On The Ambiguity Of The Solution Of The Muskhelishvili-omnes Integral Equation

The solution of the Muskhelishvili-Omnes Integral Equation is ambiguous by a real polynomial. The coefficients of this polynomial can be fixed either by the knowledge of the low energy parameters or by the asymptotic behavior of the form factor. The role of the contact terms of the low energy effective Lagrangian is explicitly analysed

Using mobile sinks in wireless sensor networks to improve building emergency response.

We propose an opportunistic routing scheme for wireless sensor networks operating in volatile environments. In particular, we consider a sensor field for sensing and reporting on buildings during fires, where sensors are progressively being destroyed by the fire. We envisage firefighters equipped with small computers which can act as mobile sink nodes, offering transient shorter routes for relaying data, and offering connectivity to disconnected areas of the network. We examine different ways in which these uncontrolled mobile sinks could enhance performance, and develop protocols for advertising the presence of the mobile sinks, gathering data for forwarding, and prioritising disconnected regions. We evaluate the performance in simulation, and on randomly damaged networks, we show that we can increase the data delivery by up to 50%

Autonomous discovery and repair of damage in Wireless Sensor Networks

Wireless Sensor Networks in volatile environments may suffer damage, and connectivity must be restored. The repairing agent must discover surviving nodes and damage to the physical and radio environment as it moves around the sensor field to execute the repair. We compare two approaches, one which re-generates a full plan whenever it discovers new knowledge, and a second which attempts to minimise the required number of new radio nodes. We apply each approach with two different heuristics, one which attempts to minimise the cost of new radio nodes, and one which aims to minimise the travel distance. We conduct extensive simulation-based experiments, varying key parameters, including the level of damage suffered, and comparing directly with the published state-of-the-art. We quantify the relative performance of the different algorithms in achieving their objectives, and also measure the execution times to assess the impact on being able to make autonomous decisions in reasonable time

Crossing Symmetry Violation of Unitarized Pion-Pion Amplitude in the Resonance Region

Pion-pion scattering amplitude obtained from one-loop Chiral Perturbation Theory (ChPT) is crossing symmetric, however the corresponding partial wave amplitudes do not respect exact unitarity relation. There are different approaches to get unitarized partial wave amplitudes from ChPT. Here we consider the inverse amplitude method (IAM) that is often used to fit pion-pion phase shifts to experimental data, by adjusting free parameters. We measure the amount of crossing symmetry violation (CSV) in this case and we show that crossing symmetry is badly violated by the IAM unitarized ChPT amplitude in the resonance region. Important CSV also occurs when all free parameters are set equal to zero.Comment: 6 pages, 4 figure

Restoring wireless sensor network connectivity in damaged environments

A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. We propose four heuristic algorithms which integrate network design with path planning, recognising the impact of obstacles on mobility and communication. We conduct an empirical evaluation of the four algorithms on random connectivity and mobility maps, showing their relative performance in terms of node and path costs, and assessing their execution speeds. Finally, we examine how the relative importance of the two objectives influences the choice of algorithm

Integration of node deployment and path planning in restoring network connectivity

A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. We propose two heuristic algorithms which integrate network design with path planning, recognising the impact of obstacles on mobility and communication. We conduct an empirical evaluation of the two algorithms on random connectivity and mobility graphs, showing their relative performance in terms of node and path costs, and assessing their execution speeds. Finally, we examine how the relative importance of the two objectives influences the choice of algorithm

Repairing Wireless Sensor Network connectivity with mobility and hop-count constraints

Wireless Sensor Networks can become partitioned due to node failure or damage, and must be repaired by deploying new sensors, relays or sink nodes to restore some quality of service. We formulate the task as a multi-objective problem over two graphs. The solution specifies additional nodes to reconnect a connectivity graph subject to network path-length constraints, and a path through a mobility graph to visit those locations. The objectives are to minimise both the cost of the additional nodes and the length of the mobility path. We propose two heuristic algorithms which prioritise the different objectives. We evaluate the two algorithms on randomly generated graphs, and compare their solutions to the optimal solutions for the individual objectives. Finally, we assess the total restoration time for different classes of agent, i.e. small robots and larger vehicles, which allows us to trade-off longer computation times for shorter mobility paths