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

Networking - A Statistical Physics Perspective

Efficient networking has a substantial economic and societal impact in a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption require new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with non-linear large scale systems. This paper aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. These include diffusion processes, methods from disordered systems and polymer physics, probabilistic inference, which have direct relevance to network routing, file and frequency distribution, the exploration of network structures and vulnerability, and various other practical networking applications.Comment: (Review article) 71 pages, 14 figure

Adaptive Square-Shaped Trajectory-Based Service Location Protocol in Wireless Sensor Networks

In this paper we propose an adaptive square-shaped trajectory (ASST)-based service location method to ensure load scalability in wireless sensor networks. This first establishes a square-shaped trajectory over the nodes that surround a target point computed by the hash function and any user can access it, using the hash. Both the width and the size of the trajectory are dynamically adjustable, depending on the number of queries made to the service information on the trajectory. The number of sensor nodes on the trajectory varies in proportion to the changing trajectory shape, allowing high loads to be distributed around the hot spot area

Analyse the Performance of Mobile Peer to Peer Network using Ant Colony Optimization

A mobile peer-to-peer computer network is the one in which each computer in the network can act as a client or server for the other computers in the network. The communication process among the nodes in the mobile peer to peer network requires more no of messages. Due to this large number of messages passing, propose an interconnection structure called distributed Spanning Tree (DST) and it improves the efficiency of the mobile peer to peer network. The proposed method improves the data availability and consistency across the entire network and also reduces the data latency and the required number of message passes for any specific application in the network. Further to enhance the effectiveness of the proposed system, the DST network is optimized with the Ant Colony Optimization method. It gives the optimal solution of the DST method and increased availability, enhanced consistency and scalability of the network. The simulation results shows that reduces the number of message sent for any specific application and average delay and increases the packet delivery ratio in the network

STARR-DCS: Spatio-temporal adaptation of random replication for data-centric storage

This article presents a novel framework for data-centric storage (DCS) in a wireless sensor and actor network (WSAN) that employs a randomly selected set of data replication nodes, which also change over time. This enables reductions in the average network traffic and energy consumption by adapting the number of replicas to applications' traffic, while balancing energy burdens by varying their locations. To that end, we propose and validate a simple model to determine the optimal number of replicas, in terms of minimizing average traffic/energy consumption, based on measurements of applications' production and consumption traffic. Simple mechanisms are proposed to decide when the current set of replication nodes should be changed, to enable new applications and nodes to efficiently bootstrap into a working WSAN, to recover from failing nodes, and to adapt to changing conditions. Extensive simulations demonstrate that our approach can extend a WSAN's lifetime by at least 60%, and up to a factor of 10× depending on the lifetime criterion being considered. The feasibility of the proposed framework has been validated in a prototype with 20 resource-constrained motes, and the results obtained via simulation for large WSANs have been also corroborated in that prototype.The research leading to these results has been partially funded by the Spanish MEC under the CRAMNET project (TEC2012-38362-C03-01) and the FIERRO project (TEC 2010- 12250-E), and by the General Directorate of Universities and Research of the Regional Government of Madrid under the MEDIANET Project (S2009/TIC-1468). G. de Veciana was supported by the National Science Foundation under Award CNS-0915928Publicad

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte