Generalized Spring Tensor Algorithms: with Workflow Scheduling Applications in Cloud Computing

In Cloud Computing, designing an efficient workflow scheduling algorithm is considered as a main goal. Load balancing is one of the most sophisticated methodologies, which can optimize workflow scheduling by distributing the load evenly among available resources. A well-designed load balancing algorithm has significant impact on performance and output in Cloud Computing. Therefore, designing robust load balancing techniques to manage the networks' load has always been a priority. Researchers have proposed and examined different load balancing methods; there is, however, a large knowledge gap in adopting an efficient load balancing algorithm in the Cloud system. This paper describes how a generalized spring tensor, an evolutionary algorithm with mathematical apparatus, can be utilized for a more efficient and effective load management in Cloud Computing. Considering the fluctuation and magnitude of the load, a novel application of workflow scheduling is investigated in the context of various mathematical patterns. The preliminary results of the research show that defining the dependency ratio between workflow tasks in Cloud Computing, results in better resource management, maximized performance and minimized response time while dealing with customer's requests

Load balancing optimization in cloud computing: Applying Endocrine-particale swarm optimization

© 2015 IEEE. Load balancing optimization is categorized as NP-hard problem, playing an important role in enhancing the cloud utilization. Different methods have been proposed for achieving the system load balancing in cloud environment. VM migration is one of these techniques, proposed to improve the VMs' functionality. Despite of the advantageous of VM migration, there are still some drawbacks which urged researchers to improve VM migration methods. In this paper we propose a new load balancing technique, using Endocrine algorithm which is inspired from regulation behavior of human's hormone system. Our proposed algorithm achieves system load balancing by applying self-organizing method between overloaded VMs. This technique is structured based on communications between VMs. It helps the overloaded VMs to transfer their extra tasks to another under-loaded VM by applying the enhanced feed backing approach using Particle Swarm Optimization (PSO). To evaluate our proposed algorithm, we expanded the cloud simulation tool (Cloudsim) which is developed by University of Melbourne. The simulation result proves that our proposed load balancing approach significantly decreases the timespan compared to traditional load balancing techniques. Moreover it increases the Quality Of Service (QOS) as it minimizes the VMs' downtime

Autonomous Model of Software Architecture for Smart Grids

Smart grids are being deployed at global level to ensure energy efficiency. As a result, scalable smart software platforms are required which can be used to incorporate and integrate information coming from various consumers using smart meters. Smart grids are supported by smart software architectures which are supported by cloud platforms. Cloud and Internet-of-Things (IoT) platforms provide scalable resources which can be used to design software infrastructures which allow always-on applications. The report paper explores smart grid and energy efficiency, how cloud and IoT platforms are used to enhance smart software architecture for smart grids, and privacy and security issues that result from the use of clouds. © Springer International Publishing Switzerland 2015

Software infrastructure for wireless sensor and actuator networks

In the development of large ad-hoc Wireless Sensor and Actuator Agent Networks (SANETS), a multitude of disparate problems are faced. In order for these networks to function, software must be able to effectively manage: unreliable dynamic distributed communication, the power constraints of un-wired devices, failure of hardware devices in hostile environments and the remote allocation of distributed processing tasks throughout the network. The solutions to these problems must be solved in a highly scalable manner. The paper describes the process of analysis of the requirements and presents a design of a service-oriented software infrastructure (middleware) solution for scalable ad-hoc networks, in a context of a system made of mobile sensors and actuators. © 2011 IEEE

Prevalence of Trichomonas vaginalis and Coinfection with Chlamydia trachomatis and Neisseria gonorrhoeae in the United States as Determined by the Aptima Trichomonas vaginalis Nucleic Acid Amplification Assay

