Device 1 Device 2
A t
1
1 t
1
A t
1
1 t
1
A t
1
1 t
1
A t
1
t
2
2 t
2
A 2
Device
A t
1
1 t
1
t
1
t t A t
1
1 t
1
A 2 t
1
t t A 2 t
1
t tA t
1
t
2
2 t
2
A t
1
t
2
t
t
t A t
1
t
2
t
t
tA 2 t
1
t t
A t
1
t
2
t
t
t A t
1
t
2
t
t
t A t
1
t
2
t
t
t
Figure 8: Synchronization test with three devices and a con-
flict, which is handled during the two synchronization steps
at the bottom. Time flows from top to bottom.
assess the platform more thoroughly and compare it
to existing distributed storage solutions.
At the moment, the application informationblocks
are quite small, upto a few kilobytes. If these infor-
mation blocks are increased to several megabytes, it
becomes necessary to synchronize only the parts that
have actually changed, e.g. by using something simi-
lar to the rsync algorithm (Tridgell, 1999).
Some kinds of applications store hierarchical in-
formation, e.g. news postings with comments. At the
moment, the application is responsible for storing the
relationship between these information blocks. If the
storage platform is aware of these relationships, it can
make better decisions on their storage and possible
deletion.
Finally, the current storage platform uses only
time and location (i.e. a circle with a given center
and radius on a map) to denote the IoI. Other forms of
IoI are also interesting, such as author, clearance level
and labels.
6 CONCLUSIONS
The mobile and dismounted domains of defense orga-
nizations cannot use standard cloud storage platforms
because of unreliable network connections. This pa-
per shows that it is possible to design a storage plat-
form that does not depend on any centralized entity.
Instead, it relies on a distributed discovery mechanism
to find partners to synchronize information with.
The term information of interest was introduced,
which is a way for applications to tell the storage plat-
form which information is important. The platform
uses this to decide what information to store and what
to delete when storage capacity is depleted.
A sample application was built to verify that the
proposed storage platform is a viable solution for the
problems we described earlier. It has been shown to
work on several devices, such as personal computers,
mobile phones and tablets. With some manual and
automated tests we also showed that the platform be-
haves as expected with regards to synchronization.
REFERENCES
Amazon (2011). Amazon simple storage service (s3).
http://aws.amazon.com/s3.
Bernstein, P. A. and Goodman, N. (1983). Multiversion
concurrency control - theory and algorithms. ACM
Transactions on Database Systems.
Bohossian, V., Fan, C. C., LeMahieu, P. S., Riedel, M. D.,
Xu, L., and Bruck, J. (2001). Computing in the rain:
A reliable array of independent nodes. IEEE Transac-
tions On Parallel And Distributed Systems.
Brewer, E. A. (2000). Towards robust distributed systems.
Symposium on Principles of Distributed Computing.
Burbank, J. L., Chimento, P. F., Haberman, B. K., and
Kasch, W. T. (2006). Key challenges of military tacti-
cal networking and the elusive promise of manet tech-
nology. IEEE Communications Magazine.
Gulbrandsen, A., Vixie, P., and Esibov, L. (2000). A dns
rr for specifying the location of services (dns srv).
http://www.rfc-editor.org/rfc/rfc2782.txt.
Halinger, G. and Hohlfeld, O. (2010). Efficiency of caches
for content distribution on the internet. Teletraffic
Congress.
Hancock, P. A. and Szalma, J. L. (2008). Performance Un-
der Stress (Human Factors in Defence). Ashgate.
Nguyen, T. T. M. and Dong, T. T. B. (2011). An adaptive
cache consistency strategy in a disconnected mobile
wireless network. IEEE International Conference On
Computer Science and Automation Engineering.
OpenStack (2011). Openstack object storage.
http://openstack.org/projects/storage.
Pilato, C. M., Collins-Sussman, B., and Fitzpatrick, B. W.
(2008). Version Control With Subversion. O’Reilly
Media.
Rhea, S., Wells, C., Eaton, P., Geels, D., Zhao, B., Weather-
spoon, H., and Kubiatowicz, J. (2001). Maintenance-
free global data storage. IEEE Internet Computing.
Shinkuma, R., Jain, S., and Yates, R. (2011). In-network
caching mechanisms for intermittently connected mo-
bile users. Sarnoff Symposium.
Steinberg, D. and Cheshire, S. (2005). Zero Configuration
Networking: The Definitive Guide. O’Reilly Media.
Suel, T., Noel, P., and Trenafilov, D. (2004). Improved
file synchronization techniques for maintaining large
replicated collections over slow networks. Interna-
tional Conference on Data Engineering.
Thomas, T. L. (2000). Kosovo and the current myth of in-
formation superiority. Parameters.
Tridgell, A. (1999). Efficient algorithms for sorting and syn-
chronization. PhD thesis, Australian National Univer-
sity.
Vesperman, J. (2006). Essential CVS. O’Reilly Media.
ACLOUDSTORAGEPLATFORMINTHEDEFENSECONTEXT-MobileDataManagementwithUnreliableNetwork
Conditions
467