Accelerated Distributed Average Consensus via Localized Node State Prediction
نویسندگان
چکیده
منابع مشابه
Distributed n-player approachability via time and space average consensus
In this paper we consider repeated coalitional games with transferable utilities (TU) over networks. Namely, we consider a set of n players that have to distribute among themselves a vector of rewards (one for each player). In our network version there is no coordinator allocating the rewards, but the agents have to agree on a common time-averaged vector by updating the local estimates of the r...
متن کاملSource Coding Optimization for Distributed Average Consensus
PILGRIM, RYAN ZACHARY. Source Coding Optimization for Distributed Average Consensus. (Under the direction of Dror Baron.) Consensus is a common method for computing a function of the data distributed among the nodes of a network. Of particular interest is distributed average consensus, whereby the nodes iteratively compute the sample average of the data stored at all the nodes of the network us...
متن کاملDistributed Stopping for Average Consensus in Digraphs
We consider how iterative strategies for asymptotic average consensus in directed graphs (digraphs) can be adapted so that the nodes can determine, in a distributed fashion, a stopping criterion that allows them to terminate the execution of the iteration when approximate average consensus has been reached. The nodes are said to have reached approximate average consensus when each of them has a...
متن کاملAccelerated consensus via Min-Sum Splitting
•Common choice is Metropolis-Hastings: W M H i j = { 1/(2dmax) if {i , j } ∈ E 1−di /(2dmax) if i = j 0 otherwise •Rate of convergence is controlled by ρ(W −11T /n). • min{ρ(W −11T /n) : W symmetrical} is a convex problem (SDP). •Optimal matrix yields slow rate O(D2), achieved by W M H . •Lower-bound: Ω(D), where D is graph diameter. •To get fast rates, two approaches have been developed indepe...
متن کاملDistributed Solution of Large-Scale Linear Systems via Accelerated Projection-Based Consensus
Solving a large-scale system of linear equations is a key step at the heart of many algorithms in machine learning, scientific computing, and beyond. When the problem dimension is large, computational and/or memory constraints make it desirable, or even necessary, to perform the task in a distributed fashion. In this paper, we consider a common scenario in which a taskmaster intends to solve a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2009
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2008.2010376