Global research priorities for sea turtles : informing management and conservation in the 21st century

Over the past 3 decades, the status of sea turtles and the need for their protection to aid population recovery have increasingly captured the interest of government agencies, non-governmental organisations (NGOs) and the general public worldwide. This interest has been matched by increased research attention, focusing on a wide variety of topics relating to sea turtle biology and ecology, together with the interrelations of sea turtles with the physical and natural environments. Although sea turtles have been better studied than most other marine fauna, management actions and their evaluation are often hindered by the lack of data on turtle biology, human–turtle interactions, turtle population status and threats. In an effort to inform effective sea turtle conservation a list of priority research questions was assembled based on the opinions of 35 sea turtle researchers from 13 nations working in fields related to turtle biology and/or conservation. The combined experience of the contributing researchers spanned the globe as well as many relevant disciplines involved in conservation research. An initial list of more than 200 questions gathered from respondents was condensed into 20 metaquestions and classified under 5 categories: reproductive biology, biogeography, population ecology, threats and conservation strategies.

Sustainability analysis and resource management for wireless mesh networks with renewable energy supplies

 There is a growing interest in the use of renewable energy sources to power wireless networks in order to mitigate the detrimental effects of conventional energy production or to enable deployment in off-grid locations. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity. The dynamics of energy supply hence impose new challenges for network planning and resource management. In this paper, the sustainable performance of a wireless mesh network powered by renewable energy sources is studied. To address the intermittently available capacity of the energy supply, adaptive resource management and admission control schemes are proposed. Specifically, the goal is to maximize the energy sustainability of the network, or equivalently, to minimize the failure probability that the mesh access points (APs) deplete their energy and go out of service due to the unreliable energy supply. To this end, the energy buffer of a mesh AP is modeled as a G/G/1(/N) queue with arbitrary patterns of energy charging and discharging. Diffusion approximation is applied to analyze the transient evolution of the queue length and the energy depletion duration. Based on the analysis, an adaptive resource management scheme is proposed to balance traffic loads across the mesh network according to the energy adequacy at different mesh APs. A distributed admission control strategy to guarantee high resource utilization and to improve energy sustainability is presented. By considering the first and second order statistics of the energy charging and discharging processes at each mesh AP, it is demonstrated that the proposed schemes outperform some existing state-of-the-art solutions.

Agent-based reactive power management of power distribution networks with distributed energy generation

In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

Setting conservation priorities for migratory networks under uncertainty

Conserving migratory species requires protecting connected habitat along the pathways they travel. Despite recent improvements in tracking animal movements, migratory connectivity remains poorly resolved at a population level for the vast majority of species, hampering conservation prioritisation. In the face of these data limitations, we develop a novel approach to spatial prioritisation based on a model of potential connectivity, derived from empirical data on species abundance and distances travelled between sites while on migration. Applying this approach to migratory shorebirds using the East Asian-Australasian Flyway, we demonstrate that conservation strategies that prioritise sites based on connectivity and abundance together, outperform strategies that only prioritise sites based on the abundance of birds. The conservation value of a site is therefore dependent on both its capacity to support migratory animals and its position within the migratory pathway, with the loss of crucial sites leading to partial or total population collapse. We suggest that strategies prioritising conservation action at sites supporting large populations of migrants should, where possible, be augmented using data or models on the spatial arrangement of sites.

Control layer resource management in SDN-IoT networks using multi-objective constraint

Software Defined Networking (SDN) and Internet of Things (IoT) integration has thrown many critical challenges. Specifically, in heterogeneous SDN-IoT ecosystem, optimized resources utilization and effective management at the control layer is very difficult. This mainly affects the application specific Quality of Service (QoS) and energy consumption of the IoT network. Motivated from this, we propose a new Resource Management (RM) method at the control layer, in distributed SDN-IoT networks. This paper starts with reasons that why at control layer RM is more complex in the SDN-IoT ecosystem. After-that, we highlight motivated examples that necessitate to investigate new RM methods in SDN-IoT context. Further, we propose a novel method to compute controller performance. Theoretical analysis is conducted to prove that the proposed method is better than the existing methods.