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Issues and Opportunities of Cloud Federations

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of Cloud Federations Massimo Coppola in collaboration with Laura Ricci, Emanuele Carlini, Patrizio Dazzi, Ranieri Baraglia XtreemOS IP project - EC IST-FP6-033576 ... – PowerPoint PPT presentation

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Title: Issues and Opportunities of Cloud Federations


1
Issues and Opportunities of Cloud Federations
  • Massimo Coppola in collaboration with Laura
    Ricci, Emanuele Carlini, Patrizio Dazzi, Ranieri
    Baraglia

2
Summary
  • Cloud Computing
  • Where do we come from HPC, Parallel Computing,
    Grids, P2P
  • Federations of Clouds
  • What and why
  • What we inherit from our past experiences
  • Autonomic, P2P, Resource Scheduling
  • Cloud applied to virtual environments
  • Business models for cloud federations

3
Parallelism, to Grid, to Clouds ...
  • To approach todays Clouds, and boldly go beyond
    them, many techniques and theoretical results
    can be reused
  • sometimes are reinvented with a different name...
  • Scheduling and resource management from Parallel
    and Grid Computing
  • P2P techniques to cheaply and widely spread
    information
  • Autonomic management based on performance models
    of applications

4
Grid and Cloud computing with XtreemOS Part 3 -
Basic of System Administration Massimo Coppola
ISTI-CNR, Italy with contributions by Christine
Morin and countless collaborators within
XtreemOS Eurosys 2010, Paris
XtreemOS IP project is funded by the European
Commission under contract IST-FP6-033576
XtreemOS IP project is funded by the European
Commission under contract IST-FP6-033576
4
5
SRDS and RSS
  • SRDS (service and resource discovery service)as
    part of the XtreemOS releases
  • Requested for node selection by the AEM
  • New functionalities
  • Support of multiple underlying DHTs (Scalaris,
    Overlay Weaver)
  • Support of XACML policy filters
  • Support of the new mutithreaded DIXI
  • Tested using up to 500 machines from Grid'5000

6
XtreemOS System
7
Contrail Iaas Federation
  • A Contrail Federation integrates in a common
    platform multiple Clouds, of public and private
    kind.
  • User identities, data, and resources are
    interoperable within the federation, thanks to
  • common supports for authentication and
    authorization
  • common mechanisms for policy definition,
    monitoring, and enforcing of all aspects of QoS
    SLA, QoP, etc.
  • the basis of a common economic model

8
Federation Objectives
  • Develop a Federation support that integrates and
    actively coordinates SLA management provided by
    single Cloud providers
  • Do not disrupt providers business model
  • Cloud administration is not Federation management
  • Allow exploiting a Federation as a single Cloud
  • Cloudbursting to and from the Federation
  • Federation Support must be scalable
  • Number of apps running, providers, resources,
    users

9
Cloud revolutions
  • Is there a place for small Cloud providers?
  • they offer lower scalability, are not worldwide
  • Large Cloud providers are subject to contrasting
    forces
  • concentration data centers where management is
    cheaper
  • placing resources scattered over the internet
    structure, to improve the networking cost
  • m.media streaming and real time enjoy lower
    latencies and round-trips, less overall bandwidth

10
Cloud revolutions
  • Federations as a way to flexibly merge separate
    providers
  • Smooth the size disadvantage
  • Increase the market size
  • Provide a competitive edge as small providers are
    already geographically distributed

11
Distributed Architecture
  • Abstract API is replicated onto each Federation
    access point
  • FAP act as brokers, but share a common view
  • Security, provider status, user actions
  • FAP not restricted to local provider
  • Policies and auth/authZ are common
  • Contention issues
  • Final resource allocation is on providers
  • Shared info helps management
  • AP either hosted by provider, or on independent HW

12
Holistic approach to QoS
  • Extend the set of characteristics to be measured
    on the platform
  • Protection
  • Type of security mechanisms which are in place
  • Auth. Protocols, Encryption mechanisms, Isolation
  • Privacy
  • Guarantees offered by storage holder, network
    infrastructure
  • Geo-localization
  • Can have deep legal implications
  • More in the future
  • E.g. power consumption overall power, efficiency

13
Planning for SLAs
  • Choose the best provider(s) and map the
    application on the virtual resources provided
  • Beside constraints, multiple criteria choice
  • Many user criteria
  • Federation has its own goals
  • balance user satisfaction
  • balance provider satisfaction
  • How do you choose the resources?
  • What if one provider is not enough?

