
180 Park Ave - Building 103
Florham Park, NJ
http://www.research.att.com/~maoy/
Senior Member of Technical Staff - Research, Dependable Distributed Computing Research Department
Declarative Configuration Management for Complex and Dynamic Networks
Yun Mao, Jacobus Van , Xu Chen, Z. Morley Mao
ACM CoNEXT 2010,
2011.
[PDF]
[BIB]
ACM Copyright
(c) ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM CoNEXT 2010 , 2011-12-01.
{Network management and operations are complicated,
tedious, and error-prone, requiring significant human
involvement and domain knowledge. As the complexity
involved inevitably grows due to larger scale networks
and more complex protocol features, human operators are
increasingly short-handed, despite the best effort from existing
support systems to make it otherwise. This paper
presents COOLAID, a system under which the domain knowledge
of device vendors and service providers are formally
captured by a declarative language. Through efficient and
powerful rule-based reasoning on top of a database-like abstraction
over a network of devices, COOLAID enables new
management primitives to perform network-wide reasoning,
prevent misconfiguration, and automate network configuration,
while requiring minimum operator effort. We describe
the design and prototype implementation of COOLAID, and
demonstrate its effectiveness and scalability through various
realistic network management tasks.}

Cloud Resource Orchestration: A Data-Centric Approach
Changbin Liu, Yun Mao, Jacobus Van , Maria Fernandez
In Proceedings of The 5th biennial Conference on Innovative Data Systems Research (CIDR),
The biennial Conference on Innovative Data Systems Research (CIDR) 2011,
2011.
[PDF]
[BIB]
the CIDR conference Copyright
The definitive version was published in Conference on Innovative Data Systems Research (CIDR 2011). , 2011-01-11
Cloud computing provides users near instant access to seemingly
unlimited resources, and provides service providers the opportunity
to deploy complex information technology infrastructure, as a service,
to their customers. Providers benefit from economies of scale
and multiplexing gains afforded by sharing of resources through
virtualization of the underlying physical infrastructure. However,
the scale and highly dynamic nature of cloud platforms impose
significant new challenges to cloud service providers. In particular,
realizing sophisticated cloud services requires a cloud control
framework that can orchestrate cloud resource provisioning, configuration,
utilization and decommissioning across a distributed set
of physical resources. In this paper we advocate a data-centric approach
to cloud orchestration. Following this approach, cloud resources
are modeled as structured data that can be queried by a
declarative language, and updated with well-defined transactional
semantics. We examine the feasibility, benefits and challenges of
the approach, and present our design and prototype implementation
of the Data-centric Management Framework (DMF) as a solution,
with data models, query languages and semantics that are specifically
designed for cloud resource orchestration.