of the network. It was recently proved that in the context of local decision, there are some decision problems such that (1) they cannot be solved without unique identifiers, and (2) unique node identifiers leak a sufficient amount of information such that the problem becomes solvable (PODC 2013). In this work

We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of touters and a packer's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router

that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. We apply the algorithm to image segmentation using two different kinds of local neighborhoods in constructing the graph, and illustrate the results with both real and synthetic images. The algorithm

of block propagation, and, thus, makes the distribution more efficient. This is particularly important in large unstructured overlay networks, where the nodes need to make decisions based on local information only. We compare network coding to other schemes that transmit unencoded information (i.e. blocks

, for the identities to play no role, some other kinds of mechanisms for breaking symmetry must be employed, such as edgelabeling or sense of direction. When it comes to local distributed decision problems, the specification of the decision task does not seem to involve symmetry breaking. Therefore, it is expected

Board is the ultimate decision-maker in those areas assigned to it by state and federal laws and regulations. In executing that responsibility, the Board is committed to its obligation to ensure that appropriate members of the District participate in developing recommended policies for Board action

Board is the ultimate decision-maker in those areas assigned to it by state and federal laws and regulations. In executing that responsibility, the Board is committed to its obligation to ensure that appropriate members of the District participate in developing recommended policies for Board action

In this paper, an adaptive fusion algorithm is proposed for an environment where the observations and local decisions are dependent from one sensor to another. An optimal decision rule, based on the maximum posterior probability (MAP) detection criterion for such an environment, is derived

This paper presents a new technique to improve the combination of classification decisions obtained from local analysis of patterns. Specifically, a genetic algorithm is used to determine the optimal weight vector to balance the local decisions in the combination process. The experimental results

Abstract — The topology of wireless multihop ad hoc networks can be controlled by varying the transmission power of each node. We propose a simple distributed algorithm where each node makes local decisions about its transmission power and these local decisions collectively guarantee global