The book discusses key principles and techniques for evaluating capital expenditure proposals, as well as strategic, qualitative and organizational considerations impacting capital budgeting decisions. We say that the information from the source undergoes a “near-broadcast” if the expected fraction of nodes that receive at least k of the n coded packets is close to 1.Projects presents the entire gamut of capital budgeting. Every other node in the network follows a probabilistic forwarding protocol, in which it forwards a previously unreceived packet to all its neighbours with a certain probability p. The source transmits the n coded packets to its one-hop neighbours. It encodes these data packets into n coded packets in such a way that any node in the network that receives any k out of the n coded packets will be able to retrieve all the original data packets. A source node in the network has some data packets to broadcast. We consider a scenario of broadcasting information over a network of nodes connected by noiseless communication links. IEEE/ACM Transactions on Networking, 2020.

Probabilistic forwarding of coded packets on networks It is anticipated that these will lead to faster and more efficient deployment of outdoor Internet of title = Together they enable quick and automated estimation of coverage in outdoor environments. In the second part of the paper, a method to use readily available geographic information system (GIS) data (for classifying geographic areas into various propagation environments) followed by an algorithm for estimating received signal strength (which is motivated by the first part of the paper) is proposed. It also provides the correct link function for performing a nonlinear regression in our communication systems context. antenna-gain, in measurements that are made across multiple propagation environments. The second purpose is to exploit commonality of physical parameters, e.g. The first purpose is to reduce the bias in the estimated received signal strength arising from estimations performed only on the successfully received packets. The proposed technique achieves two purposes.

The estimation technique combines multiple machine-learning-based regression ideas. In the first part of the paper, a data-driven coverage estimation technique is proposed.

This paper is on a coverage estimation procedure for the deployment of outdoor Internet of Things (IoT).

Projects By Prasanna Chandra