Distributed algorithm

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

Coalition Formation Games for Collaborative Spectrum Sensing

Abstract: Collaborative spectrum sensing (CSS) between secondary users (SUs) in cognitive networks exhibits an inherent tradeoff between minimizing the probability of missing the detection of the primary user (PU) and maintaining a reasonable false alarm probability (e.g., for maintaining good spectrum utilization). In this paper, we study the impact of this tradeoff on the network structure and the cooperative incentives of the SUs that seek to cooperate to improve their detection performance. We model the CSS problem as a nontransferable coalitional game, and we propose distributed algorithms for coalition formation (CF). First, we construct a distributed CF algorithm that allows the SUs to self-organize into disjoint coalitions while accounting for the CSS tradeoff. Then, the CF algorithm is complemented with a coalitional voting game to enable distributed CF with detection probability (CF-PD) guarantees when required by the PU. The CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e., coalitions that achieve the target detection probability with minimal costs. For both algorithms, we study and prove various properties pertaining to network structure, adaptation to mobility, and stability. Simulation results show that CF reduces the average probability of miss per SU up to 88.45%, relative to the noncooperative case, while maintaining a desired false alarm. For CF-PD, the results show that up to 87.25% of the SUs achieve the required detection probability through MWCs.

Distributed coverage verification in sensor networks without location information

Abstract: In this paper, we present three distributed algorithms for coverage verification in sensor networks with no location information. We demonstrate how, in the absence of localization devices, simplicial complexes and tools from algebraic topology can be used in providing valuable information about the properties of the cover. Our approach is based on computation of homologies of the Rips complex corresponding to the sensor network. First, we present a decentralized scheme based on Laplacian flows to compute a generator of the first homology, which represents coverage holes. Then, we formulate the problem of localizing coverage holes as an optimization problem for computing a sparse generator of the first homology. Furthermore, we show that one can detect redundancies in the sensor network by finding a sparse generator of the second homology of the cover relative to its boundary. We demonstrate how subgradient methods can be used in solving these optimization problems in a distributed manner. Finally, we provide simulations that illustrate the performance of our algorithms.

Distributed algorithms for control of demand response and distributed energy resources

Abstract: This paper proposes distributed algorithms for control and coordination of loads and distributed energy resources (DERs) in distribution networks. These algorithms are relevant for load curtailment control in demand response programs, and also for coordination of DERs for provision of ancillary services. Both the distributed load-curtailment and DER coordination problems can be cast as distributed resource allocation problems with constraints on resource capacity. We focus on linear iterative algorithms in which each resource j maintains a set of values that is updated to be a weighted linear combination of the resource's own previous set of values and the previous sets of values of its neighboring resources. This set of values can be used by each node to determine its own contribution to load curtailment or to resource request.

A flexible distributed framework for realising electric and plug-in hybrid vehicle charging policies

Abstract: Motivated by the problems of charging a number of electric vehicles via limited capacity infrastructure, this article considers the problem of individual load adjustment under a total capacity constraint. For reasons of scalability and simplified communications, distributed solutions to this problem are sought. Borrowing from communication networks (AIMD algorithms) and distributed convex optimisation, we describe a number of distributed algorithms for achieving relative average fairness whilst maximising utilisation. We present analysis and simulation results to show the performance of these algorithms. In the scenarios examined, the algorithm's performance is typically within 5% of that achievable in the ideal centralised case, but with greatly enhanced scalability and reduced communication requirements.

Cooperative information-gathering: a distributed problem-solving approach

Abstract: Two approaches to the problem of information-gathering, that may be characterised as distributed processing and distributed problem-solving, are contrasted. The former is characteristic of most existing information-gathering systems, and the latter is central to research in multi-agent systems. The features of complex information-carrying environments and the information-gathering task are examined, demonstrating both the utility of viewing information-gathering as distributed problem-solving and difficulties with viewing it as distributed processing. A new approach is proposed to information-gathering based on the distributed problem-solving paradigm and its attendant body of research in multi-agent systems and distributed artificial intelligence. This approach, called cooperative information-gathering, involves concurrent, asynchronous discovery and composition of information spread across a network of information servers. Top-level queries drive the creation of partially elaborated information-gathering plans, resulting in the employment of multiple semi-autonomous cooperative agents for the purpose of achieving goals and subgoals within those plans. The system as a whole satisfies, trading off solution quality and search cost while respecting user-imposed deadlines. Current work on distributed and agent-based approaches to information-gathering is also surveyed.