673 research outputs found
EARM: An Efficient and Adaptive File Replication with Consistency Maintenance in P2P Systems
In p2p systems, file replication and replica consistency maintenance are most widely used techniques for better system performance. Most of the file replication methods replicates file in all nodes or at two ends in a clientserver query path or close to the server, leading to low replica utilization, produces unnecessary replicas and hence extra consistency maintenance overhead. Most of the consistency maintenance methods depends on either message spreading or structure based for update message propagation without considering file replication dynamism, leading to inefficient file update and outdated file response. These paper presents an Efficient and Adaptive file Replication and consistency Maintenance (EARM) that combines file replication and consistency maintenance mechanism that achieves higher query efficiency in file replication and consistency maintenance at a low cost. Instead of accepting passively file replicas and updates, each node determines file replication and update polling by adapting to time-varying file query and update rates. Simulation results demonstrate the effectiveness of EARM in comparison with other approaches
A Literature Survey of Cooperative Caching in Content Distribution Networks
Content distribution networks (CDNs) which serve to deliver web objects
(e.g., documents, applications, music and video, etc.) have seen tremendous
growth since its emergence. To minimize the retrieving delay experienced by a
user with a request for a web object, caching strategies are often applied -
contents are replicated at edges of the network which is closer to the user
such that the network distance between the user and the object is reduced. In
this literature survey, evolution of caching is studied. A recent research
paper [15] in the field of large-scale caching for CDN was chosen to be the
anchor paper which serves as a guide to the topic. Research studies after and
relevant to the anchor paper are also analyzed to better evaluate the
statements and results of the anchor paper and more importantly, to obtain an
unbiased view of the large scale collaborate caching systems as a whole.Comment: 5 pages, 5 figure
DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling
The dynamic provisioning of virtualized resources offered by cloud computing
infrastructures allows applications deployed in a cloud environment to
automatically increase and decrease the amount of used resources. This
capability is called auto-scaling and its main purpose is to automatically
adjust the scale of the system that is running the application to satisfy the
varying workload with minimum resource utilization. The need for auto-scaling
is particularly important during workload peaks, in which applications may need
to scale up to extremely large-scale systems.
Both the research community and the main cloud providers have already
developed auto-scaling solutions. However, most research solutions are
centralized and not suitable for managing large-scale systems, moreover cloud
providers' solutions are bound to the limitations of a specific provider in
terms of resource prices, availability, reliability, and connectivity.
In this paper we propose DEPAS, a decentralized probabilistic auto-scaling
algorithm integrated into a P2P architecture that is cloud provider
independent, thus allowing the auto-scaling of services over multiple cloud
infrastructures at the same time. Our simulations, which are based on real
service traces, show that our approach is capable of: (i) keeping the overall
utilization of all the instantiated cloud resources in a target range, (ii)
maintaining service response times close to the ones obtained using optimal
centralized auto-scaling approaches.Comment: Submitted to Springer Computin
Enhanced Failure Detection Mechanism in MapReduce
The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until now has not reached its satisfying level. Motivated by this, I decided to devote my main research during this period into having a prototype system architecture of MapReduce framework with a new failure detection service, containing both analytical (theoretical) and implementation part. I am confident that this work should lead the way for further contributions in detecting failures to any NoSQL App frameworks, and cloud storage systems in general
File management in a mobile DHT-based P2P environment
The emergence of mobile P2P systems is largely due to the evolution of mobile devices into powerful information processing units. The relatively structured context that results from the mapping of mobile patterns of behaviour onto P2P models is however constrained by the vulnerabilities of P2P networks and the inherent limitations of mobile devices. Whilst the implementation of P2P models gives rise to security and reliability issues, the deployment of mobile devices is subject to efficiency constraints. This paper presents the development and deployment of a mobile P2P system based on distributed hash tables (DHT). The secure, reliable and efficient dispersal of files is taken as an application. Reliability was addressed by providing two methods for file dispersal: replication and erasure coding. Security constraints were catered for by incorporating an authentication mechanism and three encryption schemes. Lightweight versions of various algorithms were selected in order to attend to efficiency requirements
Smart PIN: performance and cost-oriented context-aware personal information network
The next generation of networks will involve interconnection of heterogeneous individual
networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore,
there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent contentâs
characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches
for data delivery across the heterogeneous network are also required.
In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed:
Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD).
MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and
QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches
Data Management in the APPA System
International audienceCombining Grid and P2P technologies can be exploited to provide high-level data sharing in large-scale distributed environments. However, this combination must deal with two hard problems: the scale of the network and the dynamic behavior of the nodes. In this paper, we present our solution in APPA (Atlas Peer-to-Peer Architecture), a data management system with high-level services for building large-scale distributed applications. We focus on data availability and data discovery which are two main requirements for implementing large-scale Grids. We have validated APPA's services through a combination of experimentation over Grid5000, which is a very large Grid experimental platform, and simulation using SimJava. The results show very good performance in terms of communication cost and response time
- âŠ