Multi-hop data dissemination with selfish nodes: Optimal decision and fair cost allocation based on the Shapley value

Mousavi, Mahdi; Müller, Sabrina; Al-Shatri, Hussein; Freisleben, Bernd; Klein, Anja

doi:10.1109/icc.2016.7511321

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…We now discuss the properties of ES and SV schemes if one applies them to the MPBT problem. ES and SV are two of the widely-adopted budget-balanced schemes in the field of CSGs and are known to be fair depending on the application [40], [41]. CNs are sorted as M j and p uni 0,j = 0 ≤ p uni 1,j ≤ · · · ≤ p uni i,j ≤ · · · ≤ p uni |M j |,j , then, the cost of the i-th node based on the Shapley value is given by [43]…”

Section: Definition 2 (Potential Game)mentioning

confidence: 99%

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

Mousavi

Al-Shatri

Klein

2020

IEEE Trans. Wireless Commun.

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We study multi-hop broadcast in wireless networks with one source node and multiple receiving nodes. The message flow from the source to the receivers can be modeled as a tree-graph, called broadcast-tree. The problem of finding the minimum-power broadcast-tree (MPBT) is NP-complete.Unlike most of the existing centralized approaches, we propose a decentralized algorithm, based on a non-cooperative cost-sharing game. In this game, every receiving node, as a player, chooses another node of the network as its respective transmitting node for receiving the message. Consequently, a cost is assigned to the receiving node based on the power imposed on its chosen transmitting node.In our model, the total required power at a transmitting node consists of (i) the transmit power and (ii) the circuitry power needed for communication hardware modules. We develop our algorithm using the marginal contribution (MC) cost-sharing scheme and show that it is the only scheme by which the optimum broadcast-tree is always a Nash equilibrium (NE) of the game. Simulation results demonstrate that our proposed algorithm outperforms conventional algorithms for the MPBT problem. Besides, we show that the circuitry power, which is usually ignored by existing algorithms, significantly impacts the energy-efficiency of the network. Index TermsEnergy-efficiency; minimum-power multi-hop broadcast; potential game; optimization. is disseminated through the network with the help of some intermediate nodes which re-transmit the message. This problem is known as the minimum-power broadcast-tree (MPBT) problem since the connections between the source and the receiving nodes form a tree-graph rooted at the source, called the broadcast-tree [1]. MPBT construction has been studied by researchers extensively during the past two decades [1][2][3][4][5][6][7][8][9][10][11][12]. NP-completeness of the MPBT can be shown by reducing the Steiner tree problem to it [13]. This means that a polynomial-time algorithm to find the optimum broadcast-tree unlikely exists. Although many algorithms have been proposed for the MPBT problem, most of them are centralized heuristics [1-6]. Since multi-hop device-todevice communication is seen as a promising technique for improving the capacity of 5G cellular networks [14] and due to the variety of its applications, e.g., video streaming [15], vehicular communications [16], etc., it is vital to revisit the MPBT problem to find a decentralized yet efficient algorithm for it.Seeing the MPBT problem from a decentralized optimization point of view, every individual node has to play its own role in forming the broadcast-tree by establishing a communication link to another node. This can be suitably modeled by game theory, in which the players of the game, here the nodes, are typically modeled as selfish agents seeking to minimize (maximize) their own cost (revenue). In our work, the action of a node is to choose another node in the network as its respective transmitting node to receive the source's message from. As a consequence of i...

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Section: Definition 2 (Potential Game)mentioning

confidence: 99%

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

Mousavi

Al-Shatri

Klein

2020

IEEE Trans. Wireless Commun.

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“…The importance of multi-hop broadcast for future communication networks implies the need for a more comprehensive algorithm capable of addressing both the energy efficiency and incentive issue which, to the best of our knowledge, has not been addressed in the literature. In [1], [16], we proposed game-theoretic algorithms for minimum-power multihop broadcast. Although [16] considers MRC, the decision making at the nodes is based on a heuristic iterative approach which may not necessarily be the best decision for the node.…”

Section: State Of the Art And Main Contributionsmentioning

confidence: 99%

“…Although [16] considers MRC, the decision making at the nodes is based on a heuristic iterative approach which may not necessarily be the best decision for the node. In [1], we showed that the decision-making problem at the nodes can be solved optimally by a linear program in contrast to the heuristic approach of [16].…”

Section: State Of the Art And Main Contributionsmentioning

confidence: 99%

“…In the present work, we improve our work in [1], where a decentralized approach merely for social cost minimization is proposed. Here, we propose a general framework for data dissemination which can be employed for social cost or network power minimization.…”

Section: State Of the Art And Main Contributionsmentioning

confidence: 99%

“…We investigate two scenarios in this network. In the first scenario, we assume 1 Part of this paper has been published in [1].…”

Section: Introductionmentioning

confidence: 99%

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Energy and Social Cost Minimization for Data Dissemination in Wireless Networks: Centralized and Decentralized Approaches

Mousavi

Klein

2020

IEEE Trans. Veh. Technol.

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We study multi-hop data-dissemination in a wireless network from one source to multiple nodes where some of the nodes of the network act as re-transmitting nodes and help the source in data dissemination. In this network, we study two scenarios; i) the transmitting nodes do not need an incentive and ii) they do need an incentive and are paid by their corresponding receiving nodes by virtual tokens. We investigate two problems; P1) network power minimization for the first scenario and P2) social cost minimization for the second scenario, defined as the total cost paid by the nodes of the network for receiving data. In this paper, we propose centralized and decentralized approaches for each of the problems. The proposed decentralized approach is based on a non-cooperative cost-sharing game (CSG). In our proposed game, every receiving node chooses its respective transmitting nodes and consequently, a cost is assigned to it according to the power imposed on its chosen transmitting nodes. For the sake of energy efficiency, in our model, we employ maximal-ratio combining (MRC) at the receivers so that a receiver can be served by multiple transmitters. Moreover, besides the radio-link power, we capture the power required by the passive modules of wireless devices involved in reception/transmission. We discuss how the network is formed in a decentralized way, find the actions of the nodes in the game and show that the proposed game reaches a Nash equilibrium. To find the centralized global optimum, which is a benchmark to our decentralized approach, we use a mixed-integer-liner-program (MILP). The proposed MILP can be used for both of the problems P1 and P2 with a minor change. Simulation results show that our proposed decentralized approach outperforms the conventional algorithms in terms of energy efficiency and social cost while it can address the need for an incentive for collaboration. 1

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Mechanism Transitions in Publish/Subscribe Systems

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Multi-hop data dissemination with selfish nodes: Optimal decision and fair cost allocation based on the Shapley value

Cited by 6 publications

References 14 publications

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

Energy and Social Cost Minimization for Data Dissemination in Wireless Networks: Centralized and Decentralized Approaches

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