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Department of Compu.ng and Digital System Engineering
LASSU Sustainability on ICT Research Laboratory
Public University, founded in 1934
• 11 campi (4 – city of São Paulo). • 89 Uni8es.
• 92.064 students (undergrad, grad and extension). • 5.860 professors.
• 16.837 administra8ve staff. • 249 undergratua8on programs.
• 239 gradua8on Programs
Source: Anuário Esta8s8co 2013
University of São Paulo
LASSU-PCS-EPUSP • LASSU – Laboratory on Sustainability
• Created in 2010 • 3 professors (Engineering School, Architecture & Urbanism, EACH) • 10 collaborators - Doctorate, Master and Undergrad students and
employees. • Strong Partnership with CEDIR (Center For Discard and Reuse of E-
Waste)
• Main fields of interest • ITC Governance • Network Management oriented to Sustainability Policies • Energy Efficiency applied to:
• SDN (Software Defined Network) • Cloud Computing • Data Centers
• Electronic Waste • Sustainability in Productive Chain • Life Cycle Assessment
Main Partnerships • RNP (Na8onal Network for Research and Educa8on) • ANSP (Academic Network of São Paulo State) • I2Cat – Living Laboratories • University of Illinois – Chicago • FIU – Florida Interna8onal University
• Ericsson Research Sweden, Canada, Finland • Center for InnovaJon -‐ Ericsson Brazil • PETROBRAS • IBM Research – T.J. Watson • MIT CISR (Center For Informa8on System Research) • MIT D-‐Lab • MIT L-‐Lab (Leadership on Sustainability)
Sponsered
Introduction • Trade-off between performance and energy consumption à
challenge • How to correlate quality of service and actions targeting
efficiency improvement? • Is a broader sustainability view possible at network management
level? • How to compare device efficiency and prioritize more efficient
device for multiple network paths? • How to coordinate power-saving features in a heterogeneous
network?
SUStainability oriented Network Management System (SustNMS)
SWITC H / ROUTE RSWITC H / ROUTE RNE TWORK MANAGEMENT S Y S TEM
SUSTAINABILITY MONITOR
ENERGY EFFICIENCY EVALUATOR
POLICY MANAGEMENT FRAMEWORK
DEVICE UPDATER
QUALITY OF SERVICE MONITOR
MANAGEMENT PROTOCOL
AVAILABILITY EVALUATOR
TRAFFIC LOAD FORECAST
POL IC Y MANAGEMENT
TOOLS
POL IC Y DE C IS ION POINT
POL IC Y E NFORC EMENT
PERFORMANCE EVALUATOR
MODE L R E POS ITORY
AVAILABILITY MODEL
POWER MODEL
SWITC H / ROUTE R
SUBSYSTEMS
CARDS / PORTS
FORWARDINGENGINE / CPU
CHASSIS
MANAGEMENT SYSTEM CLIENT
MANAGEMENT PROTOCOL CLIENT
MIB
STATIC POWER METERS
TRAFFIC DATA
SUBSYSTEMS
CARDS / PORTS
FORWARDINGENGINE / CPU
AVAILABILITY DATA
POL IC Y C ONS OLE
POLICY ENFORCEMENT POINT
POL IC IE S R E POS ITORY
Results • S a v i n g s o f 4 3 % w h e n prioritizing energy efficiency
• Savings of 30% when no performance degradation is allowed
• Savings of 27% when a seven-nines reliability constraint is imposed
• Patent application
• 3 papers • 2 Master’s Thesis
Software Router (Linux-kernel based) MPLS-Linux support for TE
Power-saving mode emulation
SustNMS • Monitoring through SNMP
• Policy enforcement through CLI/SNMP • Efficiency evaluation performed using power
profiles derived from the literature
Sponsored by Innovation Center – Ericsson Brazil
Introduction • ICT energy spending is growing
− 2% of worldwide emissions [1] • Networks represent a significant part of this amount
− Voice and Data Networks ~23% in 2020 [1] • And they are usually overprovisioned • There are some research works aiming at saving energy in the network
− Sleeping − Link Rating
• How to bring business together? • How to coordinate the different green functionalities?
Current Research
• Energy efficiency features to save energy in the network à but there is no automated way to “bring” a sustainability high level policy to these features • There is no automated policy refinement method able to handle all the refinement requirements of sustainability-oriented policies
Expected Results • Comprise a method to support the selection of green functionalities using an utility function; • Use Table Lookup for policies translation; • Determine different information models to standardize the definition of policies and comply with the Policy Continuum; • Use parameterized policies to enable dynamicity, besides incorporating time conditions in the description of policies, and having a type of policy to change policies in case of change in scenario.
