  This paper provides a global picture about the deployment of networked
processing services for genomic data sets. Many current research make an
extensive use genomic data, which are massive and rapidly increasing over time.
They are typically stored in remote databases, accessible by using Internet.
For this reason, a significant issue for effectively handling genomic data
through data networks consists of the available network services. A first
contribution of this paper consists of identifying the still unexploited
features of genomic data that could allow optimizing their networked
management. The second and main contribution of this survey consists of a
methodological classification of computing and networking alternatives which
can be used to offer what we call the Genomic-as-a-Service (GaaS) paradigm. In
more detail, we analyze the main genomic processing applications, and classify
not only the main computing alternatives to run genomics workflows in either a
local machine or a distributed cloud environment, but also the main software
technologies available to develop genomic processing services. Since an
analysis encompassing only the computing aspects would provide only a partial
view of the issues for deploying GaaS system, we present also the main
networking technologies that are available to efficiently support a GaaS
solution. We first focus on existing service platforms, and analyze them in
terms of service features, such as scalability, flexibility, and efficiency.
Then, we present a taxonomy for both wide area and datacenter network
technologies that may fit the GaaS requirements. It emerges that
virtualization, both in computing and networking, is the key for a successful
large-scale exploitation of genomic data, by pushing ahead the adoption of the
GaaS paradigm. Finally, the paper illustrates a short and long-term vision on
future research challenges in the field.
