156,389 research outputs found
Storage and Search in Dynamic Peer-to-Peer Networks
We study robust and efficient distributed algorithms for searching, storing,
and maintaining data in dynamic Peer-to-Peer (P2P) networks. P2P networks are
highly dynamic networks that experience heavy node churn (i.e., nodes join and
leave the network continuously over time). Our goal is to guarantee, despite
high node churn rate, that a large number of nodes in the network can store,
retrieve, and maintain a large number of data items. Our main contributions are
fast randomized distributed algorithms that guarantee the above with high
probability (whp) even under high adversarial churn:
1. A randomized distributed search algorithm that (whp) guarantees that
searches from as many as nodes ( is the stable network size)
succeed in -rounds despite churn, for
any small constant , per round. We assume that the churn is
controlled by an oblivious adversary (that has complete knowledge and control
of what nodes join and leave and at what time, but is oblivious to the random
choices made by the algorithm).
2. A storage and maintenance algorithm that guarantees (whp) data items can
be efficiently stored (with only copies of each data item)
and maintained in a dynamic P2P network with churn rate up to
per round. Our search algorithm together with our
storage and maintenance algorithm guarantees that as many as nodes
can efficiently store, maintain, and search even under churn per round. Our algorithms require only polylogarithmic in bits to
be processed and sent (per round) by each node.
To the best of our knowledge, our algorithms are the first-known,
fully-distributed storage and search algorithms that provably work under highly
dynamic settings (i.e., high churn rates per step).Comment: to appear at SPAA 201
Data Structures in Classical and Quantum Computing
This survey summarizes several results about quantum computing related to
(mostly static) data structures. First, we describe classical data structures
for the set membership and the predecessor search problems: Perfect Hash tables
for set membership by Fredman, Koml\'{o}s and Szemer\'{e}di and a data
structure by Beame and Fich for predecessor search. We also prove results about
their space complexity (how many bits are required) and time complexity (how
many bits have to be read to answer a query). After that, we turn our attention
to classical data structures with quantum access. In the quantum access model,
data is stored in classical bits, but they can be accessed in a quantum way: We
may read several bits in superposition for unit cost. We give proofs for lower
bounds in this setting that show that the classical data structures from the
first section are, in some sense, asymptotically optimal - even in the quantum
model. In fact, these proofs are simpler and give stronger results than
previous proofs for the classical model of computation. The lower bound for set
membership was proved by Radhakrishnan, Sen and Venkatesh and the result for
the predecessor problem by Sen and Venkatesh. Finally, we examine fully quantum
data structures. Instead of encoding the data in classical bits, we now encode
it in qubits. We allow any unitary operation or measurement in order to answer
queries. We describe one data structure by de Wolf for the set membership
problem and also a general framework using fully quantum data structures in
quantum walks by Jeffery, Kothari and Magniez
A Search Strategy of Level-Based Flooding for the Internet of Things
This paper deals with the query problem in the Internet of Things (IoT).
Flooding is an important query strategy. However, original flooding is prone to
cause heavy network loads. To address this problem, we propose a variant of
flooding, called Level-Based Flooding (LBF). With LBF, the whole network is
divided into several levels according to the distances (i.e., hops) between the
sensor nodes and the sink node. The sink node knows the level information of
each node. Query packets are broadcast in the network according to the levels
of nodes. Upon receiving a query packet, sensor nodes decide how to process it
according to the percentage of neighbors that have processed it. When the
target node receives the query packet, it sends its data back to the sink node
via random walk. We show by extensive simulations that the performance of LBF
in terms of cost and latency is much better than that of original flooding, and
LBF can be used in IoT of different scales
Localized quantum walks as secured quantum memory
We show that a quantum walk process can be used to construct and secure
quantum memory. More precisely, we show that a localized quantum walk with
temporal disorder can be engineered to store the information of a single,
unknown qubit on a compact position space and faithfully recover it on demand.
Since the localization occurss with a finite spread in position space, the
stored information of the qubit will be naturally secured from the simple
eavesdropper. Our protocol can be adopted to any quantum system for which
experimental control over quantum walk dynamics can be achieved.Comment: 7 pages, 4 figure
Doped Fountain Coding for Minimum Delay Data Collection in Circular Networks
This paper studies decentralized, Fountain and network-coding based
strategies for facilitating data collection in circular wireless sensor
networks, which rely on the stochastic diversity of data storage. The goal is
to allow for a reduced delay collection by a data collector who accesses the
network at a random position and random time. Data dissemination is performed
by a set of relays which form a circular route to exchange source packets. The
storage nodes within the transmission range of the route's relays linearly
combine and store overheard relay transmissions using random decentralized
strategies. An intelligent data collector first collects a minimum set of coded
packets from a subset of storage nodes in its proximity, which might be
sufficient for recovering the original packets and, by using a message-passing
decoder, attempts recovering all original source packets from this set.
Whenever the decoder stalls, the source packet which restarts decoding is
polled/doped from its original source node. The random-walk-based analysis of
the decoding/doping process furnishes the collection delay analysis with a
prediction on the number of required doped packets. The number of doped packets
can be surprisingly small when employed with an Ideal Soliton code degree
distribution and, hence, the doping strategy may have the least collection
delay when the density of source nodes is sufficiently large. Furthermore, we
demonstrate that network coding makes dissemination more efficient at the
expense of a larger collection delay. Not surprisingly, a circular network
allows for a significantly more (analytically and otherwise) tractable
strategies relative to a network whose model is a random geometric graph
- …