A comprehensive survey for scheduling techniques in cloud computing

Harnessing the massively parallel architectures soon to become available into efficient algorithmic cooperation is one of the most important intellectual challenges facing Computer Science today. To the theoretician, the task seems similar to thiat of understanding the issues involved in the performance of sequential algorithms (which motivated Knuth’s books, among other important works), only mfinitely more complex. In sequential computation, th.e design process involves (a) choosing an algorithm and (b) analyzing it (mostly, counting its steps). In the parallel context, however, we have at least four stages: (1) Choose the algorithm (say, a directed acyclic graph (dag) indicating the elementary computations and their interdependence, a model in which evaluation of sequential performance is trivial). (2) Choose a particular multiprocessor architecture. (3) Find a schedule whereby the algorithm is executed on the processors (so that all necessary data a:re available at the appropriate processor at the time of each computation). (4) Only now can we talk about the performance of the algorithm, measured as the makespan of the schedule (elapsed time for computing the last result). In our opinion, it is this multi-layered nature of the problem that lies at the heart of the difficulties encountered in the development of the necessary ideas, principles, and tools for the design of parallel algorithms. Is there a way to shortcut the process, thus improving our chances of finally gaining some insight into parallel algorithms? It would be very interesting if we could combine stages (3) and (4) into a single step whereby the performance of the algorithm cho-

Towards an Architecture-Independent Analysis of Parallel Algorithms (Extended Abstract)

In 1998, Ian Foster and Carl Kesselman, together with thirty distinguished experts in high-performance computing and networking, laid the foundations of a new computing model called GRID. Their vision was introduced in the book, The GRID: Blueprint for a New Computing Infrastructure (see review, SCPE Vol. 3, No. 3 ). The editors wrote: … A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities… allowing new classes of applications to emerge… as yet, we have only a preliminary understanding of what these new applications will look like. Over the next five years, Grid computing became the hottest R&D field. Academia and national labs built experimental infrastructures, new startups were established to develop Grid technologies, and the HPC giant vendors joined the party. Each one pushed in a different direction based on what and how he believed Grid computing should look. It was only a matter of time until people started to ask what the Grid is all about. A survey of ten Grid experts produced ten different answers. The question remains without a clear answer, leaving many people confused. Ian Foster picked up the gloves. In his article, What is the GRID? A three point checklist (GRIDtoday, July 22, 2002: Vol. 1, No. 6), he redefines the Grid model to reflect the trades and changes in the field during the past five years. According to Foster, a Grid is a system that: Coordinates resources that are not subject to centralized control. Uses standard, open, general-purpose protocols and interfaces. Delivers a nontrivial quality of service. But Foster's new definition could not encompass all of the Grid's approaches. Moreover, Foster explained by example what the Grid is not: A cluster management system such as Sun's Sun Grid Engine, Platform's Load Sharing Facility, or Viridian's Portable Batch System can, when installed on a parallel computer or local area network, deliver quality of service guarantees and thus constitutes a powerful Grid resource. However, such a system is not a Grid itself, due to its centralized control of the hosts that it manages Within a week the responses started to come in. The first one was from Wolfgang Gentzsch, Director of Grid computing at Sun Microsystems (GRIDtoday, August 5, 2002: Vol. 1, No. 8). Gentzsch wrote: I very much like Ian's two earlier definitions. Combined, they may provide a very generic Grid definition. The new checklist, however, reduces the potential of a wide and rich variety of Grids, with different architectures, operational models, and applications, and may miss the chance to becoming widely accepted as a standard definition of the Grid. Why do we need a definition for the Grid? Can the Grid be defined? Is a definition is necessary to the Grid's development? The Grid is an open vision and thus cannot be defined. An attempt to define the Grid can only reach the foreseen technology horizon, and this horizon is only one to two years ahead. Grid computing is a paradigm in shift. New architectures and standards are changing the shape and direction of the Grid's development. In the past year one such prominent architecture was Open Grid Services Architecture (OGSA). The OGSA is the first attempt to bridge the gap between two cyberspace worlds: the Internet and the Grid. The Internet and the Grid are two different computing models. There are people who believe that the Grid is the next generation of the Internet and the World Wide Web, saying that the Great Global Grid is still many years away. Others state that the Grid will complement, not replace, the Internet as we know it. In 1998, when the Grid blueprint was published, a new Internet language appeared called eXtensible Markup Language (XML). XML is a development tool for a new Internet computing model known as Web Services. At that time, nobody understood that there is a relationship between Web Services and the Grid. Three years past before Steve Tuecke from Argonne National Laboratory started to write a spec for Grid Services. Later, people from IBM joined the mission and together they created OGSA. The OGSA specification outlines interfaces to grid computing software that comply with Web Services standards. If adopted, Grid services such as job scheduling, authentication, failure-detection, staging of applications and data, and migration of applications and data, will all be accessed through standard Web Services architecture. OGSA is basically where Grid meets Web Services and maybe the first step towards full integration of the Internet and the Grid. The Internet appeared a decade ago. In the beginning, the Net offered primitive applications: a mailing system, ftp services, and a web of home pages. Nobody asked, What is the Internet? The years passed and new emerging Internet technologies were developed. Today we can talk on the phone over the Net, chat with friends, and video conference with colleagues on the other side of the world. New computing and business models were developed: e-commerce, e-learning, e-science, and e-you-name-it. And nobody asks what the Internet is. The Grid is a super-model, a bag of networking models associated with many types of architectures, software packages, applications, and standards. Today, when people talk about the Grid they mention Data Grids, Science Grids, and Campus Grids. And at the same time they mention Farm computing, Peer-to-peer computing, and Utility computing, among others. Ten years from now many of today's technologies will disappear and new ones will be developed. I don't know how Grid computing will look a decade from now, but I know that we will have g-commerce, g-learning, g-science, and g-chat. Nobody will ask what the Grid is. It will be obvious, just as the Internet is today. Ami Marowka The Computer Aided Design Laboratory School of Engineering and Computer Science Hebrew University of Jerusalem

