ASETS: A SDN Empowered Task Scheduling System for HPCaaS on the Cloud

With increasing demands for High Performance Computing (HPC), new ideas and methods are emerged to utilize computing resources more efficiently. Cloud Computing appears to provide benefits such as resource pooling, broad network access and cost efficiency for the HPC applications. However, moving the HPC applications to the cloud can face several key challenges, primarily, the virtualization overhead, multi-tenancy and network latency. Software-Defined Networking (SDN) as an emerging technology appears to pave the road and provide dynamic manipulation of cloud networking such as topology, routing, and bandwidth allocation. This paper presents a new scheme called ASETS which targets dynamic configuration and monitoring of cloud networking using SDN to improve the performance of HPC applications and in particular task scheduling for HPC as a service on the cloud (HPCaaS). Further, SETSA, (SDN-Empowered Task Scheduler Algorithm) is proposed as a novel task scheduling algorithm for the offered ASETS architecture. SETSA monitors the network bandwidth to take advantage of its changes when submitting tasks to the virtual machines. Empirical analysis of the algorithm in different case scenarios show that SETSA has significant potentials to improve the performance of HPCaaS platforms by increasing the bandwidth efficiency and decreasing task turnaround time. In addition, SETSAW, (SETSA Window) is proposed as an improvement of the SETSA algorithm

Application of Saas to Interactive Media Marketing in Public Transportation

How to render the benefit of advertisement is a question difficult to be answered in the out-of-home advertising industry. With the advance of information technology this question can be answered efficiently and effectively. Moreover, with the innovation of gamification [5], a brand vendor can interact with its consumers directly. For media companies, they not only have to provide innovative applications to attract the attention of consumers but also to serve multiple advertisers simultaneously in the same time. In this paper, we introduce a “software as a service (SaaS)” architecture [1] of interactive marketing media to solve the problem of providing interaction between brand vendors and consumers simultaneously in the cloud computing environment. According to prior research [3], advertisers can benefit from their scalability and foci on core competencies with a cloud service. In the proposed system architecture, a series of interactive activities can be designed by an advertiser with high flexibility. The activities can be initialized with any traditional or digital signage when the attention of a consumer is caught. An instruction of online interaction with any smartphone can be provided in the signage. The consumer can follow the instructions to interact with the advertisers or to place orders online immediately. Since the whole system was designed as an interactive SoLoMo application, various multimedia content databases can be plugged in as data sources, including geographic, game, and video stream databases. The system was designed with three layers (presentation, domain, and data) distinctively according to Fowler [2]. We follow the seven guidelines suggested by Hevner et. al. [4] in the paradigm of design science research. These guidelines, including design as an artifact, problem relevant, design as a search process, research rigor, design evaluation, research contributions, and communication of research, provide us a rigorous process when developing a brand new information system or solving an existing problem with a new way [4]. We evaluated the proposed SaaS architecture with three scenarios and a benchmark comparison. The contribution of our work lies in that we provide a systematic framework of value co-creation among media owners, advertisers, and consumers. The advertising activity can be interesting, economic, and flexible on scale with the help of cloud computing

HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges

High Performance Computing (HPC) clouds are becoming an alternative to on-premise clusters for executing scientific applications and business analytics services. Most research efforts in HPC cloud aim to understand the cost-benefit of moving resource-intensive applications from on-premise environments to public cloud platforms. Industry trends show hybrid environments are the natural path to get the best of the on-premise and cloud resources---steady (and sensitive) workloads can run on on-premise resources and peak demand can leverage remote resources in a pay-as-you-go manner. Nevertheless, there are plenty of questions to be answered in HPC cloud, which range from how to extract the best performance of an unknown underlying platform to what services are essential to make its usage easier. Moreover, the discussion on the right pricing and contractual models to fit small and large users is relevant for the sustainability of HPC clouds. This paper brings a survey and taxonomy of efforts in HPC cloud and a vision on what we believe is ahead of us, including a set of research challenges that, once tackled, can help advance businesses and scientific discoveries. This becomes particularly relevant due to the fast increasing wave of new HPC applications coming from big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR

Representing variant calling format as directed acyclic graphs to enable the use of cloud computing for efficient and cost effective genome analysis

Ever since the completion of the Human Genome Project in 2003, the human genome has been represented as a linear sequence of 3.2 billion base pairs and is referred to as the "Reference Genome". Since then it has become easier to sequence genomes of individuals due to rapid advancements in technology, which in turn has created a need to represent the new information using a different representation. Several attempts have been made to represent the genome sequence as a graph albeit for different purposes. Here we take a look at the Variant Calling Format (VCF) file which carries information about variations within genomes and is the primary format of choice for genome analysis tools. This short paper aims to motivate work in representing the VCF file as Directed Acyclic Graphs (DAGs) to run on a cloud in order to exploit the high performance capabilities provided by cloud computing.N/

Analyzing the Effects of Load Distribution Algorithms on Energy Consumption of Servers in Cloud Data Centers

Cloud computing has become an important driver for IT service provisioning in recent years. It offers additional flexibility to both customers and IT service providers, but also comes along with new challenges for providers. One of the major challenges for providers is the reduction of energy consumption since today, already more than 50% of operational costs in data centers account for energy. A possible way to reduce these costs is to efficiently distribute load within the data center. Although the effect of load distribution algorithms on energy consumption is a topic of recent research, an analysis-framework for evaluating arbitrary load distribution algorithms with regard to their effects on the energy consumption of cloud data centers is still nonexistent. Therefore, in this contribution, a concept of a simulation-based, quantitative analysis-framework for load distribution algorithms in cloud environments with respect to the energy consumption of data centers is developed and evaluated