Sustainability Oriented System based on Dynamic Policies with Automated Policy Refinement (SOS)
Method
System
Busin
ess
Netw
ork
Devic
eInstance
Fase
Parameters, attributes and constraints identification
CallForRefinement
The BusinessPolicy should have the following format: user (when applicable), target (In the netwokr), action (GreenPlan, save energy),
period (night) e policy validity (6 months)
8. Create Policies(Rule constructor)
Discover managed functionalities in each device
A. Fill functionalities details
SNMP / Web / Netconf
E.g. -‐ Save energy in the network at night -‐ Change Energy Source In the netoork in the morning
E.g. -‐Save energy in the network from 9pm to 5am up to 6 months
Business-‐Level Policy Information
Model
System-‐Level Policy Information Model
Information model Retrieval
1.Network parameters, attributes and constraints
Identification
Information Retrieval
Existing technologies attibutes and parameters
Useful data and constrainst to configure energy saving
In the network
Discover resources functionalities
B. Verify functionalities availability
7.Network Configuration Evaluation (Analytical solver / Utility function)
Network Configuration (List of actions and conditions)
9. Verify Policies(Goal and conflicts) Verify
If needed, Request another Network configuration(Change technologies or parameters)
4. Workloads generation(Random, historical
and Forecast)
Workloads todefine possible configurations
Device parameters, attributes and constraints
Identification
Create Policy for the devices
Device-‐Level Policy Information Model
Translate to commands
6. Network configurationgeneration (functionalities combination, restrictions)
Possible Network Configurations (List of actions and conditions)
Utility function parameters
Managed functionalitiesdetails (MFD)
Managed functionalitiesdetails (MFD)
Managed functionalitiesavailable and combinations
Map High-‐Level parameters and attibutes to System-‐Level
(Lookup table)Policy translation
Store Policy
System-‐Level PoliciesSystem-‐Level PoliciesVerify if the policy exists
Business-‐Level PoliciesBusiness-‐Level Policies
Network-‐Level PoliciesNetwork-‐Level Policies
Store Policies
Verify if such a policy exists
CallForRefinement
Mapping to devicetechnologies Policy
Instance-‐Level PoliciesInstance-‐Level Policies
CallForRefinement
Available Devices Functionalities Profile (ADFP)Available Devices Functionalities Profile (ADFP)
Available functionalitiesFunctionalities
5.Match existing functionalities with
the available functionalities
C.Check functionalitiesconflicts
Network-‐Level Policy Information Model
Policy console
InformationModelRetrieval
Store
Target, time condition
2.Check network topologyNetwork Topology
Power Profiles3.Check devices’ power profiles
ModelRepositoryModel
Repository
Discover each device and its connections
Data input and initial translation
Network data gathering
Scenarios combination and selection using a Utility Function
Decision Tree generation and policies deployment
𝑼𝑭 = 𝒑𝒍 ∗ 𝟏 ∑ 𝑬𝒏𝒆𝒓𝒈𝒚𝑨𝒇𝒕𝒆𝒓𝑺𝒂𝒗𝒊𝒏𝒈𝒔𝑹𝒐𝒖𝒕𝒆𝒓 𝒌𝒏𝒌=𝟎∑ 𝑬𝒏𝒆𝒓𝒈𝒚𝑩𝒂𝒔𝒆𝒍𝒊𝒏𝒆𝑹𝒐𝒖𝒕𝒆𝒓 𝒌𝒏𝒌=𝟎
>
Utility Function (our proposal)
Method
Sponsored by Innovation Center – Ericsson Brazil
Introduction • Energy consumption demand
• Datacenters • Operators
• New paradigm: Distributed Telecom Clouds
• Objective: Expand SOS to consider automated policies in the context of Distributed Telecom Clouds and Smart Grids
Current Research
• Sustainability-oriented policies refinement and energy efficiency functionalities management à SOS
• Cloud platforms and virtualization
• Smart Grids and renewable sources
Deliverables • Green service levels differentiation • Sustainability oriented policies specific to the Distributed Telecom Cloud Environment • Analysis of how Smart Grids can support • Expansion of SOS to the distributed telecom cloud environment • Specification and implementation of SustClouds
Sustainability Oriented Telecom Clouds with Automated Policy Refinement (SustClouds)
Continuation
Continuation
Continuation
Sustainable practices
Rational use of resources
Electrical sourcessmart grid
Compute Network Storage Cooling
Devices
Instances
SOS scope
Continuation
Policy
refinement
Distributed telco cloud powered by renewable energy sources
Cloud orchestration extensions for dynamicpower sources in smart grids
Extensions of green policy refinement for integrating new types of resources (physical infrastructure) and associated policies, while controlling availability trade-‐offs
Sponsored by Innovation Center – Ericsson Brazil
LASSU Main Research Areas • Energy Efficiency applied to:
• SDN (SoZware Defined Network) • Cloud Compu8ng • Data Centers
• Sustainability Policies for ICT System • Digital technologies as Driver for Sustainability. • Smart Grids. • ICT Governance • Life Cycle Assessment • Sustainable Produc8ve Chain
Thanks