Resilient Primal–Dual Optimization Algorithms for Distributed Resource Allocation

Adaptive Algorithms in Distributed Resource Allocation

The allocation of scarce, reusable resources over time to interconnected tasks in uncertain and dynamic environments in order to optimize a performance measure is a general problem which arises in many real-world domains. The paper overviews several recent distributed approaches to this problem and compares their properties, such as the guarantees of finding a (near-) optimal solution, their ro...

Communication Complexity of Distributed Resource Allocation Optimization

This paper investigates the communication complexity of distributed resource allocation problems. Communication complexity, which has emerged from computer science, measures the minimal number of communicated bits needed to solve some classes of problems regardless of the used algorithm, when the communication is lossless. We introduce two complexity measures for finding primal/dual saddle poin...

Distributed Newton-type Algorithms for Network Resource Allocation

Most of today's communication networks are large-scale and comprise of agents with local information and heterogeneous preferences, making centralized control and coordination impractical. This motivated much interest in developing and studying distributed algorithms for network resource allocation problems, such as Internet routing, data collection and processing in sensor networks, and cross-...

Distributed resource allocation algorithms for peer-to-peer networks

In peer-to-peer networks, each peer plays the role of client and server. As server, it receives content requests made by other peers and needs to decide on what basis and to what extent it will satisfy these requests by uploading content to others. As client, it addresses its own requests to appropriate peers to download desired content after resources are granted. We consider a network of peer...

Resource Allocation for Wireless Networks: A Distributed Optimization Approach