12,712 research outputs found
Link Prediction with Social Vector Clocks
State-of-the-art link prediction utilizes combinations of complex features
derived from network panel data. We here show that computationally less
expensive features can achieve the same performance in the common scenario in
which the data is available as a sequence of interactions. Our features are
based on social vector clocks, an adaptation of the vector-clock concept
introduced in distributed computing to social interaction networks. In fact,
our experiments suggest that by taking into account the order and spacing of
interactions, social vector clocks exploit different aspects of link formation
so that their combination with previous approaches yields the most accurate
predictor to date.Comment: 9 pages, 6 figure
PaRiS: Causally Consistent Transactions with Non-blocking Reads and Partial Replication
Geo-replicated data platforms are at the backbone of several large-scale
online services. Transactional Causal Consistency (TCC) is an attractive
consistency level for building such platforms. TCC avoids many anomalies of
eventual consistency, eschews the synchronization costs of strong consistency,
and supports interactive read-write transactions. Partial replication is
another attractive design choice for building geo-replicated platforms, as it
increases the storage capacity and reduces update propagation costs. This paper
presents PaRiS, the first TCC system that supports partial replication and
implements non-blocking parallel read operations, whose latency is paramount
for the performance of read-intensive applications. PaRiS relies on a novel
protocol to track dependencies, called Universal Stable Time (UST). By means of
a lightweight background gossip process, UST identifies a snapshot of the data
that has been installed by every DC in the system. Hence, transactions can
consistently read from such a snapshot on any server in any replication site
without having to block. Moreover, PaRiS requires only one timestamp to track
dependencies and define transactional snapshots, thereby achieving resource
efficiency and scalability. We evaluate PaRiS on a large-scale AWS deployment
composed of up to 10 replication sites. We show that PaRiS scales well with the
number of DCs and partitions, while being able to handle larger data-sets than
existing solutions that assume full replication. We also demonstrate a
performance gain of non-blocking reads vs. a blocking alternative (up to 1.47x
higher throughput with 5.91x lower latency for read-dominated workloads and up
to 1.46x higher throughput with 20.56x lower latency for write-heavy
workloads)
Overview of Polkadot and its Design Considerations
In this paper we describe the design components of the heterogenous
multi-chain protocol Polkadot and explain how these components help Polkadot
address some of the existing shortcomings of blockchain technologies. At
present, a vast number of blockchain projects have been introduced and employed
with various features that are not necessarily designed to work with each
other. This makes it difficult for users to utilise a large number of
applications on different blockchain projects. Moreover, with the increase in
number of projects the security that each one is providing individually becomes
weaker. Polkadot aims to provide a scalable and interoperable framework for
multiple chains with pooled security that is achieved by the collection of
components described in this paper
Trust models for mobile content-sharing applications
Using recent technologies such as Bluetooth, mobile users can share digital content (e.g., photos, videos)
with other users in proximity. However, to reduce the cognitive load on mobile users, it is important that
only appropriate content is stored and presented to them.
This dissertation examines the feasibility of having mobile users filter out irrelevant content by running
trust models. A trust model is a piece of software that keeps track of which devices are trusted (for
sending quality content) and which are not. Unfortunately, existing trust models are not fit for purpose.
Specifically, they lack the ability to: (1) reason about ratings other than binary ratings in a formal way;
(2) rely on the trustworthiness of stored third-party recommendations; (3) aggregate recommendations
to make accurate predictions of whom to trust; and (4) reason across categories without resorting to
ontologies that are shared by all users in the system.
We overcome these shortcomings by designing and evaluating algorithms and protocols with which
portable devices are able automatically to maintain information about the reputability of sources of
content and to learn from each otherâs recommendations. More specifically, our contributions are:
1. An algorithm that formally reasons on generic (not necessarily binary) ratings using Bayesâ theorem.
2. A set of security protocols with which devices store ratings in (local) tamper-evident tables and
are able to check the integrity of those tables through a gossiping protocol.
3. An algorithm that arranges recommendations in a âWeb of Trustâ and that makes predictions of
trustworthiness that are more accurate than existing approaches by using graph-based learning.
4. An algorithm that learns the similarity between any two categories by extracting similarities between
the two categoriesâ ratings rather than by requiring a universal ontology. It does so automatically
by using Singular Value Decomposition.
We combine these algorithms and protocols and, using real-world mobility and social network data,
we evaluate the effectiveness of our proposal in allowing mobile users to select reputable sources of
content. We further examine the feasibility of implementing our proposal on current mobile phones by
examining the storage and computational overhead it entails. We conclude that our proposal is both
feasible to implement and performs better across a range of parameters than a number of current alternatives
Amorphous Placement and Informed Diffusion for Timely Monitoring by Autonomous, Resource-Constrained, Mobile Sensors
Personal communication devices are increasingly equipped with sensors for passive monitoring of encounters and surroundings. We envision the emergence of services that enable a community of mobile users carrying such resource-limited devices to query such information at remote locations in the ïŹeld in which they collectively roam. One approach to implement such a service is directed placement and retrieval (DPR), whereby readings/queries about a specific location are routed to a node responsible for that location. In a mobile, potentially sparse setting, where end-to-end paths are unavailable, DPR is not an attractive solution as it would require the use of delay-tolerant (flooding-based store-carry-forward) routing of both readings and queries, which is inappropriate for applications with data freshness constraints, and which is incompatible with stringent device power/memory constraints. Alternatively, we propose the use of amorphous placement and retrieval (APR), in which routing and ïŹeld monitoring are integrated through the use of a cache management scheme coupled with an informed exchange of cached samples to diffuse sensory data throughout the network, in such a way that a query answer is likely to be found close to the query origin. We argue that knowledge of the distribution of query targets could be used effectively by an informed cache management policy to maximize the utility of collective storage of all devices. Using a simple analytical model, we show that the use of informed cache management is particularly important when the mobility model results in a non-uniform distribution of users over the ïŹeld. We present results from extensive simulations which show that in sparsely-connected networks, APR is more cost-effective than DPR, that it provides extra resilience to node failure and packet losses, and that its use of informed cache management yields superior performance
Practical Distributed Control Synthesis
Classic distributed control problems have an interesting dichotomy: they are
either trivial or undecidable. If we allow the controllers to fully
synchronize, then synthesis is trivial. In this case, controllers can
effectively act as a single controller with complete information, resulting in
a trivial control problem. But when we eliminate communication and restrict the
supervisors to locally available information, the problem becomes undecidable.
In this paper we argue in favor of a middle way. Communication is, in most
applications, expensive, and should hence be minimized. We therefore study a
solution that tries to communicate only scarcely and, while allowing
communication in order to make joint decision, favors local decisions over
joint decisions that require communication.Comment: In Proceedings INFINITY 2011, arXiv:1111.267
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