13,731 research outputs found
Socially-Aware Distributed Hash Tables for Decentralized Online Social Networks
Many decentralized online social networks (DOSNs) have been proposed due to
an increase in awareness related to privacy and scalability issues in
centralized social networks. Such decentralized networks transfer processing
and storage functionalities from the service providers towards the end users.
DOSNs require individualistic implementation for services, (i.e., search,
information dissemination, storage, and publish/subscribe). However, many of
these services mostly perform social queries, where OSN users are interested in
accessing information of their friends. In our work, we design a socially-aware
distributed hash table (DHTs) for efficient implementation of DOSNs. In
particular, we propose a gossip-based algorithm to place users in a DHT, while
maximizing the social awareness among them. Through a set of experiments, we
show that our approach reduces the lookup latency by almost 30% and improves
the reliability of the communication by nearly 10% via trusted contacts.Comment: 10 pages, p2p 2015 conferenc
Crux: Locality-Preserving Distributed Services
Distributed systems achieve scalability by distributing load across many
machines, but wide-area deployments can introduce worst-case response latencies
proportional to the network's diameter. Crux is a general framework to build
locality-preserving distributed systems, by transforming an existing scalable
distributed algorithm A into a new locality-preserving algorithm ALP, which
guarantees for any two clients u and v interacting via ALP that their
interactions exhibit worst-case response latencies proportional to the network
latency between u and v. Crux builds on compact-routing theory, but generalizes
these techniques beyond routing applications. Crux provides weak and strong
consistency flavors, and shows latency improvements for localized interactions
in both cases, specifically up to several orders of magnitude for
weakly-consistent Crux (from roughly 900ms to 1ms). We deployed on PlanetLab
locality-preserving versions of a Memcached distributed cache, a Bamboo
distributed hash table, and a Redis publish/subscribe. Our results indicate
that Crux is effective and applicable to a variety of existing distributed
algorithms.Comment: 11 figure
Dynamic, Latency-Optimal vNF Placement at the Network Edge
Future networks are expected to support low-latency, context-aware and user-specific services in a highly flexible and efficient manner. One approach to support emerging use cases such as, e.g., virtual reality and in-network image processing is to introduce virtualized network functions (vNF)s at the edge of the network, placed in close proximity to the end users to reduce end-to-end latency, time-to-response, and unnecessary utilisation in the core network. While placement of vNFs has been studied before, it has so far mostly focused on reducing the utilisation of server resources (i.e., minimising the number of servers required in the network to run a specific set of vNFs), and not taking network conditions into consideration such as, e.g., end-to-end latency, the constantly changing network dynamics, or user mobility patterns. In this paper, we formulate the Edge vNF placement problem to allocate vNFs to a distributed edge infrastructure, minimising end-to-end latency from all users to their associated vNFs. We present a way to dynamically re-schedule the optimal placement of vNFs based on temporal network-wide latency fluctuations using optimal stopping theory. We then evaluate our dynamic scheduler over a simulated nation-wide backbone network using real-world ISP latency characteristics. We show that our proposed dynamic placement scheduler minimises vNF migrations compared to other schedulers (e.g., periodic and always-on scheduling of a new placement), and offers Quality of Service guarantees by not exceeding a maximum number of latency violations that can be tolerated by certain applications
Octopus: A Secure and Anonymous DHT Lookup
Distributed Hash Table (DHT) lookup is a core technique in structured
peer-to-peer (P2P) networks. Its decentralized nature introduces security and
privacy vulnerabilities for applications built on top of them; we thus set out
to design a lookup mechanism achieving both security and anonymity, heretofore
an open problem. We present Octopus, a novel DHT lookup which provides strong
guarantees for both security and anonymity. Octopus uses attacker
identification mechanisms to discover and remove malicious nodes, severely
limiting an adversary's ability to carry out active attacks, and splits lookup
queries over separate anonymous paths and introduces dummy queries to achieve
high levels of anonymity. We analyze the security of Octopus by developing an
event-based simulator to show that the attacker discovery mechanisms can
rapidly identify malicious nodes with low error rate. We calculate the
anonymity of Octopus using probabilistic modeling and show that Octopus can
achieve near-optimal anonymity. We evaluate Octopus's efficiency on Planetlab
with 207 nodes and show that Octopus has reasonable lookup latency and
manageable communication overhead
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