Policies for the reconfiguration of cognitive wireless infrastructures to 3G Radio Access Technologies

The ceaseless evolution of wireless communications is reflected nowadays on the introduction of Beyond-3G (B3G) systems, characterized by the coexistence and cooperation of various Radio Access Technologies (RATs), over a common infrastructure. Major facilitator of this convergence is the advent of cognitive networks, which deploy elements (base stations and mobile terminals) that are able to proactively adapt to environmental stimuli, so that to optimize their performance. Part of the adaptation action takes place in cognitive base stations that own several reconfigurable transceivers, which are controlled by appropriate management functionality and may dynamically change their operating parameters. Each reconfiguration set includes a specific RAT, carrier frequency, as well as demand volume to be allocated per transceiver. Accordingly, proper evaluation of the various candidate reconfiguration sets appears to be of high significance. To this effect, in this paper we consider a cognitive network segment with transceivers operating at 3G RAT/carrier and we solve the DAMC problem (Demand Allocation into Multiple Carriers problem), which aims at evaluating and selecting the optimum policy to allocate the demand into the available 3G carrier frequencies. Optimality is expressed in terms of minimizing the total transmitted/received power per base station, thus deciding for the reconfigurations with the least impact on network interference. Indicative simulation scenarios and results are also presented for the validation and verification of the proposed functionality.

A Management Framework for Ambient Systems Operating in Wireless B3G Environments

As the wireless world is rapidly evolving towards the “Beyond the 3rd Generation” (B3G) era, communication infrastructures need to tackle external conditions that are continuously changing, and thus become less predictable in terms of quality of service (QoS) provision. On the contrary, the B3G era, through the coexistence and complementary use of a multitude of Radio Access Technologies (RATs), offers additional capabilities for providing users with advanced levels of convenience and flexibility for living and working. Those advances in communications and networking technology are making it possible to devise ‘ambient’ systems, i.e. systems that realize the vision of an all-encompassing multimedia networking environment, which is aware of the users’ presence and context, and is sensitive, adaptive, and responsive to their needs, habits, gestures and emotions. All above pose significant challenges regarding the intelligent management of heterogeneous wireless infrastructures. In the light of the above, this paper presents such an advanced management framework, as an enabling technology for designing and developing ambient, wireless systems in B3G environments. The paper focuses on the main components of the proposed framework, as well as on their functionality and interactions. Additionally, indicative simulation results showcase the efficiency of the proposed framework.     

Optimal mining rates revisited: Managing mining equipment and geological risk at a given mine setup

This paper presents a mixed integer programming formulation dealing with the effective minimisation of risk incurred when optimizing mining production rates in such a way that production targets are met in the presence of geological uncertainty. This is developed through the concept of a “stable solution domain” that provides all feasible combinations of ore and waste extraction for the ultimate pit limit of a given deposit, independent of the geological risk. The proposed formulation provides an optimal annual extraction rate, together with the optimal utilization of a mining fleet and an equipment acquisition program. This solution eliminates unnecessary capital expenses and is feasible under all geological scenarios. The mathematical programming model is detailed and tested at a gold deposit. The results are used as input to a production schedule design and are compared to the schedule generated using a constant mining rate; the comparison shows that about 40% of equipment acquisition can be delayed for 7 years and mill demand still be met, thus maximizing profit and minimizing costs.     

A matheuristic approach for optimizing mineral value chains under uncertainty

Optimization and Engineering - Mineral value chains, also known as mining complexes, involve mining, processing, stockpiling, waste management and transportation activities. Their optimization is...     

