TY - JOUR
T1 - Coordination capacity
AU - Cuff, Paul Warner
AU - Permuter, Haim H.
AU - Cover, Thomas M.
N1 - Funding Information:
Manuscript received August 19, 2009; revised March 16, 2010. Date of current version August 18, 2010. This work was supported in part by the National Science Foundation (NSF) under Grant CCF-0635318 and in part by STC Grant CCF-0939370. The material in this paper was presented in part at the IEEE International Symposium on Information Theory, Nice, France, June 2007. P. W. Cuff is with the Department of Electrical Engineering at Princeton University, B316 E-Quad, Princeton, NJ 08544 USA (e-mail: [email protected]). H. H. Permuter is with the Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel (e-mail: [email protected]). T. M. Cover is with the Department of Electrical Engineering, Stanford University, Stanford, CA 94305 USA (e-mail: [email protected]). Communicated by H. Yamamoto, Associate Editor for Shannon Theory. Digital Object Identifier 10.1109/TIT.2010.2054651
Funding Information:
Dr. Cuff was awarded the ISIT 2008 Student Paper Award for his work titled ”Communication Requirements for Generating Correlated Random Variables” and was a recipient of the National Defense Science and Engineering Graduate Fellowship and the Numerical Technologies Fellowship.
PY - 2010/9/1
Y1 - 2010/9/1
N2 - We develop elements of a theory of cooperation and coordination in networks. Rather than considering a communication network as a means of distributing information, or of reconstructing random processes at remote nodes, we ask what dependence can be established among the nodes given the communication constraints. Specifically, in a network with communication rates {Ri,j between the nodes, we ask what is the set of all achievable joint distributions p(x1,⋯, xm) of actions at the nodes of the network. Several networks are solved, including arbitrarily large cascade networks. Distributed cooperation can be the solution to many problems such as distributed games, distributed control, and establishing mutual information bounds on the influence of one part of a physical system on another.
AB - We develop elements of a theory of cooperation and coordination in networks. Rather than considering a communication network as a means of distributing information, or of reconstructing random processes at remote nodes, we ask what dependence can be established among the nodes given the communication constraints. Specifically, in a network with communication rates {Ri,j between the nodes, we ask what is the set of all achievable joint distributions p(x1,⋯, xm) of actions at the nodes of the network. Several networks are solved, including arbitrarily large cascade networks. Distributed cooperation can be the solution to many problems such as distributed games, distributed control, and establishing mutual information bounds on the influence of one part of a physical system on another.
KW - Common randomness
KW - Wyner common information
KW - cooperation capacity
KW - coordination capacity
KW - network dependence
KW - rate distortion
KW - source coding
KW - strong Markov lemma
KW - task assignment
UR - http://www.scopus.com/inward/record.url?scp=77955754773&partnerID=8YFLogxK
U2 - 10.1109/TIT.2010.2054651
DO - 10.1109/TIT.2010.2054651
M3 - Article
AN - SCOPUS:77955754773
SN - 0018-9448
VL - 56
SP - 4181
EP - 4206
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 9
M1 - 5550277
ER -