility of the flows in the network. Howev ..."
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Cited by 134 (1 self)
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OpenFlow is a great concept, but its original design imposes excessive overheads. It can simplify network and traffic management in enterprise and data center environments, because it enables flow-level control over Ethernet switching and provides global visibility of the flows in the network. However, such fine-grained control and visibility comes with costs: the switch-implementation costs of involving the switch’s control-plane too often and the distributed-system costs of involving the OpenFlow controller too frequently, both on flow setups and especially for statistics-gathering. In this paper, we analyze these overheads, and show that OpenFlow’s current design cannot meet the needs of highperformance networks. We design and evaluate DevoFlow, a modification of the OpenFlow model which gently breaks the coupling between control and global visibility, in a way that maintains a useful amount of visibility without imposing unnecessary costs. We evaluate DevoFlow through simulations, and find that it can load-balance data center traffic as well as fine-grained solutions, without as much overhead: DevoFlow uses 10–53 times fewer flow table entries at an average switch, and uses 10–42 times fewer control messages.
Device Requirements for Optical Interconnects to Silicon Chips
"... Abstract — We examine the current performance and future demands of interconnects to and on silicon chips. We compare electrical and optical interconnects and project the requirements for optoelectronic and optical devices if optics is to solve the major problems of interconnects to future high perf ..."
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Cited by 129 (2 self)
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Abstract — We examine the current performance and future demands of interconnects to and on silicon chips. We compare electrical and optical interconnects and project the requirements for optoelectronic and optical devices if optics is to solve the major problems of interconnects to future high performance silicon chips. Optics has potential benefits in interconnect density, energy and timing. The necessity of low interconnect energy imposes low limits especially on the energy of the optical output devices, with a ~ 10 fJ/bit device energy target emerging. Some optical modulators and radical laser approaches may meet this requirement. Low (e.g., a few fF or less) photodetector capacitance is important. Very compact wavelength splitters are essential for connecting the information to fibers. Dense waveguides are necessary on-chip or on boards for guided wave optical approaches, especially if very high clock rates or dense WDM are to be avoided. Free space optics potentially can handle the necessary bandwidths even without fast clocks or WDM. With such technology, however, optics may enable the continued scaling of interconnect capacity required by future chips. Index Terms—ITRS roadmap, optical interconnections, optical modulators O I.
ElasticTree: Saving Energy in Data Center Networks
- IN NSDI
, 2010
"... Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network’s ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power ..."
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Cited by 106 (4 self)
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Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network’s ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power manager, which dynamically adjusts the set of active network elements — links and switches — to satisfy changing data center traffic loads. We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50 % of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.
Minimizing electricity cost: Optimization of distributed internet data centers in a multi-electricity-market environment
- In Proc. of INFOCOM
, 2010
"... Abstract—The study of Cyber-Physical System (CPS) has been an active area of research. Internet Data Center (IDC) is an important emerging Cyber-Physical System. As the demand on Internet services drastically increases in recent years, the power used by IDCs has been skyrocketing. While most existin ..."
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Cited by 98 (9 self)
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Abstract—The study of Cyber-Physical System (CPS) has been an active area of research. Internet Data Center (IDC) is an important emerging Cyber-Physical System. As the demand on Internet services drastically increases in recent years, the power used by IDCs has been skyrocketing. While most existing research focuses on reducing power consumptions of IDCs, the power management problem for minimizing the total electricity cost has been overlooked. This is an important problem faced by service providers, especially in the current multi-electricity market, where the price of electricity may exhibit time and location diversities. Further, for these service providers, guaranteeing quality of service (i.e. service level objectives-SLO) such as service delay guarantees to the end users is of paramount importance. This paper studies the problem of minimizing the total electricity cost under multiple electricity markets environment while guaranteeing quality of service geared to the location diversity and time diversity of electricity price. We model the problem as a constrained mixed-integer programming and propose an efficient solution method. Extensive evaluations based on reallife electricity price data for multiple IDC locations illustrate the efficiency and efficacy of our approach. I.
Power management of online data-intensive services
- In ISCA
, 2011
"... Much of the success of the Internet services model can be attributed to the popularity of a class of workloads that we call Online Data-Intensive (OLDI) services. These workloads perform significant computing over massive data sets per user request but, unlike their offline counterparts (such as Map ..."
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Cited by 85 (2 self)
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Much of the success of the Internet services model can be attributed to the popularity of a class of workloads that we call Online Data-Intensive (OLDI) services. These workloads perform significant computing over massive data sets per user request but, unlike their offline counterparts (such as MapReduce computations), they require responsiveness in the sub-second time scale at high request rates. Large search products, online advertising, and machine translation are examples of workloads in this class. Although the load in OLDI services can vary widely during the day, their energy consumption sees little variance due to the lack of energy proportionality of the underlying machinery. The scale and latency sensitivity of OLDI workloads also make them a challenging target for power management techniques.
