Mobile Agents in Healthcare, a Distributed Intelligence Approach - Computational Intelligence in Healthcare: Advanced Methodologies - page 50

needed in medical environments, because it is based on storing some key data over
many computers in the network to ease the searches.
- Web services can be a good solution, but are not flexible enough. They can contact
with a set of institutions but it is difficult to dynamically increase it to reach more
data. Web services do not have a pro-active nature, and it usually implies working
in a synchronous way, so all systems must be available when a request is done.
- Mobile agents can stand as the most well fitted technology for MedIGS. They have
pro-active nature, they can be sent to search over a set of data sources in an asyn-
chronous way dealing with resources unavailability or heavy load. And they can
choose where and when to go and also dynamically change their itinerary to visit
new locations. Although one of the disadvantages of the agents is the complexity
of guaranteeing their security, recent agent driven security developments [1] have
solved the most important issues related to this fact.
The multi-agent paradigm has been shown to address procedural complexity issues in
the health care information systems arena. It can be used with success for modeling
complex communication processes, building highly distributed systems and overcom-
ing the cost and technical demand of a central systems approach [42]. Besides all known
characteristics of agents such as sociability, pro-activity and adaptive behavior, the mo-
bility of the agents has been used in the healthcare domain in order to ease the de-
velopment of data integration mechanisms and to provide data availability throughout.
Mobility tends also to be used for overcoming issues originating from connectivity in-
stability, load balancing, or complex legacy systems interfacing.
Authors point out several additional reasons as advantages for the use of mobile
agents : the ability to optimize computational load distribution, and the ability to handle
failure; the need to handle instable or dynamically changing communication channels
[45]. Support for a more flexible peer-to-peer model, scalability and decentralization of
control and data [27] is also pointed out.
3.1.2 Issues, Challenges, and Requirements
MedIGS arise for networked and distributed medical systems when considering patient
mobility. Its architecture is supposed to fulfill the requirements of modern health insti-
tutions, where roaming patients contribute to a highly distributed data scenario where
useful information is digitally unreachable outside each institutional island. Current sit-
uation has important drawbacks:
- Data are distributed and the location where they are actually stored is often un-
known.
- A common database is often unfeasible because of its cost and technical require-
ments.
- Medical institutions usually prefer to keep control of their own medical data.
- Remote on-line data retrieval is not always possible, especially when considering
network disruptions, high latencies or specific search procedures.
From this situation, and the need for data integration at the inter-institutional level,
several questions arise: