1. SLA INFORMATION MANAGEMENT THROUGH
DEPENDENCY DIGRAPHS: THE CASE OF
CLOUD DATA SERVICES
Katerina Stamou, Verena Kantere, Jean-Henry
Morin
Institute of Services Science, University of Geneva,
Switzerland
and Michael Georgiou
Cyprus University of Technology, Cyprus
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2. In a nutshell..
2

The term SLA data management encloses data operations that may take
place before, during or after the service level agreement (SLA) and service
execution.

The systematic management of SLA data is required for the automation of
SLAs and of service management processes (e.g. auditing, monitoring) that
generate a new cloud computing market and add business value in a
service-oriented economy.

We propose that the systematic management of SLAs can be efficiently
achieved using a digraph data model that perceives SLA elements and
their data relations as operational pipelines.

Service Level Agreements
dependency graphs.

A dependency graph is defined as a directed graph that contains
properties.- Secure Cloud edges security mini-track, Hawaii,
Graph computing denote dependencies among connected
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component pairs.
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can
be
formalized
and
processed
as

3. Agenda
3
Definitions, problem description
 SLA
formalization:
anatomy,
service
dependencies
 SLA data management requirements
 SLA digraph data model: WSLA [1] into a
property digraph
 Data service provisioning scenario: service
properties, SLA template
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 Ongoing work: SLA representation as a triple1/10/2014

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4. Definitions, problem description
4

Service Level Agreements (SLAs) express mutually agreed service
levels between providers and customers [1]. SLAs define quality of
service (QoS) criteria, along with functional service properties.

The definition and structure of SLAs for cloud computing services
are not yet standardized.


The term “systematic SLA data management” describes the
process of automated SLA formulation, storage and processing
according to a dynamic, adaptable data-schema and by one or more
backend supporting data-stores or DBMS.
SLA data management through graph data structures allows for
numerous traversal and filtering options that support the service and
SLA management over distributed virtual resources that are
dominated by availability and demand.
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5. SLA anatomy:
Web Service Level Agreement (WSLA), IBM [1]
5
Signatories, third parties: customerprovider pair and their connections to third
party support for the service execution.
Service
description:
decomposition and hierarchical
classification of service objects or
operations, whose accumulation
and/or combination constitutes the
service definition.
Guarantees: obligations, typically from the provider part, to fulfill agreed and
promised levels or service provisioning. IBM distinguishes between
measureable targets (objectives) and predefined actions that occur during the
serviceHICSS 47 - Secure Cloud computing security mini-track, Hawaii,
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6. SLA formalization: service
dependencies
6




According to Keller et al [2], service dependencies represent
customer/provider relationships that are reflected to cooperating
components in a distributed service management system.
The term "dependency"defines the relationship between a
dependent service component that requires an operation
performed by an antecedent component in order for the former
to execute its function.
Service dependencies between internal SLA components can
be translated as actions (rules) that are fired when a predefined
condition is triggered.
Service dependencies are reflected in the SLA by:


Identified relationships between SLA components of the same service
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networks

7. 7
SLA data management
requirements
Data criteria/ SLA
components
SLA
paramet
er
Metrics
SLOs
Action
guarantee
s
SLA
doc
exampleSLA mgt
operations
accessibility,
integrity
✖
✖
✖
✖
✖
measurement,
auditing
velocity rate
high
high
high
low
na
real-time monitoring
replication, staging
✖
✖
na
na
✖
real-time value
evaluation
dependencies
✖
na
✖
✖
✖
alerts, actions
cleanness
✖
✖
✖
✖
✖
auditing,
guaranteeevaluation
accuracy
✖
✖
✖
✖
✖
real-time monitoring,
auditing
ownership,
authenticity
✖
✖
✖
✖
✖
auditing, guarantee
definition
✖
function definition,
metric evaluation
heterogeneity - Secure ✖ computing security mini-track, ✖
✖
✖
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8. SLA digraph formalization skeleton
8
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9. Data Service scenario (& next 3
slides)
9




A service provider offers deployed relational databases. The
scenario assumes alternative provisioning configurations
according to:
 Database isolation, data sharing
 DB/Schema administration
 Storage partitioning
Exercise goal: data service profiling and provisioning metrics.
Method: a data service representation as a collection of
attributes; map attributes to service provisioning semantics;
generate SLA template(s).
Scenario example, 3 service types:
 Separate DB, Separate schema (ST1)
 Shared DB, Separate schema (ST2)
 Shared - DB, Shared schemamini-track, Hawaii,
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10. 10
Data Service scenario
infrastructure
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11. 11
Data service properties
(scenario)
Resource/System
characteristics
ST ST
1
2
OS platform:
Windows, Unix, Linux
(32/64)
✔
CPU (family
type/frequency)
ST
3
✔
ST
1
ST
2
DB instance/Schema nr.
✔
✔
DB memory (MB)
Processor
✔
•Classification by service
(nr/frequency) generate
type to
SLA
Database/Schema criteria
✔
✔
DB memory per connection
(MB)
ST
3
✔
DB/Schema size (MB/GB)
✔
✔
DB/Schema operations
DB/Schema growing ratio
ST
✔
1
ST
✔
2
ST
3
✔
✔
✔
✔
✔
✔
✔
✔
✔
template(s).
DB shutdown/start-up
•The three service types DB/Schema administration
On-demand
represent three service DB/schema/table backups
description branches that DB/schema/table restores
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belong to the same SLA
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12. Separate DB, Separate schema
SLA template example (scenario)
12
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13. Ongoing work
13
SLA model representation in triple format.
 Advantages from SLA data management
through graphs: traversal and filtering
opportunities through RDF triple stores.
 AllegroGraph [3] servers on Amazon WS
[4] resources to evaluate the SLA graph
model for identified use cases that are
positioned in the cloud computing setting.

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14. On-going work: SLA graph model in
the Allegro triple store
14
Our current experimentation
uses:
•AllegroGraph server instances
on Amazon WS to simulate the
selection and exchange of
service
offers
through
distributed
RDF
graph
repositories.
•Synthetic data taken from real
service offers as advertised in
Amazon WS to compose SLA
data repositories for the cloud
simulation.
•The tests aim to evaluate the
efficiency, expressiveness and
usability of the proposed SLA
data model by experimenting
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use
case
over
virtual
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15. Thank you!
15
SLA template as a property digraph can be reached at:
http://thinkcloud.unige.ch/SLAgraph/ (using the
NetworkX [5] programming library
Q&A: aikaterini.stamou@unige.ch
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16. References
16
1.
2.
3.
4.
5.
H. Ludwig et al., “Web Service Level Agreement
(WSLA) Language Specification,” IBM Corporation,
2003.
A. Keller, U. Blumenthal, and G. Kar, “Classification
and Computation of Dependencies for Distributed
Management,” in Proc. of the Fifth IEEE Symposium
on Computers and Communications (ISCC 2000),
ser. ISCC ’00. IEEE Computer Society, 2000.
AllegroGraph 4.12.2,
http://www.franz.com/agraph/allegrograph/
Amazon Web Services, http://aws.amazon.com/
NetworkX: High-productivity software for complex
networks, http://networkx.github.io/
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