Distributed algorithm

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

Energy efficient communications in ad hoc networks using directional antennas

Abstract: Directional antennas can be useful in significantly increasing node and network lifetime in wireless ad hoc networks. In order to utilize directional antennas, an algorithm is needed that will enable nodes to point their antennas to the right place at the right time. In this paper we present an energy-efficient routing and scheduling algorithm that coordinates transmissions in ad hoc networks where each node has a single directional antenna. Using the topology consisting of all the possible links in the network, we first find shortest cost paths to be energy efficient. Then, we calculate the amount of traffic that has to go over each link and find the maximum amount of time each link can be up, using end-to-end traffic information to achieve that routing. Finally, we schedule nodes' transmissions, trying to minimize the total time it takes for all possible transmitter-receiver pairs to communicate with each other. We formulate this link problem as solving a series of maximal-weight matching in a graph. Furthermore, we propose a method that can enable our scheduling algorithm to work in a distributed and adaptive fashion. We demonstrate that our algorithm achieves all the possible transmitter/receiver gains possible from using directional antennas. In addition, we illustrate through simulation that our routing scheme achieves up to another 45% improvement in energy cost for routing.

Estimation on graphs from relative measurements

Abstract: Large-scale sensor networks give rise to estimation problems that have a rich graphical structure. We studied one of these problems in terms of how such an estimate can be efficiently computed in a distributed manner as well as how the quality of an optimal estimate scales with the size of the network. Two distributed algorithms are presented to compute the optimal estimates that are scalable and robust to communication failures. In designing these algorithms, we found the literature on parallel computation to be a rich source of inspiration.

Cooperative multihop broadcast for wireless networks

Abstract: We address the minimum-energy broadcast problem under the assumption that nodes beyond the nominal range of a transmitter can collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmission. We refer to this cooperative strategy as accumulative broadcast. We seek to employ accumulative broadcast in a large scale loosely synchronized, low-power network. Therefore, we focus on distributed network layer approaches for accumulative broadcast in which loosely synchronized nodes use only local information. To further simplify the system architecture, we assume that nodes forward only reliably decoded messages. Under these assumptions, we formulate the minimum-energy accumulative broadcast problem. We present a solution employing two subproblems. First, we identify the ordering in which nodes should transmit. Second, we determine the optimum power levels for that ordering. While the second subproblem can be solved by means of linear programming, the ordering subproblem is found to be NP-complete. We devise a heuristic algorithm to find a good ordering. Simulation results show the performance of the algorithm to be close to optimum and a significant improvement over the well known BIP algorithm for constructing energy-efficient broadcast trees. We then formulate a distributed version of the accumulative broadcast algorithm that uses only local information at the nodes and has performance close to its centralized counterpart.

Cluster Content Caching: An Energy-Efficient Approach to Improve Quality of Service in Cloud Radio Access Networks

Abstract: In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantages of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.

A Responsive Distributed Routing Algorithm for Computer Networks

Abstract: A new distributed algorithm is presented for dynamically determining weighted shortest paths used for message routing in computer networks The major features of the algorithm are that the paths defined do not form transient loops when weights change and the number of steps required to find new shortest paths when network links fail is less than for previous algorithms Specifically, the worst case recovery time is proportional to the largest number of hops h in any of the weighted shortest paths For previous loop-free distributed algorithms this recovery time is proportional to h2