Distributed algorithm

About: Distributed algorithm is a research topic. Over the lifetime, 20416 publications have been published within this topic receiving 548109 citations.

Distributed resource allocation schemes

Abstract: In this article, we discuss distributed resource allocation schemes in which each transmitter determines its allocation autonomously, based on the exchange of interference prices. These schemes have been primarily motivated by the common model for spectrum sharing in which a user or service provider may transmit in a designated band provided that they abide by certain rules (e.g., a standard such as 802.11). An attractive property of these schemes is that they are scalable, i.e., the information exchange and overhead can be adapted according to the size of the network.

REFIM: A Practical Interference Management in Heterogeneous Wireless Access Networks

Abstract: Due to the increasing demand of capacity in wireless cellular networks, the small cells such as pico and femto cells are becoming more popular to enjoy a spatial reuse gain, and thus cells with different sizes are expected to coexist in a complex manner. In such a heterogeneous environment, the role of interference management (IM) becomes of more importance, but technical challenges also increase, since the number of cell-edge users, suffering from severe interference from the neighboring cells, will naturally grow. In order to overcome low performance and/or high complexity of existing static and other dynamic IM algorithms, we propose a novel low-complex and fully distributed IM scheme, called REFIM (REFerence based Interference Management), in the downlink of heterogeneous multi-cell networks. We first formulate a general optimization problem that turns out to require intractable computation complexity for global optimality. To have a practical solution with low computational and signaling overhead, which is crucial for low-cost small-cell solutions, e.g., femto cells, in REFIM, we decompose it into per-BS (base station) problems based on the notion of reference user and reduce feedback overhead over backhauls both temporally and spatially. We evaluate REFIM through extensive simulations under various configurations, including the scenarios from a real deployment of BSs. We show that, compared to the schemes without IM, REFIM can yield more than 40% throughput improvement of cell-edge users while increasing the overall performance by 10~107%. This is equal to about 95% performance of the existing centralized IM algorithm (MC-IIWF) that is known to be near-optimal but hard to implement in practice due to prohibitive complexity. We also present that as long as interference is managed well, the spectrum sharing policy can outperform the best spectrum splitting policy where the number of subchannels is optimally divided between macro and femto cells.

Agent Based Restoration With Distributed Energy Storage Support in Smart Grids

Abstract: The goal of this paper is to present a new and completely distributed algorithm for service restoration with distributed energy storage support following fault detection, location, and isolation. The distributed algorithm makes use of intelligent agents, which possess three key characteristics, namely autonomy, local view, and decentralization. The switch agents will detect, locate and isolate the fault, then restore the load. The distributed energy storage agent will support the system in grid-connected as well as islanded operation. Important restoration issues such as load priority restoration and islanding coordination of multiple distributed energy storage systems will be discussed. Two case studies on the modified IEEE 34 node test feeder will be presented.

Convergence of cognitive radio networks

Abstract: In this paper, we examine the conditions and behavior of several common convergence dynamics from game theory and show how they influence the structure of networks of cognitive radios. We then apply these to previously proposed distributed power control algorithms and describe how they impact network complexity.

Multicast with network coding in application-layer overlay networks

Abstract: All of the advantages of application-layer overlay networks arise from two fundamental properties: 1) the network nodes in an overlay network, as opposed to lower-layer network elements such as routers and switches, are end systems and have capabilities far beyond basic operations of storing and forwarding; 2) the overlay topology, residing above a densely connected Internet protocol-layer wide-area network, can be constructed and manipulated to suit one's purposes. We seek to improve end-to-end throughput significantly in application-layer multicast by taking full advantage of these unique characteristics. This objective is achieved with two novel insights. First, we depart from the conventional view that overlay nodes can only replicate and forward data. Rather, as end systems, these overlay nodes also have the full capability of encoding and decoding data at the message level using efficient linear codes. Second, we depart from traditional wisdom that the multicast topology from source to receivers needs to be a tree, and propose a novel and distributed algorithm to construct a two-redundant multicast graph (a directed acyclic graph) as the multicast topology, on which network coding is applied. We design our algorithm such that the costs of link stress and stretch are explicitly considered as constraints and minimized. We extensively evaluate our algorithm by provable analytical and experimental results, which show that the introduction of two-redundant multicast graph and network coding may indeed bring significant benefits, essentially doubling the end-to-end throughput in most cases.