Age of Information in Multicast Networks with Multiple Update Streams

Buyukates, Baturalp; Soysal, Alkan; Ulukuş, Şennur

doi:10.1109/ieeeconf44664.2019.9048909

Cited by 35 publications

(17 citation statements)

References 25 publications

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“…Similarly, the convexity of f (n i |B i ) with respect to n i established by Proposition 1, together with the bounds on its minimizer established by Proposition 3, enables the efficient solution of problem (22) via the BM. Altogether, using these two techniques, the optimum bandwidth and transmit time allocation problem (20) can be obtained by solving equations (21) and (22) alternately. A pseudocode summarizing the method described above is given in Algorithm 2.…”

Section: Proposition 7: Formentioning

confidence: 99%

Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks

et al. 2020

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Section: Proposition 7: Formentioning

confidence: 99%

Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks

et al. 2020

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“…There have been significant efforts in the age literature to characterize and improve the average age scaling in large networks considering the classical age metric with possibly many sourcedestination pairs. Recent works have achieved O(1) scaling in multicast networks [21]- [25] using a centralized transmission scheme administered by the source, and O(log n) scaling in distributed peer-to-peer communication networks [26], [27] using a hierarchical local cooperation scheme.…”

Section: Introductionmentioning

confidence: 99%

Version Age of Information in Clustered Gossip Networks

Buyukates¹,

Bastopcu²,

Ulukuş³

2021

Preprint

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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 average 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. Next, we increase connectivity in the network and allow gossiping among the cluster heads to improve version age at the receiver nodes. With that, we show that when the cluster heads form a ring network among themselves, we obtain per node average version age scalings of O(n 1 3 ), O(n 1 4), and O(log n) in disconnected, ring, and fully connected cluster models, respectively.Next, focusing on a ring network topology in each cluster, we introduce hierarchy to the considered clustered gossip network model and show that when we employ two levels of hierarchy, we can achieve the same O(n 1 4 ) scaling without using dedicated cluster heads. We generalize this result for h levels of hierarchy and show that per user average version age scaling of O(n) is achievable in the case of a ring network in each cluster across all hierarchy levels. Finally, we find the version age-optimum cluster sizes as a function of the source, cluster head, and node update rates through numerical evaluations.

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“…In [24]- [27] the minimization of age is done over general multihop networks. A wireless network with heterogeneous traffic is considered in [28]- [30]. Another control policy is to assume that the source is monitoring the network servers' idle/busy state and is able to generate status updates at any time, as in [31]- [34].…”

Section: Introductionmentioning

confidence: 99%

The Cost of Delay in Status Updates and Their Value: Non-Linear Ageing

Kosta

Παππάς

Ephremides

et al. 2020

IEEE Trans. Commun.

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We consider a status update communication system consisting of a source-destination link. A stochastic process is observed at the source, where samples are extracted at random time instances, and delivered to the destination, thus, providing status updates for the source. In this paper, we expand the concept of information ageing by introducing the cost of update delay (CoUD) metric to characterize the cost of having stale information at the destination. The CoUD captures the freshness of the information at the destination and can be used to reflect the information structure of the source. Moreover, we introduce the value of information of update (VoIU) metric that captures the reduction of CoUD upon reception of an update. Using the CoUD, its by-product metric called peak cost of update delay (PCoUD), and the VoIU, we evaluate the performance of an M/M/1 system in various settings that consider exact expressions and bounds. Our results indicate that the performance of CoUD differs depending on the cost assigned per This work extends the preliminary study in [1]. A. Kosta, N. Pappas, A. Ephremides, and V. Angelakis are with the

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Age of Information in Multicast Networks with Multiple Update Streams

Cited by 35 publications

References 25 publications

Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks

Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks

Version Age of Information in Clustered Gossip Networks

The Cost of Delay in Status Updates and Their Value: Non-Linear Ageing

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