Mobile agents require an appropriate platform that can facilitate their migration and execution. In particular, the design and implementation of such a system must balance several factors that will ensure that its constituent agents are executed without problems. Besides the basic requirements of migration and execution, an agent system must also provide mechanisms to ensure the security and survivability of an agent when it migrates between hosts. In addition, the system should be simple enough to facilitate its widespread use across large scale networks (i.e Internet). To address these issues, this thesis discusses the design and implementation of the Distributed Agent Delivery System (DADS). The DADS provides a de-coupled design that separates agent acceptance from agent execution. Using functional modules, the DADS provides services ranging from language execution and security to fault-tolerance and compression. Modules allow the administrator(s) of hosts to declare, at run-time, the services that they want to provide. Since each administrative domain is different, the DADS provides a platform that can be adapted to exchange heterogeneous blends of agents across large scale networks.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / One of the problems in analyzing data is getting the data to the analysis system. The data can be stored in a variety of ways, from simple disk and tape files to a sophisticated relational database system. The variety of storage techniques requires the data analysis system to be aware of the details of how the data may be accessed (e.g., file formats, SQL statements, BBN/Probe commands, etc.). The problem is much worse in a network of heterogeneous machines; besides the details of each storage method, the analysis system must handle the details of network access, and may have to translate data from one vendor format to another as it moves from machine to machine. This paper describes a simple and powerful software interface to telemetry data in a distributed heterogeneous networking environment, and how that interface is being used in a diagnostic expert system. In this case, the interface connects the expert system, running on a Sun UNIX machine, with the data on a VAX/VMS machine. The interface exists as a small subroutine library that can be linked into a variety of data analysis systems. The interface insulates the expert system from all details of data access, providing transparent access to data across the network. A further benefit of this approach is that the data source itself can be a sophisticated data analysis system that may perform some processing of the data, again transparently to the user of the interface. The interface subroutine library can be readily applied to a wide variety of data analysis applications.

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This project examines the implications of the photovoltaic power generation as well as the battery storage systems on the distribution network tariff structures. Different types of existing distribution tariffs were applied to the residential households’ demand patterns. Several scenarios of demand profiles were theoretically investigated. First scenario included households’ consumption under current situation without on-site power production and any storage, second scenario concerned penetration of average size of solar panel installations and the last demand profile with maximum possible size of photovoltaic panels complemented with battery storage use. The distribution tariffs included in the comparison are: power based tariff and two energy based tariffs, one with flat-rate and another with time-of-use structure. Distribution tariffs were normalized with the aim to research the implications of the on-site production and storage use. Normalization factors were used when comparing financial bills from the households under above mentioned scenarios. Energy distribution tariffs have higher potential for households to save on their energy bill with the introduction of the on-site solar power utilization. On the other hand power tariff provides higher incentive for the implementation of the demand response strategies in the households.

M.Com. (Economics) / In this study the use of distributed lags in the estimation of econometric equations is discussed with special reference to Shirley Almon's model of polinomically distributed lags. In chapter 2 of this study possible reasons for the existence of distributed lags as well as a number of distributed lag models are discussed. In chapter 3 the estimation of Almon lag models with and without the existence of end restrictions is discussed with special mention of the practical problems associated with such estimations. In chapter 4 the estimation of multi-variable Almon lags and the benefit of computer programs in the estimation thereof are discussed. In chapter 5 a procedure is given for the estimation of Almon lag models with examples of the estimation of two fuctions: Investment: Private: Non-Agriculture (IPNL) and Exports Excluding Gold (XSG).

In this thesis I explore how older people make use of, and interact with, their physical environment in home and near-by settings to manage cognitive situations, specifically prospective memory situations. Older adults have in past research been shown to perform better on prospective memory in real-life settings than what findings in laboratory-like settings predict. An explanation for this paradox is that older adults has a more developed skill of using the environment for prospective memory than younger adults. However, research investigating this explanation has primarily been based on self-reports. I contribute to the understanding of this skill by doing two related things. First I introduce distributed cognition, a theoretical perspective that primarily has been used within professional and socio-technical environments, to the research field of prospective memory in everyday life. Second I present a cognitive ethnography conducted during two years across eight home, and near-by, environments and old-age retired persons, for which I have used theoretical concepts from distributed cognition to analyze observations. The analysis shows rich variations in how participants use common cultural cognitive tools, invent their own cognitive tools, deliberately and incidentally shape more or less functional spaces, make use of other physical features, orient themselves toward and make sense of cognitive resources. I complement both prospective memory and distributed cognition research by describing both the intelligent shaping and use of space. Furthermore, by taking a distributed cognitive perspective I show that prospective memory processes in home environments involve properties, and the management, of a multipurpose environment. Altogether this supports the understanding of distributed cognition as a perspective on all cognition. Distributed cognition is not a reflection of particular work practices, instead it is a formulation of the general features of human cognition. Prospective memory in everyday life can be understood as an ability persons have. However, in this thesis I show that prospective memory can also be understood as a process that takes place between persons, arrangements of space, and tools.

