Integrating mobile and cloud resources management using the cloud personal assistant

The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources.

Climate change, water resources, and the politics of adaptation in the Middle East and North Africa

Through an examination of global climate change models combined with hydrological data on deteriorating water quality in the Middle East and North Africa (MENA), we elucidate the ways in which the MENA countries are vulnerable to climate-induced impacts on water resources. Adaptive governance strategies, however, remain a low priority for political leaderships in the MENA region. To date, most MENA governments have concentrated the bulk of their resources on large-scale supply side projects such as desalination, dam construction, inter-basin water transfers, tapping fossil groundwater aquifers, and importing virtual water. Because managing water demand, improving the efficiency of water use, and promoting conservation will be key ingredients in responding to climate-induced impacts on the water sector, we analyze the political, economic, and institutional drivers that have shaped governance responses. While the scholarly literature emphasizes the importance of social capital to adaptive governance, we find that many political leaders and water experts in the MENA rarely engage societal actors in considering water risks. We conclude that the key capacities for adaptive governance to water scarcity in MENA are underdeveloped. © 2010 Springer Science+Business Media B.V.

An Integrated Approach to Quantifying Groundwater and Surface Water Contributions of Stream Flow

The management of water resources in Ireland prior to the Water Framework Directive (WFD) has focussed on surface water and groundwater as separate entities. A critical element to the successful implementation of the
WFD is to improve our understanding of the interaction between the two and flow mechanisms by which groundwaters discharge to surface waters. An improved understanding of the contribution of groundwater to surface water is required for the classification of groundwater body status and the determination of groundwater quality thresholds. The results of the study will also have a wider application to many areas of the WFD.
A subcommittee of the WFD Groundwater Working Group (GWWG) has been formed to develop a methodology to estimate the groundwater contribution to Irish Rivers. The group has selected a number of analytical techniques to quantify components of stream flow in an Irish context (Master Recession Curve, Unit Hydrograph, Flood Studies Report methodologies and
hydrogeological analytical modelling). The components of stream flow that can be identified include deep groundwater, intermediate and overland. These analyses have been tested on seven pilot catchments that have a variety of hydrogeological settings and have been used to inform and constrain a mathematical model. The mathematical model used was the NAM (NedbØr-AfstrØmnings-Model) rainfall-runoff model which is a module of DHIs MIKE 11 modelling suite. The results from these pilot catchments have been used to develop a decision model based on catchment descriptors from GIS datasets for the selection of NAM parameters. The datasets used include the mapping of aquifers, vulnerability and subsoils, soils, the Digital Terrain Model, CORINE and lakes. The national coverage of the GIS datasets has allowed the extrapolation of the mathematical model to regional catchments across Ireland.