1,352 research outputs found
Investigating the Cost of Anonymity on Dynamic Networks
In this paper we study the difficulty of counting nodes in a synchronous
dynamic network where nodes share the same identifier, they communicate by
using a broadcast with unlimited bandwidth and, at each synchronous round,
network topology may change. To count in such setting, it has been shown that
the presence of a leader is necessary. We focus on a particularly interesting
subset of dynamic networks, namely \textit{Persistent Distance} - PD, in which each node has a fixed distance from the leader across
rounds and such distance is at most . In these networks the dynamic diameter
is at most . We prove the number of rounds for counting in PD is at least logarithmic with respect to the network size .
Thanks to this result, we show that counting on any dynamic anonymous network
with constant w.r.t. takes at least
rounds where represents the additional cost to be
payed for handling anonymity. At the best of our knowledge this is the fist non
trivial, i.e. different from , lower bounds on counting in anonymous
interval connected networks with broadcast and unlimited bandwith
Line-Recovery by Programmable Particles
Shape formation has been recently studied in distributed systems of
programmable particles. In this paper we consider the shape recovery problem of
restoring the shape when of the particles have crashed. We focus on the
basic line shape, used as a tool for the construction of more complex
configurations.
We present a solution to the line recovery problem by the non-faulty
anonymous particles; the solution works regardless of the initial distribution
and number of faults, of the local orientations of the non-faulty
entities, and of the number of non-faulty entities activated in each round
(i.e., semi-synchronous adversarial scheduler)
On deterministic counting in anonymous dynamic networks
Nella tesi di dottorato si analizza il problema del counting in reti anonime dinamiche ed interval connesse. Vengono dimostrati lower bound non triviali sul tempo di conteggio in reti a diametro costante. Inoltre vengono sviluppati nuovi algoritmi di conteggio.Counting is a fundamental problem of every distributed system as it represents a basic building block to implement high level abstractions [2,4,6]. We focus on deterministic counting algorithms, that is we assume that no source of randomness is available to processes. We consider a dynamic system where processes do not leave the compu- tation while there is an adversary that continuously changes the communication graph connecting such processes. The adversary is only constrained to maintain at each round a connected topology, i.e. 1-interval connectivity G(1-IC) [3]. In such environment, it has been shown, [5], that counting cannot be solved without a leader. Therefore, we assume that all processes are anonymous but the distinguished leader.
In the thesis we will discuss bounds and algorithms for counting in the aforementioned framework. Our bounds are obtained investigating networks where the distance between the leader and an anonymous process is persistent across rounds and is at most h, we denote such networks as G(PD)h [1]. Interestingly we will show that counting in G(PD)2 requires Ω(log |V |) rounds even when the bandwidth is unlimited. This implies that counting in networks with constant dynamic diameter requires a number of rounds that is function of the network size. We will discuss other results concerning the accuracy of counting algorithms.
For the possibility side we will show an optimal counting algorithm for G(PD)h networks and a counting algorithm for G(1-IC) networks
Non Trivial Computations in Anonymous Dynamic Networks
In this paper we consider a static set of anonymous processes, i.e., they do not have distinguished IDs, that communicate with neighbors using a local broadcast primitive. The communication graph changes at each computational round with the restriction of being always connected, i.e., the network topology guarantees 1-interval connectivity. In such setting non trivial computations, i.e., answering to a predicate like "there exists at least one process with initial input a?", are impossible. In a recent work, it has been conjectured that the impossibility holds even if a distinguished leader process is available within the computation. In this paper we prove that the conjecture is false. We show this result by implementing a deterministic leader-based terminating counting algorithm. In order to build our counting algorithm we first develop a counting technique that is time optimal on a family of dynamic graphs where each process has a fixed distance h from the leader and such distance does not change along rounds. Using this technique we build an algorithm that counts in anonymous 1-interval connected networks
Optimal Computation in Leaderless and Multi-Leader Disconnected Anonymous Dynamic Networks
We give a simple characterization of which functions can be computed
deterministically by anonymous processes in disconnected dynamic networks,
depending on the number of leaders in the network. In addition, we provide
efficient distributed algorithms for computing all such functions assuming
minimal or no knowledge about the network. Each of our algorithms comes in two
versions: one that terminates with the correct output and a faster one that
stabilizes on the correct output without explicit termination. Notably, these
are the first deterministic algorithms whose running times scale linearly with
both the number of processes and a parameter of the network which we call
"dynamic disconnectivity". We also provide matching lower bounds, showing that
all our algorithms are asymptotically optimal for any fixed number of leaders.
