3,071 research outputs found
Analyzing Peer Selection Policies for BitTorrent Multimedia On-Demand Streaming Systems in Internet
The adaptation of the BitTorrent protocol to multimedia on-demand streaming
systems essentially lies on the modification of its two core algorithms, namely
the piece and the peer selection policies, respectively. Much more attention
has though been given to the piece selection policy. Within this context, this
article proposes three novel peer selection policies for the design of
BitTorrent-like protocols targeted at that type of systems: Select Balanced
Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select
Optimistic Neighbour Policy (SONP). These proposals are validated through a
competitive analysis based on simulations which encompass a variety of
multimedia scenarios, defined in function of important characterization
parameters such as content type, content size, and client interactivity
profile. Service time, number of clients served and efficiency retrieving
coefficient are the performance metrics assessed in the analysis. The final
results mainly show that the novel proposals constitute scalable solutions that
may be considered for real project designs. Lastly, future work is included in
the conclusion of this paper.Comment: 19 PAGE
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
Exploring heterogeneity of unreliable machines for p2p backup
P2P architecture is a viable option for enterprise backup. In contrast to
dedicated backup servers, nowadays a standard solution, making backups directly
on organization's workstations should be cheaper (as existing hardware is
used), more efficient (as there is no single bottleneck server) and more
reliable (as the machines are geographically dispersed).
We present the architecture of a p2p backup system that uses pairwise
replication contracts between a data owner and a replicator. In contrast to
standard p2p storage systems using directly a DHT, the contracts allow our
system to optimize replicas' placement depending on a specific optimization
strategy, and so to take advantage of the heterogeneity of the machines and the
network. Such optimization is particularly appealing in the context of backup:
replicas can be geographically dispersed, the load sent over the network can be
minimized, or the optimization goal can be to minimize the backup/restore time.
However, managing the contracts, keeping them consistent and adjusting them in
response to dynamically changing environment is challenging.
We built a scientific prototype and ran the experiments on 150 workstations
in the university's computer laboratories and, separately, on 50 PlanetLab
nodes. We found out that the main factor affecting the quality of the system is
the availability of the machines. Yet, our main conclusion is that it is
possible to build an efficient and reliable backup system on highly unreliable
machines (our computers had just 13% average availability)
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
DCCast: Efficient Point to Multipoint Transfers Across Datacenters
Using multiple datacenters allows for higher availability, load balancing and
reduced latency to customers of cloud services. To distribute multiple copies
of data, cloud providers depend on inter-datacenter WANs that ought to be used
efficiently considering their limited capacity and the ever-increasing data
demands. In this paper, we focus on applications that transfer objects from one
datacenter to several datacenters over dedicated inter-datacenter networks. We
present DCCast, a centralized Point to Multi-Point (P2MP) algorithm that uses
forwarding trees to efficiently deliver an object from a source datacenter to
required destination datacenters. With low computational overhead, DCCast
selects forwarding trees that minimize bandwidth usage and balance load across
all links. With simulation experiments on Google's GScale network, we show that
DCCast can reduce total bandwidth usage and tail Transfer Completion Times
(TCT) by up to compared to delivering the same objects via independent
point-to-point (P2P) transfers.Comment: 9th USENIX Workshop on Hot Topics in Cloud Computing,
https://www.usenix.org/conference/hotcloud17/program/presentation/noormohammadpou
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