Data Sharing in P2P Systems

To appear in Springer's "Handbook of P2P Networking"In this chapter, we survey P2P data sharing systems. All along, we focus on the evolution from simple file-sharing systems, with limited functionalities, to Peer Data Management Systems (PDMS) that support advanced applications with more sophisticated data management techniques. Advanced P2P applications are dealing with semantically rich data (e.g. XML documents, relational tables), using a high-level SQL-like query language. We start our survey with an overview over the existing P2P network architectures, and the associated routing protocols. Then, we discuss data indexing techniques based on their distribution degree and the semantics they can capture from the underlying data. We also discuss schema management techniques which allow integrating heterogeneous data. We conclude by discussing the techniques proposed for processing complex queries (e.g. range and join queries). Complex query facilities are necessary for advanced applications which require a high level of search expressiveness. This last part shows the lack of querying techniques that allow for an approximate query answering

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Managing contextual information in semantically-driven temporal information systems

Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the user’s environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the user’s profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to users‘ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Supply chain management as the key to a firm’s strategy in the global marketplace

Purpose: This research aims to analyze the intersection of two literature streams: that of strategy and supply chain management (SCM). This review should create a better understanding of “strategic SCM” by focusing on relevant theories in the strategic management field and their intersection with SCM to develop a joint research agenda. Design/Methodology/Approach: We conducted a correspondence analysis on the content of 3,402 articles from the top SCM journals. This analysis provides a map of the intellectual structure of content in this field to date. The key trends and changes were identified in strategic SCM research from 1990-2014 as well as the intersection with the key schools of strategic management. Findings: The results suggest that SCM is key to a successful deployment of strategy for competing in the global marketplace. The main theoretical foundations for research in this field were identified and discussed. Gaps were detected and combinations of theoretical foundations of strategic management and SCM suggest four poles for future research: agents and focal firm; distributions and logistics strategic models; SCM competitive requirements; SCM relational governance. Research limitations/implications: Scholars in both the strategy and the SCM fields continue to search for competitive advantages. Much recent research indicates that strategic SCM can be a critical source for that advantage. One of the limitations of our research is that the analysis does not include every journal that published an article mentioning SCM. However, the 34 journals selected are reputed to be the most influential on SCM and focused primarily on SCM. Practical implications: The map of the intellectual structure of research to strategic SCM highlights the need to combine different theoretical approaches to the complex phenomenon of SCM. Practitioners should consider the supply chain as an informal organization and should devote time and resources to build a shared advantage across the supply chain. They should also consider the inherent benefits and risks that sharing Originality/value: The paper demonstrates that strategic SCM needs a balanced and rigorous combination of theoretical approaches to deliver more theory-driven evidences. Our research combines both a qualitative analysis and a quantitative methodology that summarizes gaps and then outlines future research from a large sample of articles. This methodology is an original contribution to this field and offers some assistance for enlarging the sample of future literature reviews

An Analysis of BitTorrent Cross-Swarm Peer Participation and Geolocational Distribution

Peer-to-Peer (P2P) file-sharing is becoming increasingly popular in recent years. In 2012, it was reported that P2P traffic consumed over 5,374 petabytes per month, which accounted for approximately 20.5% of consumer internet traffic. TV is the popular content type on The Pirate Bay (the world's largest BitTorrent indexing website). In this paper, an analysis of the swarms of the most popular pirated TV shows is conducted. The purpose of this data gathering exercise is to enumerate the peer distribution at different geolocational levels, to measure the temporal trend of the swarm and to discover the amount of cross-swarm peer participation. Snapshots containing peer related information involved in the unauthorised distribution of this content were collected at a high frequency resulting in a more accurate landscape of the total involvement. The volume of data collected throughout the monitoring of the network exceeded 2 terabytes. The presented analysis and the results presented can aid in network usage prediction, bandwidth provisioning and future network design.Comment: The First International Workshop on Hot Topics in Big Data and Networking (HotData I