Electrical Engineering

This paper proposes a new multimode communication service, denoted as Remote Expert Consultation Service (REC-Service) which determines the way group teleworking is realized among distributed entities (workstations, data bases, etc) during a conference for medical diagnosis. The REC-Service organizes the involved operations into five different types, called Conferencing Modes (CM), where each CM yields a traffic with variable attributes and requires of the network a special quality of service. Moreover, the structure of a Broadband user-Network Interface Unit (BNIU) is defined. BNIU statistically multiplexes the traffic of the entities working in different CMs into an Integrated Broadband Communication (IBC) network. The maximum number of entities served per BNIU and the bandwidth usability have been calculated for several operating modes by modelling the BNIU as a queueing system and by applying special quality criteria, delay demands and traffic assumptions.

Given n randomly located source-destination (S-D) pairs on a fixed area network that want to communicate with each other, we study the age of information with a particular focus on its scaling as the network size n grows. We propose a threephase transmission scheme that utilizes hierarchical cooperation between users along with mega update packets and show that an average age scaling of O(n α(h) log n) per-user is achievable where h denotes the number of hierarchy levels and α(h) = 1 3•2 h +1 which tends to 0 as h increases such that asymptotically average age scaling of the proposed scheme is O(log n). To the best of our knowledge, this is the best average age scaling result in a status update system with multiple S-D pairs.

We consider the age of information in a multicast network where there is a single source node that sends timesensitive updates to n receiver nodes. Each status update is one of two kinds: type I or type II. To study the age of information experienced by the receiver nodes for both types of updates, we consider two cases: update streams are generated by the source node at-will and update streams arrive exogenously to the source node. We show that using an earliest k1 and k2 transmission scheme for type I and type II updates, respectively, the age of information of both update streams at the receiver nodes can be made a constant independent of n. In particular, the source node transmits each type I update packet to the earliest k1 and each type II update packet to the earliest k2 of n receiver nodes. We determine the optimum k1 and k2 stopping thresholds for arbitrary shifted exponential link delays to individually and jointly minimize the average age of both update streams and characterize the pareto optimal curve for the two ages.

We study age of information in a multiple sourcemultiple destination setting with a focus on its scaling in large wireless networks. There are n nodes that are randomly paired with each other on a fixed area to form n source-destination (S-D) pairs. We propose a three-phase transmission scheme which utilizes local cooperation between the nodes by forming what we call mega update packets to serve multiple S-D pairs at once. We show that under the proposed scheme average age of an S-D pair scales as O(n 1 4) as the number of users, n, in the network grows. To the best of our knowledge, this is the best age scaling result for a multiple source-multiple destination setting.

Distributed implementations are crucial in speeding up large scale machine learning applications. Distributed gradient descent (GD) is widely employed to parallelize the learning task by distributing the dataset across multiple workers. A significant performance bottleneck for the per-iteration completion time in distributed synchronous GD is straggling workers. Coded distributed computation techniques have been introduced recently to mitigate stragglers and to speed up GD iterations by assigning redundant computations to workers. In this paper, we consider gradient coding (GC), and propose a novel dynamic GC scheme, which assigns redundant data to workers to acquire the flexibility to dynamically choose from among a set of possible codes depending on the past straggling behavior. In particular, we consider GC with clustering, and regulate the number of stragglers in each cluster by dynamically forming the clusters at each iteration; hence, the proposed scheme is called GC with dyna...

We study age of information in a status updating system that consists of a single sampler, i.e., source node, that sends time-sensitive status updates to a single monitor node through a server node. We first consider a Gilbert-Elliot service profile at the server node. In this model, service times at the server node follow a finite state Markov chain with two states: bad state b and good state g where the server is faster in state g. We determine the time average age experienced by the monitor node and characterize the age-optimal state transition matrix P with and without an average cost constraint on the service operation. Next, we consider a Gilbert-Elliot sampling profile at the source. In this model, the interarrival times follow a finite state Markov chain with two states: bad state b and good state g where samples are more frequent in state g. We find the time average age experienced by the monitor node and characterize the age-optimal state transition matrix P .

We consider a network consisting of a single source and n receiver nodes that are grouped into m equal size communities, i.e., clusters, where each cluster includes k nodes and is served by a dedicated cluster head. The source node keeps versions of an observed process and updates each cluster through the associated cluster head. Nodes within each cluster are connected to each other according to a given network topology. Based on this topology, each node relays its current update to its neighboring nodes by local gossiping. We use the version age metric to quantify information timeliness at the receiver nodes. We consider disconnected, ring, and fully connected network topologies for each cluster. For each of these network topologies, we characterize the average version age at each node and find the version age scaling as a function of the network size n. Our results indicate that per node version age scalings of O(√ n), O(n 1 3), and O(log n) are achievable in disconnected, ring, and fully connected cluster models, respectively. Finally, through numerical evaluations, we determine the version age-optimum (m, k) pairs as a function of the source, cluster head, and node update rates.

