The broadcast storm problem in a mobile ad hoc network
Wireless Networks - Selected Papers from Mobicom'99
MoCA: A Middleware for Developing Collaborative Applications for Mobile Users
IEEE Distributed Systems Online
MiddleWhere: a middleware for location awareness in ubiquitous computing applications
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Modelling mobility in disaster area scenarios
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Data-centric middleware for context-aware pervasive computing
Pervasive and Mobile Computing
Pervasive and Mobile Computing
Context-Aware Computing Applications
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
CAR: Context-Aware Adaptive Routing for Delay-Tolerant Mobile Networks
IEEE Transactions on Mobile Computing
Adaptive context data distribution with guaranteed quality for mobile environments
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
A distributed information repository for autonomic context-aware MANETs
IEEE Transactions on Network and Service Management
Multihop Ad Hoc Networking: The Theory
IEEE Communications Magazine
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Emergency response scenarios where team members coordinate impromptu towards the common human rescue goal are pushing to the extreme the demand for novel services fully aware of any (dynamically collected) relevant information describing the disaster area, namely context-aware services. Unfortunately, the real-world realization of emergency response context-aware services poses several and still unsolved issues. Timeliness is crucial when dealing with safe critical data, while efficiency and reliability are necessary to guarantee services provisioning in disaster areas. This paper proposes an original solution to increase context data distribution scalability and reliability with agreed quality levels, mainly focusing on data retrieval time. The primary design guideline is to monitor and self-adapt the data distribution task by dynamically reorganizing (a limited number of) data distribution paths. The reported experimental simulation results point out that our solution can significantly reduce exchanged message number and fulfill agreed quality levels.