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cycle of satellites and stations management must
include fast reaction to new events, allocation of
orders to resources, scheduling of orders/resources,
optimization of orders (if time is available),
communication with users, monitoring of plan
execution, re-scheduling in case of a growing gap
between the plan and reality.
The revision of the schedule must be made by
the allocation of operations to open time slots or by
solving conflicts between operations that can be
shifted to previously allocated resource or re-
allocated / swapped to the new resources.
Communication with users means supporting a
dialogue with the users via mobile phones or other
tools initiated by either side at any time.
The developed approach is based on a “holon”
concept of PROSA system (Brussel, 1998) where
specific classes of agents of “orders”, “products”
and “resources” were introduced as well as a “staff”
agent which monitors results and advises other
agents when required.
To make this approach more flexible and
efficient the concept of Demand-Supply Networks
(DSN) was introduced where agents of demands and
supply are competing and cooperating on Virtual
Market (VM). In the concept any agent (holon) of
physical or abstract entity can generate “small”
demand and supply agents, which follow the specific
requirements.
As a result, the schedule can be formed as a kind
of requirement-driven network of operations which
can be easily adapted by events in real time
(Skobelev, Vittikh, 2003, Skobelev, Vittikh, 2009).
The core part of the method of adaptive
scheduling can be identified as the following:
1. The number of classes of demand and supply
agents represents specifics of the problem
domain with the required level of granularity.
2. Satisfaction function and function of bonuses /
penalties are represented by linear combination
of multi-criteria objectives, preferences and
constraints of each agent.
3. Protocols are defined which specify how to
identify conflicts and find trade-offs with the
open slots, shifts and swaps of operations.
4. A schedule formed in the process of DSN
agents self-organization is based on decision-
making and interaction of agents.
5. Special event procession protocols are
triggered when new events occur (for example,
arrival of a new demand):
a. An agent is allocated to a demand as it
arrives into the system. The Demand
Agent sends a message to all agents
assigned to available resources stating
that it requires a resource with particular
features and it can pay for this resource
with a certain amount of virtual money.
b. All agents representing resources with
all or some specified features and with
the cost smaller or equal to the specified
amount of money, offer them to the
Demand Agent.
c. The Demand Agent selects the most
appropriate free resource from those on
offer. If no suitable resource is free, the
Demand Agent attempts to obtain a
resource, which has already been linked
to another demand, by offering to that
demand some compensation.
d. The Demand Agent who has been
offered some compensation considers
the offer. It accepts the offer only if the
compensation enables it to obtain a
different satisfactory resource and at the
same time increase the overall value of
the system.
e. If the Demand Agent accepts the offer,
it reorganises the previously established
relationship between that demand and
resource and search for a new
relationship with resource increasing the
overall value of the system.
f. The same process is running for
Resource agents which are able to
generate Supply agents with specific
context-based requirements.
6. The above process is repeated until all
resources are linked to orders and there is no
way for agents to improve their current state or
until the time available is exhausted.
To achieve the best possible results agents use
the virtual money that regulates their behaviour. The
amount of virtual money can be increased by getting
bonuses or decreased by penalties depending of their
individual cost functions. The key rule of the
designed VM is that any agent that is searching for a
new better position in the schedule must compensate
losses to other agents that change their allocations to
resources, and propagation of such wave of changes
is limited by virtual money (Skobelev, Vittikh,
2009).
Therefore, the final schedule is built as a
dynamic balance of interests (consensus) of satellites
and stations agents that negotiate for their position in
the network schedule and plan their work by shifting
and reallocating time slots with the view on their
objectives and interest of the whole swarm.
RealTimeSchedulingofDataTransmissionSessionsinaMicrosatellitesSwarmandGroundStationsNetworkBasedon
Multi-AgentTechnology
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