A Survey on Vertical and Horizontal Scaling Platforms for Big Data Analytics

There is no doubt that we are entering the era of big data. The challenge is on how to store, search, and analyze the huge amount of data that is being generated per second. One of the main obstacles to the big data researchers is how to find the appropriate big data analysis platform. The basic aim of this work is to present a complete investigation of all the available platforms for big data analysis in terms of vertical and horizontal scaling, and its compatible framework and applications in detail. Finally, this article will outline some research trends and other open issues in big data analytic

Scheduling for Large Scale Distributed Computing Systems: Approaches and Performance Evaluation Issues

Although our everyday life and society now depends heavily oncommunication infrastructures and computation infrastructures,scientists and engineers have always been among the main consumers ofcomputing power. This document provides a coherent overview of theresearch I have conducted in the last 15 years and which targets themanagement and performance evaluation of large scale distributedcomputing infrastructures such as clusters, grids, desktop grids,volunteer computing platforms, ... when used for scientific computing.In the first part of this document, I present how I have addressedscheduling problems arising on distributed platforms (like computinggrids) with a particular emphasis on heterogeneity and multi-userissues, hence in connection with game theory. Most of these problemsare relaxed from a classical combinatorial optimization formulationinto a continuous form, which allows to easily account for keyplatform characteristics such as heterogeneity or complex topologywhile providing efficient practical and distributed solutions.The second part presents my main contributions to the SimGrid project,which is a simulation toolkit for building simulators of distributedapplications (originally designed for scheduling algorithm evaluationpurposes). It comprises a unified presentation of how the questions ofvalidation and scalability have been addressed in SimGrid as well asthoughts on specific challenges related to methodological aspects andto the application of SimGrid to the HPC context

Resource aware load distribution strategies for scheduling divisible loads on large-scale data intensive computational grid systems

Ph.DDOCTOR OF PHILOSOPH

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Drone location and scheduling problems in humanitarian logistics.

Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, are a promising technology for the last-mile delivery of medical and aid items in humanitarian logistics. In emergency scenarios, like disasters, where transportation networks are destroyed and people are stranded, drones can accelerate the delivery of urgently needed items, e.g., food and water, insulin shots and blood pressure pills, to those trapped in the disaster-affected areas. Drones can also provide logistics services in many non-emergency situations by delivering medical items, e.g., vaccine shots and lab specimens, to remote communities and hard-to-access locations. The contribution of using UAVs goes beyond merely having access to remote and disaster-affected areas. With inexpensive launching infrastructures and no need for on-board pilots, drones can offer an inexpensive, agile, and ready-to-use alternative to traditional last-mile delivery modes. Motivated by the challenges associated with the last-mile delivery of aid items to hard-to-access areas, this dissertation studies the problem of drone-based delivery of aid items, e.g., medical and relief packages, to hard-to-access areas in humanitarian logistics. The main goal of this dissertation is to design the logistics and orchestrate a fleet of drones to provide the timely delivery of items to hard-to-access areas in emergency and non-emergency scenarios. In this dissertation, we develop multiple extensions of a drone location and scheduling problem while taking into account the critical aspects of drone- based delivery systems in humanitarian logistics. These critical aspects include: i) limited coverage range, ii) limited payload capacity, iii) energy consumption, iv) timeliness, and v) uncertainty. Chapter II presents a general case of the drone location and scheduling (DLS) problem for the delivery of aid items in disaster-affected areas. In this chapter, we first develop a time-slot formulation to address the problem of optimally locating drone take- off platforms and concurrently scheduling and sequencing a set of trips for each drone to minimize total disutility for product delivery. We extend a two-period problem of DLS where the platforms can be relocated using useable road networks after the first period in order to provide a higher level of coverage. Chapter III proposes a multi-stop drone location and scheduling (MDLS) problem for the delivery of medical items in rural and suburban areas. In this chapter, we assume drones are allowed to stop at one or multiple charging stations, installed on existing platforms having access to electricity, e.g., streetlights, during each trip in order to improve the drones’ coverage range while considering the drones’ energy consumption. The problem is to find optimum locations for medical item providers and charging stations as well as optimally scheduling and sequencing drone trips over a long-term horizon. Chapter IV presents a stochastic extension for the drone location and scheduling (SDLS) problem. Due to the lack of information and instability of the situation, we assume the set of demand locations is not known. The main problem is to locate a set of drone take-off platforms so that with a given probability, the maximum total disutility (or cost) under all realizations of the demand locations is minimized. Finally, Chapter V presents a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas in humanitarian logistics. Our goal is to develop a simulation-based system to perform analytical/numerical studies, evaluate the performance of a drone delivery system in humanitarian logistics, and support the decision-making process in such a context while considering multiple sources of variabilities

Cloud Security in 21st Century: Current Key Issues in Service Models on Cloud Computing and how to overcome them

Cloud computing is a disruptive innovation which offers new ways to increase capacity and capabilities of the organization’s IT infrastructure. In last few years cloud computing has taken computing industry by storm and many organizations are using cloud computing services to increase the efficiency, decrease their IT budgets and play an important role in defining the IT strategy of their business. Cloud computing offers various benefits such as scalability, elasticity, reducing IT expenditure considerably. Moreover, the architecture of such a utility computing consists of service models and deployment models which have been explained in the paper .Security is a key concern in all the web applications when they start interacting with applications in the public domain. The purpose of this paper is to provide the key security issues in service models of Cloud computing: Infrastructure-as-a-Service, Software-as-a-service and Platform-as-as-service. Finally, the paper will discuss some of the solutions been offered by cloud service providers for the following service models: Software as a service (SaaS), Platform as a service (PaaS) and Infrastructure as a Service (IaaS)

Cloud Security in 21st Century: Current Key Issues in Service Models on Cloud Computing and how to overcome them

Cloud computing is a disruptive innovation which offers new ways to increase capacity and capabilities of the organization’s IT infrastructure. In last few years cloud computing has taken computing industry by storm and many organizations are using cloud computing services to increase the efficiency, decrease their IT budgets and play an important role in defining the IT strategy of their business. Cloud computing offers various benefits such as scalability, elasticity, reducing IT expenditure considerably. Moreover, the architecture of such a utility computing consists of service models and deployment models which have been explained in the paper .Security is a key concern in all the web applications when they start interacting with applications in the public domain. The purpose of this paper is to provide the key security issues in service models of Cloud computing: Infrastructure-as-a-Service, Software-as-a-service and Platform-as-as-service. Finally, the paper will discuss some of the solutions been offered by cloud service providers for the following service models: Software as a service (SaaS), Platform as a service (PaaS) and Infrastructure as a Service (IaaS)

Proceedings of the 8th MIT/ONR Workshop on C[3] Systems, held at Massachusetts Institute of Technology, Cambridge, Massachusetts, June 24 to 28, 1985

"December 1985."Includes bibliographies and index.Office of Naval Research Contract no. ONR/N00014-77-C-0532 NR-041-519edited by Michael Athans and Alexander H. Levis

Operations Management

Global competition has caused fundamental changes in the competitive environment of the manufacturing and service industries. Firms should develop strategic objectives that, upon achievement, result in a competitive advantage in the market place. The forces of globalization on one hand and rapidly growing marketing opportunities overseas, especially in emerging economies on the other, have led to the expansion of operations on a global scale. The book aims to cover the main topics characterizing operations management including both strategic issues and practical applications. A global environmental business including both manufacturing and services is analyzed. The book contains original research and application chapters from different perspectives. It is enriched through the analyses of case studies