Information Technology Reference
In-Depth Information
4.5 Concluding Remarks
ICT increasingly pervades our dynamic natural and built environments. Decen-
tralized movement analysis results from the application of decentralized spatial
computing (DeSC) concepts for CMA. I argue in this chapter that decentraliza-
tion offers one strategy for coping with emerging big data streams. Initial work
reflected in this topic and observed in related work indicates the integration of DeSC
and CMA and puts forward promising concepts for coping with big data emerging
ubiquitous spatial information systems, that in most cases involve some form of
mobility.
Movement poses a set of additional challenges to DeSC, but also offers unique
opportunities for handling big data streams emerging from dynamic ubiquitous spa-
tial systems. Movement means constantly changing network and neighborhood struc-
tures and temporarily broken communication links. However, mobile nodes can carry
around information tokens and overcome unfavorable node constellations. Most
typical reasons given for DeSC in the first place (Duckham 2012 ), also hold for
decentralized movement analysis scenarios. Local computing reduces information
overload in flooded sinks and safeguards user privacy. Mobile systems can be very
flexible, resilient and scalable, since added nodes easily extend systems that must
grow. Latency allows nodes to explore spatial variables and exchange and enrich the
captured information.
Just as in DeSC scenarios in general, decentralized movement analysis problems
challenge system and algorithms designers with very peculiar limitations and con-
straints. The work reported on in this volume in many cases faced such challenges
by trading benefits in one aspect for costs in another. Algorithms traded a limited
spatial perception versus temporal perception, quality of service versus level of pri-
vacy, error of omission versus error of commission, latency versus detection error, or
computational complexity versus latency. In some application contexts it is perfectly
acceptable to get a task done only after a given latency period or it is equally accept-
able to get a result, possibly even only an approximation, instead of the best possible,
exact result. However, the question whether or not decentralized movement analysis
as a form of DeSC can perform just as well as any centralized system remains on
open research question.
References
Ahas, R., Silm, S., Järv, O., Saluveer, E., & Tiru, M. (2010). Using mobile positioning data to model
locations meaningful to users of mobile phones. Journal of Urban Technology , 17 (1), 3-27.
Arampatzis, T., Lygeros, J., & Manesis, S. (2005). A survey of applications of wireless sensors
and wireless sensor networks. In Proceedings of the 2005 IEEE International Symposium on
Intelligent Control and Mediterrean Conference on Control and Automation , pp. 719-724.
Augusto, J. C., & Shapiro, D. (Eds.). (2007). Advances in Ambient Intelligence, Volume 164 of
Frontiers in Artificial Intelligence and Applications . Amsterdam, NL: IOS Press.
 
Search WWH ::




Custom Search