In a military scenario, commanders need to determine what kinds of information will help them execute missions.
The amount of information available to support each mission is constrained by the availability of information
assets. For example, there may be limits on the numbers of sensors that can be deployed to cover a certain
area, and limits on the bandwidth available to collect data from those sensors for processing. Therefore, options
for satisfying information requirements should take into consideration constraints on the underlying information
assets, which in certain cases could simultaneously support multiple missions. In this paper, we propose a
system architecture for modeling missions and allocating information assets among them. We model a mission
as a graph of tasks with temporal and probabilistic relations. Each task requires some information provided by the
information assets. Our system suggests which information assets should be allocated among missions. Missions
are compatible with each other if their needs do not exceed the limits of the information assets; otherwise,
feedback is sent to the commander indicating information requirements need to be adjusted. The decision loop
will eventually converge and the utilization of the resources is maximized.
Broadcast scheduling has been extensively studied in wireless environments, where a base station broadcasts
data to multiple users. Due to the sole wireless channel's limited bandwidth, only a subset of the needs may be
satisfiable, and so maximizing total (weighted) throughput is a popular objective. In many realistic applications,
however, data are dependent or correlated in the sense that the joint utility of a set of items is not simply the
sum of their individual utilities. On the one hand, substitute data may provide overlapping information, so one
piece of data item may have lower value if a second data item has already been delivered; on the other hand,
complementary data are more valuable than the sum of their parts, if, for example, one data item is only useful
in the presence of a second data item.
In this paper, we define a data bundle to be a set of data items with possibly nonadditive joint utility, and we
study a resulting broadcast scheduling optimization problem whose objective is to maximize the utility provided
by the data delivered.
Timely dissemination of information to mobile users is vital in many applications. In a critical situation, no
network infrastructure may be available for use in dissemination, over and above the on-board storage capability
of the mobile users themselves. We consider the following specialized content distribution application: a group
of users equipped with wireless devices build an ad hoc network in order cooperatively to retrieve information
from certain regions (the mission sites). Each user requires access to some set of information items originating
from sources lying within a region. Each user desires low-latency access to its desired data items, upon request
(i.e., when pulled). In order to minimize average response time, we allow users to pull data either directly from
sources or, when possible, from other nearby users who have already pulled, and continue to carry, the desired
data items. That is, we allow for data to be pushed to one user and then pulled by one or more additional users.
The total latency experienced by a user vis-vis a certain data item is then in general a combination of the push
delay and the pull delay. We assume each delay time is a function of the hop distance between the pair of points
Our goal in this paper is to assign data to mobile users, in order to minimize the total cost and the average
latency experienced by all the users. In a static setting, we solve this problem in two different schemes, one of
which is easy to solve but wasteful, one of which relates to NP-hard problems but is less so. Then in a dynamic
setting, we adapt the algorithm for the static setting and develop a new algorithm with respect to users' gradual
arrival. In the end we show a trade-off can be made between minimizing the cost and latency.
In this paper we propose system architecture for providing direction and dissemination in military environments.
We start with a description of the problem of direction and dissemination. We then present our high level architecture
and describe the functions of the main system components on which we focus. This includes the types of information
and means by which they may be delivered, the filtering and fusion engines employed to focus and limit the information
sent to each personnel, and the schedulers used to determine the order of delivery. We consider a structure that includes
sending information directly to personnel, or depending on bandwidth and delay constraints, sending meta-information
to personnel to assist in self-retrieval of information from a peer-to-peer network of sensors and other personnel. We
illustrate the operation of the architecture using a specific military scenario.