Our aim was to determine Trichomonas vaginalis prevalence using the Aptima Trichomonas vaginalis assay (ATV; Gen-Probe) and the prevalence of Chlamydia trachomatis and Neisseria gonorrhoeae coinfections in U.S. women undergoing screening for C. trachomatis/N. gonorrhoeae. Discarded urogenital samples from 7,593 women (18 to 89 years old) undergoing C. trachomatis/N. gonorrhoeae screening using the Aptima Combo 2 assay (Gen-Probe) in various clinical settings were tested with ATV. Overall, T. vaginalis, C. trachomatis, and N. gonorrhoeae prevalences were 8.7%, 6.7%, and 1.7%, respectively. T. vaginalis was more prevalent than C. trachomatis or N. gonorrhoeae in all age groups except the 18- to 19-year-old group. The highest T. vaginalis prevalence was in women ≥40 years old (>11%), while the highest C. trachomatis prevalence (9.2%) and N. gonorrhoeae prevalence (2.2%) were in women C. trachomatis/T. vaginalis, 0.61% for C. trachomatis/N. gonorrhoeae and N. gonorrhoeae/T. vaginalis, and 0.24% for C. trachomatis/N. gonorrhoeae/T. vaginalis and highest in women T. vaginalis prevalence differed by race/ethnicity, with the highest prevalence in black women (20.2%). T. vaginalis prevalence ranged from 5.4% in family planning clinics to 22.3% in jails. Multivariate analysis determined that ages of ≥40 years, black race, and patient locations were significantly associated with T. vaginalis infection. T. vaginalis is the most common sexually transmitted infection (STI) in women of >40 years, while C. trachomatis and N. gonorrhoeae prevalence is lowest in that age group. Higher T. vaginalis prevalence in women of >40 years is probably attributed to the reason for testing, i.e., symptomatic status versus routine screening in younger women. Coinfections were relatively low. High T. vaginalis prevalence in all age groups suggests that women screened for C. trachomatis/N. gonorrhoeae, whether asymptomatic or symptomatic, should be screened for T. vaginalis

Cloud Computing for business: Enablers and Inhibitors

The main issues affecting cloud computing are the high costs associated with the transfer of data and the availability of cloud systems. Data transfer costs are rather high especially for those businesses that extensively use document management systems that are characterised by the production of large amounts of transactions and data records. Communication traffic associated with these large data transfers significantly adds to the operational cost as well. In this article we will focus on cloud computing from the perspective of business application and highlight the technology' s potential benefits and shortcomings both in short and long terms

C²EN: Anisotropic model of cloud computing

In Cloud computing, due to non-locale and a multitenancy of services and resources, there is a need for sophisticated methods for the metering of efficiency, availability and utilisation of services and resources. Setup and management of computing infrastructure, that is in a state of constant flux, related uncertainties of the state of individual elements as well as levels of their usage per application or user on an hourly, daily, weekly, monthly, and yearly basis - pose serious challenges. This paper describes how the Anisotropic Network concept, with its mathematical apparatus, can be adopted to model, monitor and manage usage of the cloud computing resources and services seen as an elastic network of interacting elements that are in a constant motion. Various aspects of service utilisation prediction and anisotropic resource movements related to the novel Cloud Computing Elastic Network (C2EN) model will be discussed in the context of a mathematical model and experimental results of simulations. © 2011 IEEE

The artificial immune system approach for smart air-conditioning control

Biologically inspired computing that looks to nature and biology for inspiration is a revolutionary change to our thinking about solving complex computational problems. It looks into nature and biology for inspiration rather than conventional approaches. The Human Immune System with its complex structure and the capability of performing pattern recognition, self-learning, immune-memory, generation of diversity, noise tolerance, variability, distributed detection and optimisation-is one area that has been of strong interest and inspiration for the last decade. An air conditioning system is one example where immune principles can be applied. This paper describes new computational technique called Artificial Immune System that is based on immune principles and refined for solving engineering problems. The presented system solution applies AIS algorithms to monitor environmental variables in order to determine how best to reach the desired temperature, learn usage patterns and predict usage needs. The aim of this paper is to explore the AIS-based artificial intelligence approach and its impact on energy efficiency. It will examine, if AIS algorithms can be integrated within a Smart Air Conditioning System as well as analyse the impact of such a solution

Development of software with cloud computing in 3TZ collaborative team environment

In the global economy, we have seen a decrease in the barriers towards communication across the globe along with an increase of service availability to support this communication. Software development is one discipline that is capable of effectively utilizing and benefiting from global collaboration prospect lent by ever increasing capability of information and communication technology. 24-hour continues development is ideal for application towards tasks that have hard-deadlines or require work completed as soon as possible. This article will mainly focus on introducing 24/7 global models that can be applied in cloud environment used in three different time zones. The case study related to developing agricultural software has been investigated in this article. © 2011 IEEE