Load and Cost Aware Min-Min Workflow Scheduling Algorithm for Heterogeneous Resources in Fog, Cloud and Edge Scenarios

Fog computing and Edge computing are few of the latest technologies which are offered as solution to challenges faced in Cloud Computing. Instead of offloading of all the tasks to centralized cloud servers, some of the tasks can be scheduled at intermediate Fog servers or Edge devices. Though this solves most of the problems faced in cloud but also encounter other traditional problems due to resource-related constraints like load balancing, scheduling, etc. In order to address task scheduling and load balancing in Cloud-fog-edge collaboration among servers, we have proposed an improved version of min-min algorithm for workflow scheduling which considers cost, makespan, energy and load balancing in heterogeneous environment. This algorithm is implemented and tested in different offloading scenarios- Cloud only, Fog only, Cloud-fog and Cloud-Fog-Edge collaboration. This approach performed better and the result gives minimum makespan, less energy consumption along with load balancing and marginally less cost when compared to min-min and ELBMM algorithms

Organizing workflows of academic libraries with online digital educational resources

Accommodating lists of links to recommended online educational resources on the academic library websites is discussed. The author concludes that that is not quite efficient as it could be, as qualitatively heterogeneous resources often unadapted for learning purposes are included; their titles are complex, unintelligible, and elusive; or oriented toward different groups of users. The authors suggest to develop: methods to annotate and critically evaluate resource contents, to select resources efficiently so they meet user information needs; classification scheme to differentiate online educational resources by stage and field of study, and prospectively – by larger professional groups. It might be also helpful to design end-to-end navigator of resources suggestible for academic libraries and learning in every code of professional training field.

Declarative Application Management in the Fog

Orchestrating next-gen applications over heterogeneous resources along the Cloud-IoT continuum calls for new strategies and tools to enable scalable and application-specific managements. Inspired by the self-organisation capabilities of bacteria colonies, we propose a declarative, fully decentralised application management solution, targeting pervasive opportunistic Cloud-IoT infrastructures. We present a customisable declarative implementation of the approach and validate its scalability through simulation over motivating scenarios, also considering end-user’s mobility and the possibility to enforce application-specific management policies for different (classes of) applications.

How Venture Capital Firms Choose Syndication Partners: The Moderating Effects of Institutional Uncertainty and Investment Preference

ABSTRACT This study investigates how venture capital firms (VCs) choose syndication partners. Exponential random graph models of Chinese VC syndication networks from 2006 to 2013 show that the homophily mechanism does not always determine VCs’ partner selection. In selecting partners, VCs have to strike a balance between reducing uncertainty and mobilizing heterogeneous resources. Therefore, decisions about partners depend on institutional uncertainty and VCs’ investment preferences. While VCs that focus on traditional business in an immature market are more likely to form homogeneous syndications, their peers that prefer to invest in innovative companies and that can rely on a stable market tend to syndicate with heterogeneous partners.

Hybrid load balance based on genetic algorithm in cloud environment

Load balancing is an efficient mechanism to distribute loads over cloud resources in a way that maximizes resource utilization and minimizes response time. Metaheuristic techniques are powerful techniques for solving the load balancing problems. However, these techniques suffer from efficiency degradation in large scale problems. This paper proposes three main contributions to solve this load balancing problem. First, it proposes a heterogeneous initialized load balancing (HILB) algorithm to perform a good task scheduling process that improves the makespan in the case of homogeneous or heterogeneous resources and provides a direction to reach optimal load deviation. Second, it proposes a hybrid load balance based on genetic algorithm (HLBGA) as a combination of HILB and genetic algorithm (GA). Third, a newly formulated fitness function that minimizes the load deviation is used for GA. The simulation of the proposed algorithm is implemented in the cases of homogeneous and heterogeneous resources in cloud resources. The simulation results show that the proposed hybrid algorithm outperforms other competitor algorithms in terms of makespan, resource utilization, and load deviation.

Public-good driven release of heterogeneous resources leads to genotypic diversification of an isogenic yeast population in melibiose.

Adaptive diversification of an isogenic population, and its molecular basis has been a subject of a number of studies in the last few years. Microbial populations offer a relatively convenient model system to study this question. In this context, an isogenic population of bacteria (E. coli, B. subtilis, and Pseudomonas) has been shown to lead to genetic diversification in the population, when propagated for a number of generations. This diversification is known to occur when the individuals in the population have access to two or more resources/environments, which are separated either temporally or spatially. Here, we report adaptive diversification in an isogenic population of yeast, S. cerevisiae, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good, enzyme α-galactosidase, leading to hydrolysis of melibiose into two distinct resources, glucose and galactose. The diversification is driven by a mutations at a single locus, in the GAL3 gene in the GAL/MEL regulon in the yeast.