Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

Why adopt now? Multiple case studies and survey studies comparing small, medium and large firms

While a number of factors have been highlighted in the innovation adoption literature, little is known about whether different factors are related to innovation adoption in differently-sized firms. We used preliminary case studies of small, medium and large firms to ground our hypotheses, which were then tested using a survey of 94 firms. We found that external stakeholder pressure and non-financial readiness were related to innovation adoption in SMEs; but that for large firms, adoption was related to the opportunity to innovate. It may be that the difficulties of adopting innovations, including both the financial cost and the effort involved, are too great for SMEs to overcome unless there is either a compelling need (external pressure) or enough in-house capability (non-financial readiness). This suggests that SMEs are more likely to have innovation “pushed” onto them while large firms are more likely to “pull” innovations when they have the opportunity.

CDKN2A mutation in a non-FAMMM kindred with cancers at multiple sites results in a functionally abnormal protein

The CDKN2A gene encodes p16 (CDKN2A), a cell-cycle inhibitor protein which prevents inappropriate cell cycling and, hence, proliferation. Germ-line mutations in CDKN2A predispose to the familial atypical multiple-mole melanoma (FAMMM) syndrome but also have been seen in rare families in which only 1 or 2 individuals are affected by cutaneous malignant melanoma (CMM). We therefore sequenced exons 1alpha and 2 of CDKN2A using lymphocyte DNA isolated from index cases from 67 families with cancers at multiple sites, where the patterns of cancer did not resemble those attributable to known genes such as hMLH1, hMLH2, BRCA1, BRCA2, TP53 or other cancer susceptibility genes. We found one mutation, a mis-sense mutation resulting in a methionine to isoleucine change at codon 53 (M531) of exon 2. The individual tested had developed 2 CMMs but had no dysplastic nevi and lacked a family history of dysplastic nevi or CMM. Other family members had been diagnosed with oral cancer (2 persons), bladder cancer (1 person) and possibly gall-bladder cancer. While this mutation has been reported in Australian and North American melanoma kindreds, we did not observe it in 618 chromosomes from Scottish and Canadian controls. Functional studies revealed that the CDKN2A variant carrying the M531 change was unable to bind effectively to CDK4, showing that this mutation is of pathological significance. Our results have confirmed that CDKN2A mutations are not limited to FAMMM kindreds but also demonstrate that multi-site cancer families without melanoma are very unlikely to contain CDKN2A mutations.

Letter to the editor : likelihood of tetraplegia after CT clearance of the cervical spine in obtunded blunt trauma patients

...the probabilistic computer simulation study by Dunham and colleagues evaluating the impact of different cervical spine management (CSM) strategies on tetraplegia and brain injury outcomes.1 Based on literature findings, expert opinion and with use of advances programming techniques the authors conclude that early collar removal without cervical spine magnetic resonance imaging (MRI) is a preferable CSM strategy for comatose, blunt trauma patients with extremity movement and a negative cervical spine computed tomography(CT) scan. Although we do not have the required expertise to comment on the applied statistical approach, we would like to comment on one of the medical assumptions raised by the authors, namely the likelihood of tetraplegia in this specific population....

Beyond MOF constraints : multiple constraint set metamodelling for lifecycle management

The management of models over time in many domains requires different constraints to apply to some parts of the model as it evolves. Using EMF and its meta-language Ecore, the development of model management code and tools usually relies on the meta- model having some constraints, such as attribute and reference cardinalities and changeability, set in the least constrained way that any model user will require. Stronger versions of these constraints can then be enforced in code, or by attaching additional constraint expressions, and their evaluations engines, to the generated model code. We propose a mechanism that allows for variations to the constraining meta-attributes of metamodels, to allow enforcement of different constraints at different lifecycle stages of a model. We then discuss the implementation choices within EMF to support the validation of a state-specific metamodel on model graphs when changing states, as well as the enforcement of state-specific constraints when executing model change operations.