82 research outputs found
Centralized Coded Caching with User Cooperation
In this paper, we consider the coded-caching broadcast network with user
cooperation, where a server connects with multiple users and the users can
cooperate with each other through a cooperation network. We propose a
centralized coded caching scheme based on a new deterministic placement
strategy and a parallel delivery strategy. It is shown that the new scheme
optimally allocate the communication loads on the server and users, obtaining
cooperation gain and parallel gain that greatly reduces the transmission delay.
Furthermore, we show that the number of users who parallelly send information
should decrease when the users' caching size increases. In other words, letting
more users parallelly send information could be harmful. Finally, we derive a
constant multiplicative gap between the lower bound and upper bound on the
transmission delay, which proves that our scheme is order optimal.Comment: 9 pages, submitted to ITW201
Cascaded Code Distributed Computing With Low Complexity and Improved Flexibility
Coded distributed computing (CDC), proposed by Li et al., offers significant
potential for reducing the communication load in MapReduce computing systems.
In the setting of the cascaded CDC that consisting of nodes, input
files, and output functions, the objective is to compute each output
function through nodes with a computation load , enabling
the application of coding techniques during the Shuffle phase to achieve
minimum communication load. However, a significant limitation in most existing
cascaded CDC schemes is their demand for splitting the original data into an
exponentially growing number of input files and requiring an exponentially
large number of output functions, which imposes stringent requirements for
implementation. In this paper, we focus on the cascaded case of
, deliberately designing the strategy of data placement and
output functions assignment based on a grouping method, such that a
low-complexity Shuffle strategy is achievable. The main advantages of the
proposed scheme include: 1) the multicast gains equal to and
which is approximate to when is relatively large, and the
communication load is quite approximate to or surprisingly better than the
optimal state-of-the-art scheme proposed by Li et al.; 2) the proposed scheme
requires significantly less number of input files and output functions; 3) all
the operations are implemented over the minimum binary field in
the one-shot fashion. Finally, we derive a new converse bound for the cascaded
CDC framework, under the given strategies of data placement and output
functions assignment. We demonstrate that the communication load of the
proposed scheme is order optimal within a factor of ; and is also
approximately optimal when is sufficiently large for a given
Multi-access Coded Caching with Optimal Rate and Linear Subpacketization under PDA and Consecutive Cyclic Placement
This work considers the multi-access caching system proposed by Hachem et
al., where each user has access to L neighboring caches in a cyclic wrap-around
fashion. We first propose a placement strategy called the consecutive cyclic
placement, which achieves the maximal local caching gain. Then under the
consecutive cyclic placement, we derive the optimal coded caching gain from the
perspective of Placement Delivery Array (PDA), thus obtaining a lower bound on
the rate of PDA. Finally, under the consecutive cyclic placement, we construct
a class of PDA, leading to a multi-access coded caching scheme with linear
subpacketization, which achieves our derived lower bound for some parameters;
while for other parameters, the achieved coded caching gain is only 1 less than
the optimal one. Analytical and numerical comparisons of the proposed scheme
with existing schemes are provided to validate the performance.Comment: 30 pages, 7 figure
Hierarchical Cache-Aided Linear Function Retrieval with Security and Privacy Constraints
The hierarchical caching system where a server connects with multiple mirror
sites, each connecting with a distinct set of users, and both the mirror sites
and users are equipped with caching memories has been widely studied. However
all the existing works focus on single file retrieval, i.e., each user requests
one file, and ignore the security and privacy threats in communications. In
this paper we investigate the linear function retrieval problem for
hierarchical caching systems with content security and demand privacy, i.e.,
each user requests a linear combination of files, and meanwhile the files in
the library are protected against wiretappers and users' demands are kept
unknown to other users and unconnected mirror sites. First we propose a new
combination structure named hierarchical placement delivery array (HPDA), which
characterizes the data placement and delivery strategy of a coded caching
scheme. Then we construct two classes of HPDAs. Consequently two classes of
schemes with or without security and privacy are obtained respectively where
the first dedicates to minimizing the transmission load for the first hop and
can achieve the optimal transmission load for the first hop if ignoring the
security and privacy constraints; the second has more flexible parameters on
the memory sizes and a lower subpacketization compared with the first one, and
achieves a tradeoff between subpacketization and transmission loads.Comment: arXiv admin note: substantial text overlap with arXiv:2205.0023
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data
The Transformer has emerged as a versatile and effective architecture with
broad applications. However, it still remains an open problem how to
efficiently train a Transformer model of high utility with differential privacy
guarantees. In this paper, we identify two key challenges in learning
differentially private Transformers, i.e., heavy computation overhead due to
per-sample gradient clipping and unintentional attention distraction within the
attention mechanism. In response, we propose DPFormer, equipped with Phantom
Clipping and Re-Attention Mechanism, to address these challenges. Our
theoretical analysis shows that DPFormer can reduce computational costs during
gradient clipping and effectively mitigate attention distraction (which could
obstruct the training process and lead to a significant performance drop,
especially in the presence of long-tailed data). Such analysis is further
corroborated by empirical results on two real-world datasets, demonstrating the
efficiency and effectiveness of the proposed DPFormer
One-Bit Byzantine-Tolerant Distributed Learning via Over-the-Air Computation
Distributed learning has become a promising computational parallelism
paradigm that enables a wide scope of intelligent applications from the
Internet of Things (IoT) to autonomous driving and the healthcare industry.
This paper studies distributed learning in wireless data center networks, which
contain a central edge server and multiple edge workers to collaboratively
train a shared global model and benefit from parallel computing. However, the
distributed nature causes the vulnerability of the learning process to faults
and adversarial attacks from Byzantine edge workers, as well as the severe
communication and computation overhead induced by the periodical information
exchange process. To achieve fast and reliable model aggregation in the
presence of Byzantine attacks, we develop a signed stochastic gradient descent
(SignSGD)-based Hierarchical Vote framework via over-the-air computation
(AirComp), where one voting process is performed locally at the wireless edge
by taking advantage of Bernoulli coding while the other is operated
over-the-air at the central edge server by utilizing the waveform superposition
property of the multiple-access channels. We comprehensively analyze the
proposed framework on the impacts including Byzantine attacks and the wireless
environment (channel fading and receiver noise), followed by characterizing the
convergence behavior under non-convex settings. Simulation results validate our
theoretical achievements and demonstrate the robustness of our proposed
framework in the presence of Byzantine attacks and receiver noise.Comment: This work has been submitted to the IEEE for possible publication.
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