Multi-service management in a multi-provider environment

As the spread of digital networks makes access to data communications globally available, the interest of communication service providers is switching away from the provision of these bearer networks and towards the provision of the value added services that will operate over them. At the same time the liberalisation of telecommunication markets is precipitating a dramatic change in the profile of communication service providers. In this complex telecommunications markets the open management, not only of the networks, but of the services themselves will become increasingly important. The large number and diversity of roles of the market players makes the management of inter-organisational relationships fundamentally important to the management of services. The ITU's series of recommendations on the telecommunication management network (TMN) provides a basis for inter-domain management, however, this and other standards have so far concentrated on the management of individual network components and of networks operated by single organisations. This paper provides an initial example of how the management of multiple services in a complex multi-player market can be modelled using TMN techniques for implementation on existing management platforms. The paper begins by briefly outlining current work in this field before describing aspects of this multi-player multi-service management problem and how they can be modelled and implemented in a real system

From Multi-User Virtual Environment to 3D Virtual Learning Environment

While digital virtual worlds have been used in education for a number of years, advances in the capabilities and spread of technology have fed a recent boom in interest in massively multi‐user 3D virtual worlds for entertainment, and this in turn has led to a surge of interest in their educational applications. In this paper we briefly review the use of virtual worlds for education, from informal learning to formal instruction, and consider what is required to turn a virtual world from a Multi‐User Virtual Environment into a fully fledged 3D Virtual Learning Environment (VLE). In this we focus on the development of Sloodle – a system which integrates the popular 3D virtual world of Second Life with the open‐source VLE Moodle. Our intent is not simply to provide additional learning support features for Second Life, but to study more generally the ways in which integrated virtual environments can benefit teaching and learning, and this is the focus of our closing discussion

Multi-environment field testing to identify broad, stable resistance to sterility mosaic disease of pigeonpea

Sterility mosaic disease (SMD) caused by Pigeonpea sterility mosaic virus and vectored by the eriophyid mite is a serious disease of pigeonpea in almost all pigeonpea-growing areas. Managing the disease with chemicals such as acaricides is very difficult, non-eco-friendly and costly; hence, host plant resistance is the best strategy implemented to manage this disease. In this context, 28 pigeonpea genotypes identified as resistant from preliminary screening of 976 pigeonpea accessions were evaluated in field at eight different agro-ecological locations in India for the stability of their resistance against SMD during 2007/2008 and 2008/2009. Genotype plus genotype × environment (GGE) analysis partitioned main effects into genotype, environments and G × E interactions and showed significant effects (P < 0.001) for SMD percentage incidence. Environment variance had the greatest effect (76.68 %), indicating the maximum variation in the disease due to the environment. At Bangalore, Dholi and Rahuri locations, all genotypes were susceptible to SMD with mean disease incidence of 71.1, 50.4 and 32.6 % respectively. However, most of the genotypes were resistant at four locations, Akola, Badnapur, Patancheru, and Vamban, and moderately resistant at Coimbatore. The GGE biplot analysis explained about 67.26 % of total variation and identified four genotypes (ICPLs 20094, 20106, 20098, 20115) as the most stable and resistant to SMD. Three genotypes (ICPLs 20096, 20107, 20110) showed moderately stable performance against SMD. These genotypes should be included in pigeonpea breeding programs as additional sources of resistance to SMD

Efficient Multi-Robot Coverage of a Known Environment

This paper addresses the complete area coverage problem of a known environment by multiple-robots. Complete area coverage is the problem of moving an end-effector over all available space while avoiding existing obstacles. In such tasks, using multiple robots can increase the efficiency of the area coverage in terms of minimizing the operational time and increase the robustness in the face of robot attrition. Unfortunately, the problem of finding an optimal solution for such an area coverage problem with multiple robots is known to be NP-complete. In this paper we present two approximation heuristics for solving the multi-robot coverage problem. The first solution presented is a direct extension of an efficient single robot area coverage algorithm, based on an exact cellular decomposition. The second algorithm is a greedy approach that divides the area into equal regions and applies an efficient single-robot coverage algorithm to each region. We present experimental results for two algorithms. Results indicate that our approaches provide good coverage distribution between robots and minimize the workload per robot, meanwhile ensuring complete coverage of the area.Comment: In proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 201

Multi-user Internet environment for gear design optimization

A Web based multi-user system has been developed to remotely execute a large size software package via the Internet. The software implements genetic algorithm to optimize the design of spur and helical gears. To accomplish this, a combination of HTML, JavaServlets, JavaApplets, JavaScript and HTTP protocol has been employed

Resource dedication problem in a multi-project environment

Resource dedication problem (RDP) in a multi-project environment is defined as the optimal dedication of resource capacities to dierent projects within the overall limits of the resources with the objective of minimizing the sum of the weighted tardinesses of all projects. The projects involved are in general multi-mode resource constrained project scheduling problems (MRCPSP) with nish to start zero time lag and nonpreemtive activities. In general, approaches to multi-project scheduling consider the resources as a pool shared by all projects. When projects are distributed geographically or sharing resources between projects is too costly, then the resource sharing policy may not be appropriate and hence the resources are dedicated to individual projects throughout project durations. To the best of our knowledge, this point of view for resources is not considered in multi-project literature. In the following, we propose a solution methodology for RDP with a new local improvement heuristic by determining the resource dedications to individual projects and solving scheduling problems with the given resource limits

Resource dedication problem in a multi-project environment

There can be different approaches to the management of resources within the context of multi-project scheduling problems. In general, approaches to multiproject scheduling problems consider the resources as a pool shared by all projects. On the other hand, when projects are distributed geographically or sharing resources between projects is not preferred, then this resource sharing policy may not be feasible. In such cases, the resources must be dedicated to individual projects throughout the project durations. This multi-project problem environment is defined here as the resource dedication problem (RDP). RDP is defined as the optimal dedication of resource capacities to different projects within the overall limits of the resources and with the objective of minimizing a predetermined objective function. The projects involved are multi-mode resource constrained project scheduling problems with finish to start zero time lag and non-preemptive activities and limited renewable and nonrenewable resources. Here, the characterization of RDP, its mathematical formulation and two different solution methodologies are presented. The first solution approach is a genetic algorithm employing a new improvement move called combinatorial auction for RDP, which is based on preferences of projects for resources. Two different methods for calculating the projects’ preferences based on linear and Lagrangian relaxation are proposed. The second solution approach is a Lagrangian relaxation based heuristic employing subgradient optimization. Numerical studies demonstrate that the proposed approaches are powerful methods for solving this problem