14
Application and SLA splitting
  • Application deployment on multiple providers a
    federation is more than the sum of its providers
  • Type and amount of resources needed
  • Sudden elasticity
  • Peculiar resource dislocation
  • Tough issue
  • Multi-criteria and problem size
  • Both at SLA negotiation and at run-time
  • Matching application structure and SLA
  • Identifying suitable set of providers and mapping

15
Standard interoperation
  • Standards are still flowing in the Cloud
  • except de facto ones
  • Interoperation is mandatory
  • We are building an open-source OVF toolkit ? a
    standard converter
  • with INRIA and XLAB
  • (de)serialize in memory Java structures from to
    OVF and other standards for VM and Application
    description
  • will be extended to deal with SLA standards

16
Future directions
  • Apply autonomic heuristics to Clouds and
    Federations, and develop new ones.
  • New business models to be applied in Cloud
    Federations
  • For Service Providers, Federation aggregators
    and/or end-users
  • W.r.t the security and trust counterpart 24/7
    UCON authorization and geographic SLA
    constraints

17
Digital Virtual Environments
  • Player can move and interact with the surrounding
    environment
  • Shared sense of space among players
  • Modifications of the environment visible to every
    players
  • Area Of Interest (AOI)

18
Virtual Environments
  • Complex and challenging applications
  • High number of players
  • Near real-time constraints
  • Quadratic (or cubic) load (bandwidth, cpu)
    depending on the number of players seasonal
  • QoS requirements depends on the user behavior
  • movements vs interactions

19
Aim of the work
  • Distributed architecture for Virtual Environments
  • scalable in QoS and cost
  • Exploit the (illusion of) infinite resources of
    Cloud Computing and the free resources of user
    machines.

20
Hybrid Architecture?
  • Private server-racks are fine... but they are
    statically sized for the peak load
  • Pure P2P should scale up.. but makes it hard to
    manage the QoS in limit situations
  • Only cloud? Costly for large instances

Combination of the Cloud and P2P to support the
DVE in an inexpensive and QoS-aware fashion
21
Cloud P2P Combination
Letting the cloud manage the bootstrap and peak
load
22
Concrete Architecture
  • State Action Manager (SAM)
  • manages the state. Medium rate, No error
    tolerance, Conflicts
  • Positional Action Manager (PAM)
  • manages the position. High rate, Some error
    tolerance, No conflicts

23
SAM
  • Cloud IAASs runs on a DHT together with users
    machines
  • Heuristics decide when moving load from users to
    Cloud
  • Backups for user machines

w/o heuristic
with heuristic
24
PAM (she likes to gossip!)
  • Wisdom of the Crowds
  • A best-effort gossip-based algorithm
  • Storage Cloud as support
  • Around 70-80 less requests to the Cloud

Percentage of object retrieval using gossip
accurate, slower heuristic
faster heuristic
25
Workload for Simulations
Load and number of players
Positions of objects/avatar
26
Whats next?
  • Elastic provisioning and Prediction in SAM
  • Dynamic management of the AOI in PAM

27
Some References
Carlini E., Coppola M., Dazzi P., Ricci L., and
Righetti G.. Cloud Federations in Contrail.
Euro-Par 2011 Parallel Processing Workshops,
LLNCS 7155, 2012. Carlini, E., M. Coppola, and L.
Ricci. Flexible Load Distribution for Hybrid
Distributed Virtual Environments.
submitted Carlini, E., M. Coppola, and L. Ricci.
Gossip-Based Best-Effort Interest Management for
Distributed Virtual Environments.
submitted Carlini, E., M. Coppola, and L. Ricci
(2010). Integration of P2P and Clouds to Support
Massively Multiuser Virtual Environments. In
Network and Systems Support for Games (NetGames),
2010 9th Annual Workshop on. IEEE, pp.16.
http//ieeexplore.ieee.org/xpl/articleDetails.jsp?
tparnumber5679660
28
Beware!
  • Backup slides behind.

29
Load Characterization
Cloud
P2P
Cloud
30
SAM Architecture
31
PAM Area Coverage
Find a subset of areas that maximize the coverage
is a NP problem
Two heuristic - greedy slower, but more
accurate - score faster, but less accurate
32
Some Collaborations
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