Collocation Games and Their Application to Distributed Resource Management

We introduce Collocation Games as the basis of a general framework for modeling, analyzing, and facilitating the interactions between the various stakeholders in distributed systems in general, and in cloud computing environments in particular. Cloud computing enables fixed-capacity (processing, communication, and storage) resources to be offered by infrastructure providers as commodities for sale at a fixed cost in an open marketplace to independent, rational parties (players) interested in setting up their own applications over the Internet. Virtualization technologies enable the partitioning of such fixed-capacity resources so as to allow each player to dynamically acquire appropriate fractions of the resources for unencumbered use. In such a paradigm, the resource management problem reduces to that of partitioning the entire set of applications (players) into subsets, each of which is assigned to fixed-capacity cloud resources. If the infrastructure and the various applications are under a single administrative domain, this partitioning reduces to an optimization problem whose objective is to minimize the overall deployment cost. In a marketplace, in which the infrastructure provider is interested in maximizing its own profit, and in which each player is interested in minimizing its own cost, it should be evident that a global optimization is precisely the wrong framework. Rather, in this paper we use a game-theoretic framework in which the assignment of players to fixed-capacity resources is the outcome of a strategic "Collocation Game". Although we show that determining the existence of an equilibrium for collocation games in general is NP-hard, we present a number of simplified, practically-motivated variants of the collocation game for which we establish convergence to a Nash Equilibrium, and for which we derive convergence and price of anarchy bounds. In addition to these analytical results, we present an experimental evaluation of implementations of some of these variants for cloud infrastructures consisting of a collection of multidimensional resources of homogeneous or heterogeneous capacities. Experimental results using trace-driven simulations and synthetically generated datasets corroborate our analytical results and also illustrate how collocation games offer a feasible distributed resource management alternative for autonomic/self-organizing systems, in which the adoption of a global optimization approach (centralized or distributed) would be neither practical nor justifiable.NSF (CCF-0820138, CSR-0720604, EFRI-0735974, CNS-0524477, CNS-052016, CCR-0635102); Universidad Pontificia Bolivariana; COLCIENCIAS–Instituto Colombiano para el Desarrollo de la Ciencia y la Tecnología "Francisco José de Caldas

BIGhybrid - A Toolkit for Simulating MapReduce on Hybrid Infrastructures

Cloud computing has increasingly been used as a platform for running large business and data processing applications. Although clouds have become highly popular, when it comes to data processing, the cost of usage is not negligible. Conversely, Desktop Grids, have been used by a plethora of projects, taking advantage of the high number of resources provided for free by volunteers. Merging cloud computing and desktop grids into hybrid infrastructure can provide a feasible low-cost solution for big data analysis. Although frameworks like MapReduce have been conceived to exploit commodity hardware, their use on hybrid infrastructure poses some challenges due to large resource heterogeneity and high churn rate. This study introduces BIGhybrid a toolkit to simulate MapReduce on hybrid environments. The main goal is to provide a framework for developers and system designers to address the issues of hybrid MapReduce. In this paper, we describe the framework which simulates the assembly of two existing middleware: BitDew- MapReduce for Desktop Grids and Hadoop-BlobSeer for Cloud Computing. Experimental results included in this work demonstrate the feasibility of our approach

Parallel and Context Based Search in Cloud using Multi Agent System

Cloud Computing is one of the fast growing Technology. Cloud computing support large scale infrastructure used to increase high performance of computing. This technology support agents and with the help of integration of the agents that is Multi Agent System (MAS) which is capable of intelligent behavior. They run in an environment where they communicate with each other using message passing technique. Each agent has its own set of behavior and they run independent of each other. When a message arrives each agent shows their own behavior and hence an agent shows their coordination. The use of MAS in cloud computing help us for searching context with better performance. The JADE is a platform which supports agent. This paper discusses about Cloud computing models and architectures, information retrieving technique and the use of MAS that improve the performance of big data search from Distributed File System (DFS) which is difficult to achieve using single agent or thread. Keywords: Cloud Computing, Distributed File System, JADE, MA

A customizable multi-agent system for distributed data mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances

DECENTRALIZING THE INTERNET OF MEDICAL THINGS: THE INTERPLANETARY HEALTH LAYER

Medical mobile applications have the potential to revolutionize the healthcare industry by providing patients with easy access to their personal health information, enabling them to communicate with healthcare providers remotely and consequently improving patient outcomes by providing personalized health information. However, these applications are usually limited by privacy and security issues. A possible solution is to exploit decentralization distributing privacy concerns directly to users. Solutions enabling this vision are closely linked to Distributed Ledger Technologies that have the potential to revolutionize the healthcare industry by creating a secure and transparent system for managing patient data without a central authority. The decentralized nature of the technology allows for the creation of an international data layer that is accessible to authorized parties while preserving patient privacy. This thesis envisions the InterPlanetary Health Layer along with its implementation attempt called Halo Network and an Internet of Medical Things application called Balance as a use case. Throughout the thesis, we explore the benefits and limitations of using the technology, analyze potential use cases, and look out for future directions.Medical mobile applications have the potential to revolutionize the healthcare industry by providing patients with easy access to their personal health information, enabling them to communicate with healthcare providers remotely and consequently improving patient outcomes by providing personalized health information. However, these applications are usually limited by privacy and security issues. A possible solution is to exploit decentralization distributing privacy concerns directly to users. Solutions enabling this vision are closely linked to Distributed Ledger Technologies that have the potential to revolutionize the healthcare industry by creating a secure and transparent system for managing patient data without a central authority. The decentralized nature of the technology allows for the creation of an international data layer that is accessible to authorized parties while preserving patient privacy. This thesis envisions the InterPlanetary Health Layer along with its implementation attempt called Halo Network and an Internet of Medical Things application called Balance as a use case. Throughout the thesis, we explore the benefits and limitations of using the technology, analyze potential use cases, and look out for future directions