Transparent and scalable client-side server selection using netlets

Replication of web content in the Internet has been found to improve service response time, performance and reliability offered by web services. When working with such distributed server systems, the location of servers with respect to client nodes is found to affect service response time perceived by clients in addition to server load conditions. This is due to the characteristics of the network path segments through which client requests get routed. Hence, a number of researchers have advocated making server selection decisions at the client-side of the network. In this paper, we present a transparent approach for client-side server selection in the Internet using Netlet services. Netlets are autonomous, nomadic mobile software components which persist and roam in the network independently, providing predefined network services. In this application, Netlet based services embedded with intelligence to support server selection are deployed by servers close to potential client communities to setup dynamic service decision points within the network. An anycast address is used to identify available distributed decision points in the network. Each service decision point transparently directs client requests to the best performing server based on its in-built intelligence supported by real-time measurements from probes sent by the Netlet to each server. It is shown that the resulting system provides a client-side server selection solution which is server-customisable, scalable and fault transparent

More is Less: Perfectly Secure Oblivious Algorithms in the Multi-Server Setting

The problem of Oblivious RAM (ORAM) has traditionally been studied in a single-server setting, but more recently the multi-server setting has also been considered. Yet it is still unclear whether the multi-server setting has any inherent advantages, e.g., whether the multi-server setting can be used to achieve stronger security goals or provably better efficiency than is possible in the single-server case. In this work, we construct a perfectly secure 3-server ORAM scheme that outperforms the best known single-server scheme by a logarithmic factor. In the process, we also show, for the first time, that there exist specific algorithms for which multiple servers can overcome known lower bounds in the single-server setting.Comment: 36 pages, Accepted in Asiacrypt 201

On a batch arrival queuing system equipped with a stand-by server during vacation periods or the repairs times of the main server

This Article is provided by the Brunel Open Access Publishing Fund - Copyright @ 2011 Hindawi PublishingWe study a queuing system which is equipped with a stand-by server in addition to the main server. The stand-by server provides service to customers only during the period of absence of the main server when either the main server is on a vacation or it is in the state of repairs due to a sudden failure from time to time. The service times, vacation times, and repair times are assumed to follow general arbitrary distributions while the stand-by service times follow exponential distribution. Supplementary variables technique has been used to obtain steady state results in explicit and closed form in terms of the probability generating functions for the number of customers in the queue, the average number of customers, and the average waiting time in the queue while the MathCad software has been used to illustrate the numerical results in this work

Time Synchronization Server

Report presents the results of IST\u27s installation and integration of Network Time Protocol (NTP) and a Global Positioning System (GPS) receiver into the Distributed Interactive Stimulation (DIS) TESTBED located in IST\u27s laboratories

Continuous client-side query evaluation over dynamic linked data

Existing solutions to query dynamic Linked Data sources extend the SPARQL language, and require continuous server processing for each query. Traditional SPARQL endpoints already accept highly expressive queries, so extending these endpoints for time-sensitive queries increases the server cost even further. To make continuous querying over dynamic Linked Data more affordable, we extend the low-cost Triple Pattern Fragments (TPF) interface with support for time-sensitive queries. In this paper, we introduce the TPF Query Streamer that allows clients to evaluate SPARQL queries with continuously updating results. Our experiments indicate that this extension significantly lowers the server complexity, at the expense of an increase in the execution time per query. We prove that by moving the complexity of continuously evaluating queries over dynamic Linked Data to the clients and thus increasing bandwidth usage, the cost at the server side is significantly reduced. Our results show that this solution makes real-time querying more scalable for a large amount of concurrent clients when compared to the alternatives