INTRODUCTION Both system and relaxation induced time delays complicate image reconstruction in x-space magnetic particle imaging (MPI). Relaxation reduces the signal-to-noise ratio (SNR) and blurs the image along the scan direction [1-4]. System delays, on the other hand, introduce unwanted image artifacts. Hence, determining the delays accurately is crucial for obtaining artifact-free images. Here, we propose a method to estimate the effective time delay for relaxationand systeminduced sources, without any a priori knowledge.

In distributed synchronous gradient descent (GD) the main performance bottleneck for the per-iteration completion time is the slowest straggling workers. To speed up GD iterations in the presence of stragglers, coded distributed computation techniques are implemented by assigning redundant computations to workers. In this paper, we propose a novel gradient coding (GC) scheme that utilizes dynamic clustering, denoted by GC-DC, to speed up gradient calculations. Under time-correlated straggling behavior, GC-DC aims at regulating the number of straggling workers in each cluster based on the straggler behavior in the previous iteration. We numerically show that GC-DC provides significant improvements in the average completion time (of each iteration) with no increase in the communication load compared to the original GC scheme.

We consider a system in which an information source generates independent and identically distributed status update packets from an observed phenomenon that takes n possible values based on a given pmf. These update packets are encoded at the transmitter node to be sent to the receiver node. Instead of encoding all n possible realizations, the transmitter node only encodes the most probable k realizations and disregards whenever a realization from the remaining n−k values occurs. We find the average age and determine the age-optimal real codeword lengths such that the average age at the receiver node is minimized. Through numerical evaluations for arbitrary pmfs, we show that this selective encoding policy results in a lower average age than encoding every realization and find the age-optimal k. We also analyze a randomized selective encoding policy in which the remaining n−k realizations are encoded and sent with a certain probability to further inform the receiver at the expense o...

We consider a status update system in which the update packets need to be processed to extract the embedded useful information. The source node sends the acquired information to a computation unit (CU) which consists of a master node and n worker nodes. The master node distributes the received computation task to the worker nodes. Upon computation, the master node aggregates the results and sends them back to the source node to keep it updated. We study the age performance of uncoded and coded (repetition coded, MDS coded, and multi-message MDS (MM-MDS) coded) schemes in the presence of stragglers under i.i.d. exponential transmission delays and i.i.d. shifted exponential computation times. We show that asymptotically MM-MDS coded scheme outperforms the other schemes. Finally, we characterize the age-optimal codes.

We consider the binary freshness metric for gossip networks that consist of a single source and n end-nodes, where the end-nodes are allowed to share their stored versions of the source information with the other nodes. We develop recursive equations that characterize binary freshness in arbitrarily connected gossip networks using the stochastic hybrid systems (SHS) approach. Next, we study binary freshness in several structured gossip networks, namely disconnected, ring and fully connected networks. We show that for both disconnected and ring network topologies, when the number of nodes gets large, the binary freshness of a node decreases down to 0 as n, but the freshness is strictly larger for the ring topology. We also show that for the fully connected topology, the rate of decrease to 0 is slower, and it takes the form of n for a ρ smaller than 1, when the update rates of the source and the end-nodes are sufficiently large. Finally, we study the binary freshness metric for clust...

An information source generates independent and identically distributed status update messages from an observed random phenomenon which takes n distinct values based on a given pmf. These update packets are encoded at the transmitter to be sent to a receiver which wants to track the observed random variable with as little age as possible. The transmitter implements a selective k encoding policy such that rather than encoding all possible n realizations, the transmitter encodes the most probable k realizations and sends a designated empty symbol when one of the remaining n−k realizations occurs. We consider two scenarios: when the empty symbol does not reset the age and when the empty symbol resets the age. We find the time average age of information and the age-optimal real codeword lengths, including the codeword length for the empty symbol, for both of these scenarios. Through numerical evaluations for arbitrary pmfs, we show that this selective encoding policy yields a lower age ...

We consider a network consisting of a single source and n receiver nodes that are grouped into equal-sized clusters. Each cluster corresponds to a distinct community such that nodes that belong to different communities cannot exchange information. We use dedicated cluster heads in each cluster to facilitate communication between the source and the nodes within that cluster. Inside clusters, nodes are connected to each other according to a given network topology. Based on the connectivity among the nodes, each node relays its current stored version of the source update to its neighboring nodes by local gossiping. We use the version age metric to assess information freshness at the receiver nodes. We consider disconnected, ring, and fully connected network topologies for each cluster. For each of these network topologies, we characterize the average version age at each node and find the average version age scaling as a function of the network size n. Our results indicate that per node...

