mFish Alpha Pilot: Building a Roadmap for Effective Mobile Technology to Sustain Fisheries and Improve Fisher Livelihoods.

In June 2014 at the Our Ocean Conference in Washington, DC, United States Secretary of State John Kerry announced the ambitious goal of ending overfishing by 2020. To support that goal, the Secretary's Office of Global Partnerships launched mFish, a public-private partnership to harness the power of mobile technology to improve fisher livelihoods and increase the sustainability of fisheries around the world. The US Department of State provided a grant to 50in10 to create a pilot of mFish that would allow for the identification of behaviors and incentives that might drive more fishers to adopt novel technology. In May 2015 50in10 and Future of Fish designed a pilot to evaluate how to improve adoption of a new mobile technology platform aimed at improving fisheries data capture and fisher livelihoods. Full report

The archive solution for distributed workflow management agents of the CMS experiment at LHC

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregate $\mathcal{O}$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.Comment: This is a pre-print of an article published in Computing and Software for Big Science. The final authenticated version is available online at: https://doi.org/10.1007/s41781-018-0005-

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

Integrating Peer-to-Peer Networking and Computing in the AgentScape Framework

The combination of peer-to-peer networking and agentbased computing seems to be a perfect match. Agents are cooperative and communication oriented, while peerto -peer networks typically support distributed systems in which all nodes have equal roles and responsibilities. AgentScape is a framework designed to support large-scale multi-agent systems. Pole extends this framework with peerto -peer computing. This combination facilitates the development and deployment of new agent-based peer-to-peer applications and services