Stochastic processes as concurrent constraint programs
Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Survivable mobile wireless networks: issues, challenges, and research directions
WiSE '02 Proceedings of the 1st ACM workshop on Wireless security
Energy efficient adaptation of multicast protocols in power controlled wireless ad hoc networks
Mobile Networks and Applications
Outlining an unconventional, adaptive, and particle-based reconfigurable computer architecture
UPP'04 Proceedings of the 2004 international conference on Unconventional Programming Paradigms
Ambient cognitive environments and the distributed synthesis of visual ambiences
Engineering Self-Organising Systems
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Amorphous computing is the study of programming ultra-scale computing environments of smart sensors and actuators \cite{white-paper}. The individual elements are identical, asynchronous, randomly placed, embedded and communicate locally via wireless broadcast. Aggregating the processors into groups is a useful paradigm for programming an amorphous computer because groups can be used for specialization, increased robustness, and efficient resource allocation. This paper presents a new algorithm, called the {\em clubs algorithm}, for efficiently aggregating processors into groups in an amorphous computer, in time proportional to the local density of processors. The clubs algorithm is well-suited to the unique characteristics of an amorphous computer. In addition, the algorithm derives two properties from the physical embedding of the amorphous computer: an upper bound on the number of groups formed and a constant upper bound on the density of groups. The clubs algorithm can also be extended to find the maximal independent set (MIS) and $\Delta + 1$ vertex coloring in an amorphous computer in $O(\log N)$ rounds, where $N$ is the total number of elements and $\Delta$ is the maximum degree.