Concepts of Wildland Fire Protection of Cultural Monuments and National Parks in Greece. Case Study: Digital Telemetry Networks at the Forest of Ancient Olympia

The concepts and particularities of fire protection planning for monuments of cultural heritage that are surrounded by national parks and other public wildlands are outlined, in the context of the general wildland fire problem of Greece. Typical examples of cultural monuments that were threatened by wildland fires in Greece are reported. A conceptual flowchart that combines optimal fire protection objectives with the protected values and functions of the national parks and cultural monuments is analyzed. A case-study presents the development of an electronic forest fire protection support system in the forest around the Ancient Olympia site in Greece, as an example of the potential deployment of innovative technologies in wildland fire protection. The aim of the system is twofold. First, the system supports remote monitoring of an extensive hydraulic network of pipelines, pumps and water-storage tanks build in the vicinity of the site. Second, the system provides means for remote operation of numerous revolving water-jets installed on top of heavy-duty tree-high metal towers, spread at key-locations inside the surrounding forest. All system telemetry data and command signals are transmitted through a single underground wire link requiring no external electric power at sensor/actuator locations inside the forest. Special user interfaces allow immediate system deployment either from a central graphics-based console screen or from purpose-build remote consoles installed at selected locations in the forest, thus achieving a high degree of readiness.     

Adaptive Resource Management Platform for Reconfigurable Networks

Users’ expectations towards technology, in terms of quality, service availability and accessibility are ever increasing. Aligned with this, the wireless world is rapidly moving towards the next generation of systems, featuring cooperating and reconfiguring capabilities for coexisting (and upcoming) Radio Access Technologies (RATs), so that to improve connectivity and reduce costs. In this respect, conventional planning and management techniques ought to be replaced by advanced schemes that consider multidimensional characteristics, increased complexity and high speeds. To this effect, means are needed capable to support scalability and to cater for advanced service features, provided to users at high rates and cost-effectively. This article provides a scheme to optimize resource management in future systems, by describing a platform that accommodates engineering mechanisms that deal with dynamic, demand driven planning and managing of spectrum and radio resources in reconfigurable networks. To do so, it first discusses the fundamentals and the approach followed in the proposed architecture and then investigates the basic functional modules. The architecture is validated through a set of use-cases that exemplify the operational applicability and efficiency in a wide range of communication scenarios.

Incorporating geological and equipment performance uncertainty while optimising short-term mine production schedules

ABSTRACT

Short-term production scheduling in open pit mining consists of defining the extraction sequence and process allocation of mineralised material over time-scales of either months, weeks, or days. An effective short-term production schedule ensures compliance with the production targets and restrictions imposed by the long-term plan. The method proposed herein outlines a new approach to simultaneously optimise the short-term production sequence with the mobile equipment allocation plan while incorporating both material grade and equipment performance uncertainty. A new simulation methodology is introduced to generate more realistic equipment performance scenarios, as well as a new concept of including ramp positions in the formulation to efficiently facilitate minable extraction patterns. This short-term model is bench-marked against a conventional design at one of the largest copper mines in the world, and the results show improved production target compliance by delivering more consistent ore quantity and quality to each processing destination, and a physical extraction sequence that has a greater likelihood of being realised in the face of equipment performance and truck cycle time uncertainty.     

Production scheduling with uncertain supply: a new solution to the open pit mining problem

The annual production scheduling of open pit mines determines an optimal sequence for annually extracting the mineralized material from the ground. The objective of the optimization process is usually to maximize the total Net Present Value (NPV) of the operation. Production scheduling is typically a Mixed Integer Programming (MIP) type problem containing uncertainty in the geologic input data and economic parameters involved. Major uncertainty affecting optimization is uncertainty in the mineralized materials (resource) available in the ground which constitutes an uncertain supply for mine production scheduling. A new optimization model is developed herein based on two-stage Stochastic Integer Programming (SIP) to integrate uncertain supply to optimization; past optimization methods assume certainty in the supply from the mineral resource. As input, the SIP model utilizes a set of multiple, stochastically simulated scenarios of the mineralized materials in the ground. This set of multiple, equally probable scenarios describes the uncertainty in the mineral resource available in the ground, and allows the proposed model to generate a single optimum production schedule. The method is applied for optimizing the annual production scheduling at a gold mine in Australia and benchmarked against a traditional scheduling method using the traditional single “average type” assessment of the mineral resource in the ground. In the case study presented herein, the schedule generated using the proposed SIP model resulted in approximately 10% higher NPV than the schedule derived from the traditional approach.