Cooperative data exchange: A coalition game perspective

Heidarzadeh, Anoosheh; Sprintson, Alex

doi:10.1109/allerton.2016.7852344

Cited by 1 publication

(3 citation statements)

References 21 publications

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“…Let m be such that N (m) = N . By using similar ideas as in the proof of [13,Lemma 4], the following result can be shown. For any S ⊆ N , we say that a set of packets is Stransmittable if the encoding vector of each packet in the set lies in span(U i ) for some i ∈ S. Let ℓ min(r S , l s ).…”

Section: A Proof Of Theoremmentioning

confidence: 85%

“…Let m be such that N (m) = N . By using similar ideas as in the proof of [13,Lemma 4], the following result can be shown. Let {y l } 1≤l≤ls be the set of the algorithm's choice of packets being transmitted from the round 1 to the round l s , and let {v l } 1≤l≤ls be the set of encoding vectors of these packets.…”

Section: A Proof Of Theoremmentioning

confidence: 85%

“…Very recently, in [13], we also studied a related problem, where each user has two utility functions: its rate and its delay. Defining the stability of the grand coalition via the Pareto optimality, with respect to both the rate and delay functions simultaneously, over all minor coalitions, we showed that there does not exist any non-monetary mechanism (without the peer-to-peer payments) that stabilizes the grand coalition for all problem instances.…”

Section: A Related Workmentioning

confidence: 99%

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A Monetary Mechanism for Stabilizing Cooperative Data Exchange with Selfish Users

Heidarzadeh

Tyagi

Shakkottai

et al. 2018

2018 IEEE International Symposium on Information Theory (ISIT)

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This paper considers the problem of stabilizing cooperative data exchange with selfish users. In this setting, each user has a subset of packets in the ground set X, and wants all other packets in X. The users can exchange their packets by broadcasting coded or uncoded packets over a lossless broadcast channel, and monetary transactions are allowed between any pair of users. We define the utility of each user as the sum of two sub-utility functions: (i) the difference between the total payment received by the user and the total transmission rate of the user, and (ii) the difference between the total number of required packets by the user and the total payment made by the user. A rate-vector and payment-matrix pair (r, p) is said to stabilize the grand coalition (i.e., the set of all users) if (r, p) is Pareto optimal over all minor coalitions (i.e., all proper subsets of users who collectively know all packets in X). Our goal is to design a stabilizing rate-payment pair with minimum total sum-rate and minimum total sum-payment for any given instance of the problem. In this work, we propose two algorithms that find such a solution. Moreover, we show that both algorithms maximize the sum of utility of all users (over all solutions), and one of the algorithms also maximizes the minimum utility among all users (over all solutions).

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Section: A Proof Of Theoremmentioning

confidence: 85%

Section: A Proof Of Theoremmentioning

confidence: 85%

Section: A Related Workmentioning

confidence: 99%

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