Feasibility Study of RFID Technology for Construction Load Tracking

INE/AUTC 10.0

Virtual Backbone Configuration in Wireless Mesh Networks

This paper introduces methods for the minimisation of virtual backbone size in wireless mesh networks, subject to practical constraints. The methods are centralised, which limits their usage to static applications. Four algorithms are presented, one exact and three heuristic. The exact method guarantees to find an optimal solution but runs in exponential time. Of the three heuristics, one is shown to match the performance of the optimal algorithm for all problem instances tested. The problem is constrained to introduce potentially massive levels of redundancy into the network topology, making the designs survivable

Metaheuristics for Wireless Network Optimisation

This paper introduces two new algorithms for the minimum connected dominating set (MCDS) problem with constraints applicable to wireless network design, based on simulated annealing and tabu search principles. Each algorithm is tested on a selection of random graphs and shown to produce significantly smaller connected dominating sets when compared to a number of established methods. The simulated annealing algorithm is found to favour large, sparse graphs while the tabu search heuristic prefers smaller dense instances. In conclusion, we consider the adaptation of these algorithms to hybrid techniques and comment on the possible use of hyper-heuristics

Subsidence over Hampton Roads: SqueeSAR Cosmo-SkyMed Analysis

Presentation by Jessica Morgan of TRE Altamira Inc., Mike Aslaksen of NOAA\u27s National Geodetic Survey, and Dave Maune of Dewberry, for the Hampton Roads Adaptation Forum, October 13, 2017

Revisiting the Tsunami: Health Consequences of Flooding

Morgan and colleagues critically review the evidence on the health consequences of flooding disasters, and consider what interventions are appropriate

Temporal and Spatial Distribution of Finfish Bycatch in the U.S. Atlantic Bottom Longline Shark Fishery

Bycatch in U.S. fisheries has become an increasingly important issue to both fisheries managers and the public, owing to the wide range of marine resources that can be involved. From 2002 to 2006, the Commercial Shark Fishery Observer Program (CSFOP) and the Shark Bottom Longline Observer Program (SBLOP) collected data on catch and bycatch caught on randomly selected vessels of the U.S. Atlantic shark bottom longline fishery. Three subregions (eastern Gulf of Mexico, South Atlantic, Mid-Atlantic Bight), five years (2002–06), four hook types (small, medium, large, and other), seven depth ranges (300 m), and eight broad taxonomic categories (e.g. Selachimorpha, Batoidea, Serranidae, etc.) were used in the analyses. Results indicated that the majority of bycatch (number) was caught in the eastern Gulf of Mexico and that the Selachimorpha taxon category made up over 90% of the total bycatch. The factors year followed by depth were the most common significant factors affecting bycatch

Spanning Tree Objective Functions and Algorithms for Wireless Networks

This paper considers various forms of objective function that may be applied in the calculation of spanning trees in different network situations. Conventional link and path cost approaches are compared to those based on switch or bridge costs more appropriate for wireless applications. Variant objectives are formulated and compared. Although efficient exact algorithmic approaches exist only for the link cost objectives, reasonable approximations for the switch/bridge equivalents are to be found with simple greedy heuristics and better results still through various forms of iterated local search such as tabu search and simulated annealing

Finding Optimal Solutions to Backbone Minimisation Problems using Mixed Integer Programming

Attempts to evaluate heuristic algorithms are often hampered by the lack of known exact solutions with which to compare results. This is true, in particular, in the study of network backbone design - to date, a fairly undeveloped area in mathematical optimisation. This paper uses a Mixed Integer Programming (MIP) approach to find optimal solutions to the problem of backbone minimisation in mesh networks. A simple model is formulated and then adapted to reduce the number of variables and constraints. Network reliability issues are then considered and a more complex model introduced. Finally the model is solved using a commercial solver to generate test instances with which to test the accuracy of a simulated annealing (SA) heuristic. The heuristic is shown to be accurate to within a very small error margin and the strengths and weaknesses of the two approaches are discussed