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1. The Age of Gossip in Networks

   https://doi.org/10.1109/ISIT45174.2021.9517796  

   Yates, Roy D. (July 2021, 2021 IEEE International Symposium on Information Theory (ISIT))

   A source node updates its status as a point process and also forwards its updates to a network of observer nodes. Within the network of observers, these updates are forwarded as point processes from node to node. Each node wishes its knowledge of the source to be as timely as possible. In this network, timeliness is measured by a discrete form of age of information: each status change at the source is referred to as a version and the age at a node is how many versions out of date is its most recent update from the source. This work introduces a method for evaluating the average version age at each node in the network when nodes forward updates using a memoryless gossip protocol. This method is then demonstrated by version age analysis for a collection of simple networks. For gossip on a complete graph with symmetric updating rates, it is shown that each node has average age that grows as the logarithm of the network size. 

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2. Timely Gossip

   https://doi.org/10.1109/SPAWC51858.2021.9593163  

   Yates, Roy D. (September 2021, 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC))

   A source node forwards fresh status updates as a point process to a network of observer nodes. Within the network of observers, these updates are forwarded as point processes from node to node. Each node wishes its knowledge of the source to be as timely as possible. In this network, timeliness at each node is measured by an age of information metric: how old is the timestamp of the freshest received update. This work extends a method for evaluating the average age at each node in the network when nodes forward updates using a memoryless gossip protocol. This method is then demonstrated by age analysis for a simple network. 

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3. Average Age of Information in Update Systems with Active Sources and Packet Delivery Errors

   https://doi.org/10.1109/LWC.2020.2983397  

   Farazi, S.; Klein, A.; Brown, D. (August 2020, IEEE wireless communications letters)

   This paper studies the “age of information” (AoI) in a multi-source status update system where N active sources each send updates of their time-varying process to a monitor through a server with packet delivery errors. We analyze the average AoI for stationary randomized and round-robin scheduling policies. For both of these scheduling policies, we further analyze the effect of packet retransmission policies, i.e., retransmission without re- sampling, retransmission with resampling, or no retransmission, when errors occur. Expressions for the average AoI are derived for each case. It is shown that the round-robin schedule policy in conjunction with retransmission with resampling when errors occur achieves the lowest average AoI among the considered cases. For stationary randomized schedules with equiprobable source selection, it is further shown that the average AoI gap to round-robin schedules with the same packet management policy scales as O(N). Finally, for stationary randomized policies, the optimal source selection probabilities that minimize a weighted sum average AoI metric are derived. 

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4. Multicast with Prioritized Delivery: How Fresh is Your Data?

   https://doi.org/10.1109/SPAWC.2018.8446018  

   Zhong, Jing; Yates, Roy D.; Soljanin, Emina (June 2018, Signal Processing Advances in Wireless Communications (SPAWC), IEEE Workshop on)

   We consider a multicast network in which real-time status updates generated by a source are replicated and sent to multiple interested receiving nodes through independent links. The receiving nodes are divided into two groups: one priority group consists of k nodes that require the reception of every update packet, the other non-priority group consists of all other nodes without the delivery requirement. Using age of information as a freshness metric, we analyze the time-averaged age at both priority and non-priority nodes. For shifted-exponential link delay distributions, the average age at a priority node is lower than that at a non-priority node due to the delivery guarantee. However, this advantage for priority nodes disappears if the link delay is exponential distributed. Both groups of nodes have the same time-averaged age, which implies that the guaranteed delivery of updates has no effect the time-averaged freshness. 

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5. Decentralized Learning Robust to Data Poisoning Attacks

   https://doi.org/10.1109/CDC51059.2022.9992702  

   Mao, Yanwen; Data, Deepesh; Diggavi, Suhas; Tabuada, Paulo (January 2022, IEEE Control and Decision Conference (CDC))

   This paper addresses the problem of decentralized learning in the presence of data poisoning attacks. In this problem, we consider a collection of nodes connected through a network, each equipped with a local function. The objective is to compute the global minimizer of the aggregated local functions, in a decentralized manner, i.e., each node can only use its local function and data exchanged with nodes it is connected to. Moreover, each node is to agree on the said minimizer despite an adversary that can arbitrarily change the local functions of a fraction of the nodes. This problem setting has applications in robust learning, where nodes in a network are collectively training a model that minimizes the empirical loss with possibly attacked local data sets. In this paper, we propose a novel decentralized learning algorithm that enables all nodes to reach consensus on the optimal model, in the absence of attacks, and approximate consensus in the presence of data poisoning attacks. 

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