My name's Sarah Clinch from the University of Manchester
I'm Nigel Davies from Lancaster University
I'm Marc Langheinrich from USI Lugano
Together we're presenting work
entitled "Scheduling Content in Pervasive Display Systems"
in which we propose a novel architecture
that decomposes display scheduling
into three distinct stages.
In so doing, we reduce complexity, 9 00:00:18,330 --> 00:00:21:330 allowing developers to isolate issues specific to each stage 10 00:00:21:700 --> 00:00:23:230 and utilise different techniques to overcome them. 11 00:00:23:630 --> 00:00:25,500 Our research was conducted in the context of
the world’s largest and longest-running research testbed
Pervasive display scheduling is the process of determining
which content item should be presented at which point in time
and on which display.
Display platforms are near-ubiquitous, and
none would have been realised
without some fundamental decisions about scheduling.
In early display deployments, this was relatively simple,
but more recently,
these scheduling decisions have become increasingly complex.
Deployments have scaled up, creating new requirements,
for example, to support
synchronised orchestrations across multiple displays.
Simultaneously, a desire to adapt content based on
transient context, together with requirements for interaction,
mean that deterministic schedules may be inappropriate.
Implementing new schedulers that provide complete
coverage of requirements is becoming
an insurmountable barrier for researchers.
Furthermore, the last decade has
brought visions for "open" public display networks
that share and accept content from multiple diverse sources.
These emerging display platforms will require new forms of
scheduler that go beyond those currently available.
Based on a comprehensive literature review,
our paper identifies 11 require- ments for display scheduling,
together with the key approaches taken to date.
We observe that despite 40 years of effort,
none of the scheduling approaches
come close to realising the requirements for
future multimedia signage.
We describe these shortcomings more completely in the paper.
In light of our requirements analysis, we propose
a novel multi-stage approach to scheduling.
Our key insight is that the scheduling problem
needs to be decomposed.
While prior approaches have con- sidered the task of scheduling
to be a single monolithic process
we suggest instead that there are 3 distinct subprocesses:
High Level Goal Setting, Filtering, and Selection.
Implementation and evaluation of this model is given in the paper
For the purposes of this presentation, we will focus on
providing a complete description of the 3 distinct stages.
Our staged model begins with High Level Goal Setting,
in which the scheduling process executes a resource inventory
(i.e. what are the displays and content that form
this scheduling context),
and the gathering of stakeholder expectations.
These stakeholder expectations may pertain to
displays or network as a whole
(e.g. operating hours, no-audio periods),
to patterns of visible behaviour across the network
(e.g. showing advertising no more than 10% of the time),
to the behaviour of individual content items
(e.g. to always show the lunch menu at noon),
or to interactions between
the displays and content, and their environment
(e.g. to avoid de-scheduling content that is
presently receiving interaction).
The goal management component integrates policies
expressed by stakeholders together with the inventory data
and exports these in a format to be processed in subsequent
stages. In our example imple- mentation, both are exported as
a Content Descriptor Set (see the paper for more details).
During the Filtering stage, the scheduling process
attempts to restrict the content
by removing all items that are inappropriate for playback.
We can think of the Filtering stage as having only 2 inputs:
the content items with their associated constraints
(i.e. the output from the previous stage),
plus a set of contextual data including sensor feeds.
If the constraints associated with a content item
clearly cannot be met then this item
will not progress any further through the scheduling process.
While in some settings, the resulting content may only be
a single item, it is likely that in most cases
multiple items will remain. The resolution of these to
a final decision is made in the Selection stage.
The Selection stage operates over a set of
eligible content items, each of which has been
determined to be valid for playback in the target context.
During selection, the goal is to reduce this set to
a single content item to be shown on the given display.
To achieve this, the selection process revisits
the policies and parameters specified during Stage 1.
Contextual information may also be used
to inform decision making.
Since there are potentially a complex set of
co-existing and conflicting policies,
our implementation leverages prior work
on the use of lottery scheduling in pervasive displays.
This is explored in-depth in the paper,
but essentially ensures a probabilistic outcome.
So that's our architectural model – why does this matter?
Firstly, since scheduling itself has rarely been
the primary concern of most pervasive display systems,
the community is yet to agree on either a common vocabulary or a
set of grand challenges for future research.
We believe that our articulation of these three stages
can help future research consider each stage
with equal importance, and promote conversations
that are founded on a common understanding.
Second, we suggest that
subdivision of the scheduling problem
provides accessible entry points and allows developers to focus
their attention on innovating
within the constructs of the articulated stages
rather than trying to do everything in a single approach.
Further work is, however, needed
to determine the interfaces between the three stages.
Thirdly, the separation of concerns
presented in our architecture provides a new opportunity
for the combination of multiple scheduling techniques.
In our own implementation,
lottery scheduling offers an elegant way of allowing
multiple competing or compl- ementary policies to co-exist.
At the beginning of this talk, we suggested that
emerging display platforms are generating requirements
beyond the capabilities of current schedulers.
We hope that the presented model helps to facilitate
new innovation in scheduling to meet these needs.
Such work may include:
Resolving competing scheduling requirements
from different stakeholders.
This could encompass multiplexing,
not just in a single dimension,
but simultaneously over different channels.
Analytics-driven scheduling
that leverages large and diverse data input;
so, for example, using mobility data
to shape scheduling decisions which in turn are intended
to alter pedestrian movement in the environment.
and Viewer-centric scheduling, in which scheduling moves from
“show this content item 10 times on this display” to
“make sure that this viewer sees this content item 10 times”.
And with that, I'm going to conclude the talk.
We look forward to taking your questions.