Context. Big Data and Cloud Computing nowadays require large amounts of storage that are accessible by many servers. To overcome the performance bottlenecks and single point of failure distributed storage systems came into force. So, our main aim in this thesis is evaluating the performance of these storage systems. A file coding technique is used that is the erasure coding which will help in data protection for the storage systems. Objectives. In this study, we investigate the performance evaluation of distributed storage system and understand the effect on performance for various patterns of I/O operations that is the read and write and also different measurement approaches for storage performance. Methods. The method is to use synthetic workload generator by streaming and transcoding video data as well as benchmark tool which generates the workload like SPECsfs2014 is used to evaluate the performance of distributed storage systems of GlusterFS and Compuverde which are file based storage. Results. In terms of throughput results, Gluster and Compuverde perform similar for both NFS and SMB server. The average latency results for both NFS and SMB shares indicate that Compuverde has lower latency. When comparing results of both Compuverde and Gluster, Compuverde delivers 100% IOPS with NFS server and Gluster delivers relatively near to the requested OP rate and with SMB server Gluster delivers 100% IOPS and Compuverde delivers more than the requested OP rate.

Context : Big Data and Cloud Computing nowadays require large amounts of storage that are accessible by many servers. The Energy consumed by these servers as well as that consumed by hosts providing the storage has been growing rapidly over the recent years. There are various approaches to save energy both at the hardware and software level, respectively. In the context of software, this challenge requires identification of new development methodologies that can help reduce the energy footprint of the Distributed Storage System. Until recently, reducing the energy footprint of Distributed Storage Systems is a challenge because there is no new methodology implemented to reduce the energy footprint of the Distributed Storage Systems. To tackle this challenge, we evaluate the energy consumption of Distributed Storage Systems by using a Power Application Programming Interface (PowerAPI) that monitors, in real-time, the energy consumed at the granularity of a system process. Objectives : In this study we investigate the Energy Consumption of distributed storage system. We also attempt to understand the effect on energy consumption for various patters of video streams. Also we have observed different measurement approaches for energy performance. Methods : The method is to use a power measuring software library while a synthetic load generator generates the load i.e., video data streams. The Tool which generates the workload is Standard Performance Evaluation Corporation Solution File Server (SPECsfs 2014) and PowerAPI is the software power monitoring library to evaluate the energy consumption of distributed storage systems of GlusterFS and Compuverde. Results : The mean and median values of power samples in mill watts for Compuverde higher than Gluster. For Compuverde the mean and median values until the load increment of three streams was around a 400 milliwatt value. The values of mean and median for the Gluster system were gradually increasing. Conclusions : The results show Compuverde having a higher consumption of energy than Gluster as it has a higher number of running processes that implement additional features that do not exist in Gluster. Also we have concluded that the conpuverde performed better for higher values of Load i.e., video data streams. / <p>Topic : Evaluating Energy Consumption of Distributed Storage Systems</p><p>Advisor: Dr. Dragos Ilie, Senior Lecturer, BTH</p><p>External Advisor: Stefan Bernbo,CEO, Compuverde AB</p><p>Student: Samuel Sushanth Kolli</p><p>The report gives a clear description of Distributed Storage Sytems and their Energy consumption with Performance Evaluation.</p><p>The report also includes the complete description and working of SpecSFS 2014 and PowerAPI Tool.</p> / Performance Evaluation of Distributed Storage Systems

Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for self-partitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the Lego® Mindstorms’ NXT on a graphical programming platform using National Instruments’ LabVIEW™ forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.

R has recently gained explicit text mining support with the "tm" package enabling statisticians to answer many interesting research questions via statistical analysis or modeling of (text) corpora. However, we typically face two challenges when analyzing large corpora: (1) the amount of data to be processed in a single machine is usually limited by the available main memory (i.e., RAM), and (2) an increase of the amount of data to be analyzed leads to increasing computational workload. Fortunately, adequate parallel programming models like MapReduce and the corresponding open source implementation called Hadoop allow for processing data sets beyond what would fit into memory. In this paper we present the package "tm.plugin.dc" offering a seamless integration between "tm" and Hadoop. We show on the basis of an application in culturomics that we can efficiently handle data sets of significant size. / Series: Research Report Series / Department of Statistics and Mathematics