相关论文: Distributed backbone structure for deterministic a…

A distributed spiral algorithm for distributed optimization in WSN is proposed. By forming a spiral-shape message passing scheme among clusters, without loss of estimation accuracy and convergence speed, the algorithm is proved to converge…

It is widely perceived that leveraging the success of modern machine learning techniques to mobile devices and wireless networks has the potential of enabling important new services. This, however, poses significant challenges, essentially…

Efficient inference of Deep Neural Networks (DNNs) is essential to making AI ubiquitous. Two important algorithmic techniques have shown promise for enabling efficient inference - sparsity and binarization. These techniques translate into…

Network backbones provide useful sparse representations of weighted networks by keeping only their most important links, permitting a range of computational speedups and simplifying network visualizations. A key limitation of existing…

We consider the problem of dominating set-based virtual backbone used for routing in asymmetric wireless ad-hoc networks. These networks have non-uniform transmission ranges and are modeled using the well-established disk graphs. The…

We formulate the resource allocation problem for the uplink of code division multiple access (CDMA) networks using a game theoretic framework, propose an efficient and distributed algorithm for a joint rate and power allocation, and show…

Rapid technological advancements have tremendously increased the data acquisition capabilities of remote sensing satellites. However, the data utilization efficiency in satellite missions is very low. This growing data also escalates the…

This paper focuses on solving a data-driven distributionally robust optimization problem over a network of agents. The agents aim to minimize the worst-case expected cost computed over a Wasserstein ambiguity set that is centered at the…

This work demonstrates the potential of deep reinforcement learning techniques for transmit power control in wireless networks. Existing techniques typically find near-optimal power allocations by solving a challenging optimization problem.…

We study cost-effective communication strategies that can be used to improve the performance of distributed learning systems in resource-constrained environments. For distributed learning in sequential decision making, we propose a new…

Given $n$ wireless transceivers located in a plane, a fundamental problem in wireless communications is to construct a strongly connected digraph on them such that the constituent links can be scheduled in fewest possible time slots,…

Data-parallel SGD is the de facto algorithm for distributed optimization, especially for large scale machine learning. Despite its merits, communication bottleneck is one of its persistent issues. Most compression schemes to alleviate this…

Wireless power transfer and backscatter communications have emerged as promising solutions for energizing and communicating with power limited devices. Despite some progress in wirelessly powered backscatter communications, the focus has…

We present a distributed algorithm that enables a group of robots to collaboratively optimize the parameters of a deep neural network model while communicating over a mesh network. Each robot only has access to its own data and maintains…

We consider the scheduling of arbitrary wireless links in the physical model of interference to minimize the time for satisfying all requests. We study here the combined problem of scheduling and power control, where we seek both an…

We consider a power-controlled wireless network with an established network topology in which the communication links (transmitter-receiver pairs) are corrupted by the co-channel interference and background noise. We have fairly general…

This article investigates the basic design principles for a new Wireless Network Operating System (WNOS), a radically different approach to software-defined networking (SDN) for infrastructure-less wireless networks. Departing from…

The emergence of new wireless technologies together with the requirement of massive connectivity results in several technical issues such as excessive interference, high computational demand for signal processing, and lengthy processing…

We study robust and efficient distributed algorithms for building and maintaining distributed data structures in dynamic Peer-to-Peer (P2P) networks. P2P networks are characterized by a high level of dynamicity with abrupt heavy node…

We consider distributed average consensus in a wireless network with partial communication to reduce the number of transmissions in every iteration/round. Considering the broadcast nature of wireless channels, we propose a probabilistic…