Coded computation can speed up distributed learning in the presence of straggling workers. Partial recovery of the gradient vector can further reduce the computation time at each iteration; however, this can result in biased estimators, which may slow down convergence, or even cause divergence. Estimator bias is particularly prevalent when the straggling behavior is correlated over time, which results in the gradient estimators being dominated by a few fast servers. To mitigate biased estimators, we design a timely dynamic encoding framework for partial recovery that includes an ordering operator that changes the codewords and computation orders at workers over time. To regulate the recovery frequencies, we adopt an age metric in the design of the dynamic encoding scheme. The proposed age-based scheme prioritizes the recovery of computations with relatively large age. We show through numerical results that the proposed dynamic encoding strategy increases the timeliness of the recove...

We consider a foundational unsupervised learning task of k-means data clustering, in a federated learning (FL) setting consisting of a central server and many distributed clients. We develop SecFC, which is a secure federated clustering algorithm that simultaneously achieves 1) universal performance: no performance loss compared with clustering over centralized data, regardless of data distribution across clients; 2) data privacy: each client's private data and the cluster centers are not leaked to other clients and the server. In SecFC, the clients perform Lagrange encoding on their local data and share the coded data in an information-theoretically private manner; then leveraging the algebraic structure of the coding, the FL network exactly executes the Lloyd's k-means heuristic over the coded data to obtain the final clustering. Experiment results on synthetic and real datasets demonstrate the universally superior performance of SecFC for different data distributions across clients, and its computational practicality for various combinations of system parameters. Finally, we propose an extension of SecFC to further provide membership privacy for all data points.

We consider the age of information in a multihop multicast network where there is a single source node sending time-sensitive updates to n L end nodes, and L denotes the number of hops. In the first hop, the source node sends updates to n first-hop receiver nodes, and in the second hop each first-hop receiver node relays the update packets that it has received to n further users that are connected to it. This network architecture continues in further hops such that each receiver node in hop ℓ is connected to n further receiver nodes in hop ℓ + 1. We study the age of information experienced by the end nodes, and in particular, its scaling as a function of n. We show that, using an earliest k transmission scheme in each hop, the age of information at the end nodes can be made a constant independent of n. In particular, the source node transmits each update packet to the earliest k 1 of the n first-hop nodes, and each first-hop node that receives the update relays it to the earliest k 2 out of n second-hop nodes that are connected to it and so on. We determine the optimum k ℓ stopping value for each hop ℓ for arbitrary shifted exponential link delays.

We consider a status update system in which the update packets need to be processed to extract the embedded useful information. The source node sends the acquired information to a computation unit (CU) which consists of a master node and n worker nodes. The master node distributes the received computation task to the worker nodes. Upon computation, the master node aggregates the results and sends them back to the source node to keep it updated. We investigate the age performance of uncoded and coded (repetition coded, MDS coded, and multi-message MDS (MM-MDS) coded) schemes in the presence of stragglers under i.i.d. exponential transmission delays and i.i.d shifted exponential computation times. We show that asymptotically MM-MDS coded scheme outperforms the other schemes. Furthermore, we characterize the optimal codes such that the average age is minimized.

We study age of information in a multiple source-multiple destination setting with a focus on its scaling in large wireless networks. There are n nodes uniformly and independently distributed on a fixed area that are randomly paired with each other to form n source-destination (S-D) pairs. Each source node wants to keep its destination node as up-to-date as possible. To accommodate successful communication between all n S-D pairs, we first propose a three-phase transmission scheme which utilizes local cooperation between the nodes along with what we call mega update packets to serve multiple S-D pairs at once. We show that under the proposed scheme average age of an S-D pair scales as O(n 1 4 log n) as the number of users, n, in the network grows. Next, we observe that communications that take place in Phases I and III of the proposed scheme are scaled-down versions of network-level communications. With this along with scale-invariance of the system, we introduce hierarchy to improve this scaling result and show that when hierarchical cooperation between users is utilized, an average age scaling of O(n α(h) log n) per-user is achievable, where h denotes the number of hierarchy levels and α(h) = 1 3•2 h +1. We note that α(h) tends to 0 as h increases, and asymptotically, the average age scaling of the proposed hierarchical scheme is O(log n). To the best of our knowledge, this is the best average age scaling result in a status update system with multiple S-D pairs.