Towards critical event monitoring, detection and prediction for self-adaptive future Internet applications

The Future Internet (FI) will be composed of a multitude of diverse types of services that offer flexible, remote access to software features, content, computing resources, and middleware solutions through different cloud delivery models, such as IaaS, PaaS and SaaS. Ultimately, this means that loosely coupled Internet services will form a comprehensive base for developing value added applications in an agile way. Unlike traditional application development, which uses computing resources and software components under local administrative control, FI applications will thus strongly depend on third-party services. To maintain their quality of service, those applications therefore need to dynamically and autonomously adapt to an unprecedented level of changes that may occur during runtime. In this paper, we present our recent experiences on monitoring, detection, and prediction of critical events for both software services and multimedia applications. Based on these findings we introduce potential directions for future research on self-adaptive FI applications, bringing together those research directions

On the feasibility of collaborative green data center ecosystems

The increasing awareness of the impact of the IT sector on the environment, together with economic factors, have fueled many research efforts to reduce the energy expenditure of data centers. Recent work proposes to achieve additional energy savings by exploiting, in concert with customers, service workloads and to reduce data centers’ carbon footprints by adopting demand-response mechanisms between data centers and their energy providers. In this paper, we debate about the incentives that customers and data centers can have to adopt such measures and propose a new service type and pricing scheme that is economically attractive and technically realizable. Simulation results based on real measurements confirm that our scheme can achieve additional energy savings while preserving service performance and the interests of data centers and customers.Peer ReviewedPostprint (author's final draft

A Game-Theoretic Approach for Runtime Capacity Allocation in MapReduce

Nowadays many companies have available large amounts of raw, unstructured data. Among Big Data enabling technologies, a central place is held by the MapReduce framework and, in particular, by its open source implementation, Apache Hadoop. For cost effectiveness considerations, a common approach entails sharing server clusters among multiple users. The underlying infrastructure should provide every user with a fair share of computational resources, ensuring that Service Level Agreements (SLAs) are met and avoiding wastes. In this paper we consider two mathematical programming problems that model the optimal allocation of computational resources in a Hadoop 2.x cluster with the aim to develop new capacity allocation techniques that guarantee better performance in shared data centers. Our goal is to get a substantial reduction of power consumption while respecting the deadlines stated in the SLAs and avoiding penalties associated with job rejections. The core of this approach is a distributed algorithm for runtime capacity allocation, based on Game Theory models and techniques, that mimics the MapReduce dynamics by means of interacting players, namely the central Resource Manager and Class Managers

Predicting the need for aged care services at the small area level: the CAREMOD spatial microsimulation model

Most industrialised societies face rapid population ageing over the next two decades, including sharp increases in the number of people aged 85 years and over. As a result, the supply of and demand for aged care services has assumed increasing policy prominence. The likely spatial distribution of the need for aged care services is critical for planners and policy makers. This article describes the development of a regional microsimulation model of the need for aged care in New South Wales, a state of Australia. It details the methods involved in reweighting the 1998 Survey of Disability, Ageing and Carers, a national level dataset, against the 2001 Census to produce synthetic small area estimates at the statistical local area level. Validation shows that survey variables not constrained in the weighting process can provide unreliable local estimates. A proposed solution to this problem is outlined, involving record cloning, value imputation and alignment. Indicative disability estimates arising from this process are then discussed.Disability, ageing, spatial analysis, aged care, cloning; imputation; alignment; NATSEM

Goodbye to Projects? Working paper 1: Annotated bibliography on livelihood approaches and development interventions.

YesThis paper is one in a series of working papers prepared under a research project on Goodbye to Projects? The Institutional Impacts of a Livelihood Approach on Projects and Project Cycle Management. This is a collaborative project between the Bradford Centre for International Centre for Development (BCID) with the Economic and Policy Research Centre (EPRC), Uganda; Khanya ¿ managing rural change, South Africa; and, the Institute for Development Management (IDM), Tanzania. The project is supported by the UK Department for International Development (DFID) under their Economic and Social Research Programme (ESCOR).Department for International Developmen

Expressive Power-Based Resource Allocation for Data Centers

As data-center energy consumption continues to rise, efficient power management is becoming increasingly important. In this work, we examine the use of a novel market mechanism for finding the right balance between power and performance. The market enables a separation between a 'buyer side' that strives to maximize performance and a 'seller side' that strives to minimize power and other costs. A concise and scalable description language is defined for agent preferences that admits a mixedinteger program for computing optimal allocations. Experimental results demonstrate the robustness, flexibility, practicality and scalability of the architecture.Engineering and Applied Science