Ad-hoc Stream Adaptive Protocol

With the growing market of smart-phones, sophisticated applications that do extensive computation are common on mobile platform; and with consumers’ high expectation of technologies to stay connected on the go, academic researchers and industries have been making efforts to find ways to stream multimedia contents to mobile devices. However, the restricted wireless channel bandwidth, unstable nature of wireless channels, and unpredictable nature of mobility, has been the major road block for wireless streaming advance forward. In this paper, various recent studies on mobility and P2P system proposal are explained and analyzed, and propose a new design based on existing P2P systems, aimed to solve the wireless and mobility issues

Exploiting the power of multiplicity: a holistic survey of network-layer multipath

The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work

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

Active architecture for pervasive contextual services

International Workshop on Middleware for Pervasive and Ad-hoc Computing MPAC 2003), ACM/IFIP/USENIX International Middleware Conference (Middleware 2003), Rio de Janeiro, Brazil This work was supported by the FP5 Gloss project IST2000-26070, with partners at Trinity College Dublin and Université Joseph Fourier, and by EPSRC grants GR/M78403/GR/M76225, Supporting Internet Computation in Arbitrary Geographical Locations, and GR/R45154, Bulk Storage of XML Documents.Pervasive services may be defined as services that are available "to any client (anytime, anywhere)". Here we focus on the software and network infrastructure required to support pervasive contextual services operating over a wide area. One of the key requirements is a matching service capable of as-similating and filtering information from various sources and determining matches relevant to those services. We consider some of the challenges in engineering a globally distributed matching service that is scalable, manageable, and able to evolve incrementally as usage patterns, data formats, services, network topologies and deployment technologies change. We outline an approach based on the use of a peer-to-peer architecture to distribute user events and data, and to support the deployment and evolution of the infrastructure itself.Peer reviewe

Active architecture for pervasive contextual services

Pervasive services may be defined as services that are available to any client (anytime, anywhere). Here we focus on the software and network infrastructure required to support pervasive contextual services operating over a wide area. One of the key requirements is a matching service capable of assimilating and filtering information from various sources and determining matches relevant to those services. We consider some of the challenges in engineering a globally distributed matching service that is scalable, manageable, and able to evolve incrementally as usage patterns, data formats, services, network topologies and deployment technologies change. We outline an approach based on the use of a peer-to-peer architecture to distribute user events and data, and to support the deployment and evolution of the infrastructure itself

4Sensing - decentralized processing for participatory sensing data

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática.Participatory sensing is a new application paradigm, stemming from both technical and social drives, which is currently gaining momentum as a research domain. It leverages the growing adoption of mobile phones equipped with sensors, such as camera, GPS and accelerometer, enabling users to collect and aggregate data, covering a wide area without incurring in the costs associated with a large-scale sensor network. Related research in participatory sensing usually proposes an architecture based on a centralized back-end. Centralized solutions raise a set of issues. On one side, there is the implications of having a centralized repository hosting privacy sensitive information. On the other side, this centralized model has financial costs that can discourage grassroots initiatives. This dissertation focuses on the data management aspects of a decentralized infrastructure for the support of participatory sensing applications, leveraging the body of work on participatory sensing and related areas, such as wireless and internet-wide sensor networks, peer-to-peer data management and stream processing. It proposes a framework covering a common set of data management requirements - from data acquisition, to processing, storage and querying - with the goal of lowering the barrier for the development and deployment of applications. Alternative architectural approaches - RTree, QTree and NTree - are proposed and evaluated experimentally in the context of a case-study application - SpeedSense - supporting the monitoring and prediction of traffic conditions, through the collection of speed and location samples in an urban setting, using GPS equipped mobile phones

Efficient Processing of Ranking Queries in Novel Applications

Ranking queries, which return only a subset of results matching a user query, have been studied extensively in the past decade due to their importance in a wide range of applications. In this thesis, we study ranking queries in novel environments and settings where they have not been considered so far. With the advancements in sensor technologies, these small devices are today present in all corners of human life. Millions of them are deployed in various places and are sending data on a continuous basis. These sensors which before mainly monitored environmental phenomena or production chains, have now found their way into our daily lives as well; health monitoring being a plausible example of how much we rely on continuous observation of measurements. As the Web technology evolves and facilitates data stream transmissions, sensors do not remain the sole producers of data in form of streams. The Web 2.0 has escalated the production of user-generated content which appear in form of annotated posts in a Weblog (blog), pictures and videos, or small textual snippets reflecting the current activity or status of users and can be regarded as natural items of a temporal stream. A major part of this thesis is devoted to developing novel methods which assist in keeping track of this ever increasing flow of information with continuous monitoring of ranking queries over them, particularly when traditional approaches fail to meet the newly raised requirements. We consider the ranking problem when the information flow is not synchronized among its sources. This is a recurring situation, since sensors are run by different organizations, measure moving entities, or are simply represented by users which are inherently not synchronizable. Our methods are in particular designed for handling unsynchronized streams, calculating an object's score based on both its currently observed contribution to the registered queries as well as the contribution it might have in future. While this uncertainty in score calculation causes linear growth in the space necessary for providing exact results, we are able to define criteria which allows for evicting unpromising objects as early as possible. We also leverage statistical properties that reflect the correlation between multiple streams to predict the future to provide better bounds for the best possible contribution of an object, consequently limiting the necessary storage dramatically. To achieve this, we make use of small statistical synopses that are periodically refreshed during runtime. Furthermore, we consider user generated queries in the context of Web 2.0 applications which aim at filtering data streams in forms of textual documents, based on personal interests. In this case, the dimensionality of the data, the large cardinality of the subscribed queries, as well as the desire for consuming recent information, raise new challenges. We develop new approaches which efficiently filter the information and provide real-time updates to the user subscribed queries. Our methods rely on a novel ordering of user queries in traditional inverted lists which allows the system to effectively prune those queries for which a new piece of information is of no interest. Finally, we investigate high quality search in user generated content in Web 2.0 applications in form of images or videos. These resources are inherently dispersed all over the globe, therefore can be best managed in a purely distributed peer-to-peer network which eliminates single points of failure. Search in such a huge repository of high dimensional data involves evaluating ranking queries in form of nearest neighbor queries. Therefore, we study ranking queries in high dimensional spaces, where the index of the objects is maintained in a purely distributed fashion. Our solution meets the two major requirements of a viable solution in distributing the index and evaluating ranking queries: the underlying peer-to-peer network remains load balanced, and efficient query evaluation is feasible as similar objects are assigned to nearby peers

Using Blockchain to support Data & Service Monetization

Two required features of a data monetization platform are query and retrieval of the metadata of the resources to be monetized. Centralized platforms rely on the maturity of traditional NoSQL database systems to support these features. These databases, for example, MongoDB allows for very efficient query and retrieval of data it stores. However, centralized platforms come with a bag of security and privacy concerns, making them not the ideal approach for a data monetization platform. On the other hand, most existing decentralized platforms are only partially decentralized. In this research, I developed Cowry, a platform for publishing metadata describing available resources (data or services), discovery of published metadata including fast search and filtering. My main contribution is a fully decentralized architecture that combines blockchain and traditional distributed database to gain additional features such as efficient query and retrieval of metadata stored on the blockchain