What is the GRID

Resource scheduling for infrastructure as a service (IaaS) in cloud computing

Hybrid task scheduling strategy for cloud computing by modified particle swarm optimization and fuzzy theory

A systematic study of double auction mechanisms in cloud computing

Cloud computing is a multifarious technological paradigm that is outgrowth of decades of research in parallel computing, virtualization, networking and communication, utility computing and Service-Oriented Architecture (SOA). It offers an on-demand and scalable access to a shared pool of resources hosted in a data centre at providers’ site. It reduces the overheads of up-front investments and financial risks for the end-user. The qualitative services and lower cost of services are the key requirements of this technology. Regardless of the fact that cloud computing offers great advantages to the end users, there are several challenging issues that are mandatory to be addressed. Owing to the financial nature of use of the cloud services based on Service Level Agreements (SLA) makes these issues even more serious that needs to be taken care of. This work presents an overview, style and actuality of cloud computing with the objective of presenting challenging issues concerned with various aspects of cloud computing.

Cloud Computing: Issues & Challenges

Amazon offers spot instances to cloud customers using an auction-like mechanism. These instances are dynamically priced and offered at a lower price with less guarantee of availability. Observing the popularity of Amazon spot instances among the cloud users, research has intensified on defining the users’ and providers’ behavior in the spot market. This work presents an exhaustive survey of spot pricing in cloud ecosystem. An insight into the Amazon spot instances and its pricing mechanism has been presented for better understanding of the spot ecosystem. Spot pricing and resource provisioning problem, modeled as a market mechanism, is discussed from both computational and economics perspective. A significant amount of important research papers related to price prediction and modeling, spot resource provisioning, bidding strategy designing etc. are summarized and categorized to evaluate the state of the art in the context. All theoretical frameworks, developed for cloud spot market, are illustrated and compared in terms of the techniques and their findings. Finally, research gaps are identified and various economic and computational challenges in cloud spot ecosystem are discussed as a guide to the future research.

A Survey on Spot Pricing in Cloud Computing

Cloud computing, a new paradigm for utility computing, has brought a revolutionary change in the IT industry by enabling the elastic on demand resource provisioning of computing resources. As cloud infrastructure heavily relies on virtualization technology, there is a need for an efficient and effective virtual machine scheduling strategy. Virtual machine scheduling problem can be defined as an allocation of a set of virtual machines (VMs) to a set of physical machines (PMs). The proposed work focuses on PSO based VM scheduling strategy for VM placement in cloud infrastructure. The strategy focuses on efficient VM allocation to physical servers in order to minimize the total resource wastage and the number of servers used. Simulation experiments were conducted to observe the allocation of VMs to the servers and to evaluate the proposed algorithm with respect to performance and scalability. The results are compared with Best-Fit, First-Fit and Worst-Fit placement strategies. Simulation study conducted to evaluate the performance reveals the effectiveness of the model.

Zahid Raza

Papers

A systematic study of double auction mechanisms in cloud computing

Cloud Computing: Issues & Challenges

A Survey on Spot Pricing in Cloud Computing

A PSO Based VM Resource Scheduling Model for Cloud Computing

A truthful combinatorial double auction-based marketplace mechanism for cloud computing