Effective medical surplus recovery

We analyze not-for-profit Medical Surplus Recovery Organizations (MSROs) that manage the recovery of surplus (unused or donated) medical products to fulfill the needs of underserved healthcare facilities in the developing world. Our work is inspired by an award-winning North American non-governmental organization (NGO) that matches the uncertain supply of medical surplus with the receiving parties’ needs. In particular, this NGO adopts a recipient-driven resource allocation model, which grants recipients access to an inventory database, and each recipient selects products of limited availability to fill a container based on its preferences. We first develop a game theoretic model to investigate the effectiveness of this approach. This analysis suggests that the recipient-driven model may induce competition among recipients and lead to a loss in value provision through premature orders. Further, contrary to the common wisdom from traditional supply chains, full inventory visibility in our setting may accelerate premature orders and lead to loss of effectiveness. Accordingly, we identify operational mechanisms to help MSROs deal with this problem. These are: (i) appropriately selecting container capacities while limiting the inventory availability visible to recipients and increasing the acquisition volumes of supplies, (ii) eliminating recipient competition through exclusive single-recipient access to MSRO inventory, and (iii) focusing on learning recipient needs as opposed to providing them with supply information, and switching to a provider-driven resource allocation model. We use real data from the NGO by which the study was inspired and show that the proposed improvements can substantially increase the value provided to recipients

Disaster Recovery Services in Intercloud using Genetic Algorithm Load Balancer

Paradigm need to shifts from cloud computing to intercloud for disaster recoveries, which can outbreak anytime and anywhere. Natural disaster treatment includes radically high voluminous impatient job request demanding immediate attention. Under the disequilibrium circumstance, intercloud is more practical and functional option. There are need of protocols like quality of services, service level agreement and disaster recovery pacts to be discussed and clarified during the initial setup to fast track the distress scenario. Orchestration of resources in large scale distributed system having muli-objective optimization of resources, minimum energy consumption, maximum throughput, load balancing, minimum carbon footprint altogether is quite challenging. Intercloud where resources of different clouds are in align, plays crucial role in resource mapping. The objective of this paper is to improvise and fast track the mapping procedures in cloud platform and addressing impatient job requests in balanced and efficient manner. Genetic algorithm based resource allocation is proposed using pareto optimal mapping of resources to keep high utilization rate of processors, high througput and low carbon footprint.  Decision variables include utilization of processors, throughput, locality cost and real time deadline. Simulation results of load balancer using first in first out and genetic algorithm are compared under similar circumstances

IDEALIST control and service management solutions for dynamic and adaptive flexi-grid DWDM networks

Wavelength Switched Optical Networks (WSON) were designed with the premise that all channels in a network have the same spectrum needs, based on the ITU-T DWDM grid. However, this rigid grid-based approach is not adapted to the spectrum requirements of the signals that are best candidates for long-reach transmission and high-speed data rates of 400Gbps and beyond. An innovative approach is to evolve the fixed DWDM grid to a flexible grid, in which the optical spectrum is partitioned into fixed-sized spectrum slices. This allows facilitating the required amount of optical bandwidth and spectrum for an elastic optical connection to be dynamically and adaptively allocated by assigning the necessary number of slices of spectrum. The ICT IDEALIST project will provide the architectural design, protocol specification, implementation, evaluation and standardization of a control plane and a network and service management system. This architecture and tools are necessary to introduce dynamicity, elasticity and adaptation in flexi-grid DWDM networks. This paper provides an overview of the objectives, framework, functional requirements and use cases of the elastic control plane and the adaptive network and service management system targeted in the ICT IDEALIST project

The macro financing of natural hazards in developing countries

The authors propose a financial model to address the design of efficient risk financing strategies against natural disasters at the country level. It is simple enough to shed analytical light on some of the key issues but flexible and realistic enough to provide some quantitative guidance on the ex ante financing of catastrophic losses. The risk financing problem is decomposed into two steps. First, the resource gap, defined as the difference between losses and available ex-post resources (such as post-disaster aid), is identified. It determines the losses to be financed by ex ante financial instruments (reserves, catastrophe insurance, and contingent debt). Second, the cost-minimizing financial arrangements are derived from the marginal costs of the financial instruments. The model is solved through a series of graphical analyses that make this complex financial problem easier to apprehend. This model captures and explains the main impacts of financial parameters (such as insurance premium, cost of capital) on efficient risk financing structures.Insurance&Risk Mitigation,Banks&Banking Reform,Financial Intermediation,Natural Disasters,Non Bank Financial Institutions

Simplicial Homology for Future Cellular Networks

Simplicial homology is a tool that provides a mathematical way to compute the connectivity and the coverage of a cellular network without any node location information. In this article, we use simplicial homology in order to not only compute the topology of a cellular network, but also to discover the clusters of nodes still with no location information. We propose three algorithms for the management of future cellular networks. The first one is a frequency auto-planning algorithm for the self-configuration of future cellular networks. It aims at minimizing the number of planned frequencies while maximizing the usage of each one. Then, our energy conservation algorithm falls into the self-optimization feature of future cellular networks. It optimizes the energy consumption of the cellular network during off-peak hours while taking into account both coverage and user traffic. Finally, we present and discuss the performance of a disaster recovery algorithm using determinantal point processes to patch coverage holes