While most of the existing literature on anonymous dynamic networks relies on
classical mass-distribution techniques, our work makes use of a recently
introduced combinatorial structure called "history tree", also developing its
theory in new directions. Among other contributions, our results make
definitive progress on two popular fundamental problems for anonymous dynamic
networks: leaderless Average Consensus (i.e., computing the mean value of input
numbers distributed among the processes) and multi-leader Counting (i.e.,
determining the exact number of processes in the network). In fact, our
approach unifies and improves upon several independent lines of research on
anonymous networks, including Nedic et al., IEEE Trans. Automat. Contr. 2009;
Olshevsky, SIAM J. Control Optim. 2017; Kowalski-Mosteiro, ICALP 2019, SPAA
2021; Di Luna-Viglietta, FOCS 2022.Comment: 35 pages, 1 figure. arXiv admin note: text overlap with
arXiv:2204.0212
SAFE: Self-Attentive Function Embeddings for Binary Similarity
The binary similarity problem consists in determining if two functions are
similar by only considering their compiled form. Advanced techniques for binary
similarity recently gained momentum as they can be applied in several fields,
such as copyright disputes, malware analysis, vulnerability detection, etc.,
and thus have an immediate practical impact. Current solutions compare
functions by first transforming their binary code in multi-dimensional vector
representations (embeddings), and then comparing vectors through simple and
efficient geometric operations. However, embeddings are usually derived from
binary code using manual feature extraction, that may fail in considering
important function characteristics, or may consider features that are not
important for the binary similarity problem. In this paper we propose SAFE, a
novel architecture for the embedding of functions based on a self-attentive
neural network. SAFE works directly on disassembled binary functions, does not
require manual feature extraction, is computationally more efficient than
existing solutions (i.e., it does not incur in the computational overhead of
building or manipulating control flow graphs), and is more general as it works
on stripped binaries and on multiple architectures. We report the results from
a quantitative and qualitative analysis that show how SAFE provides a
noticeable performance improvement with respect to previous solutions.
Furthermore, we show how clusters of our embedding vectors are closely related
to the semantic of the implemented algorithms, paving the way for further
interesting applications (e.g. semantic-based binary function search).Comment: Published in International Conference on Detection of Intrusions and
Malware, and Vulnerability Assessment (DIMVA) 201
Meeting in a Polygon by Anonymous Oblivious Robots
The Meeting problem for searchers in a polygon (possibly with
holes) consists in making the searchers move within , according to a
distributed algorithm, in such a way that at least two of them eventually come
to see each other, regardless of their initial positions. The polygon is
initially unknown to the searchers, and its edges obstruct both movement and
vision. Depending on the shape of , we minimize the number of searchers
for which the Meeting problem is solvable. Specifically, if has a
rotational symmetry of order (where corresponds to no
rotational symmetry), we prove that searchers are sufficient, and
the bound is tight. Furthermore, we give an improved algorithm that optimally
solves the Meeting problem with searchers in all polygons whose
barycenter is not in a hole (which includes the polygons with no holes). Our
algorithms can be implemented in a variety of standard models of mobile robots
operating in Look-Compute-Move cycles. For instance, if the searchers have
memory but are anonymous, asynchronous, and have no agreement on a coordinate
system or a notion of clockwise direction, then our algorithms work even if the
initial memory contents of the searchers are arbitrary and possibly misleading.
Moreover, oblivious searchers can execute our algorithms as well, encoding
information by carefully positioning themselves within the polygon. This code
is computable with basic arithmetic operations, and each searcher can
geometrically construct its own destination point at each cycle using only a
compass. We stress that such memoryless searchers may be located anywhere in
the polygon when the execution begins, and hence the information they initially
encode is arbitrary. Our algorithms use a self-stabilizing map construction
subroutine which is of independent interest.Comment: 37 pages, 9 figure
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