Distributed Network Formation Strategy for Network Coding Based Wireless Networks

Kwon, Minhae; Park, Hyunggon

doi:10.1109/lsp.2017.2670645

Cited by 9 publications

(6 citation statements)

References 26 publications

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“…Even though network coding can reduce complexity in general, it is known that finding an optimal solution in network coding with multiple multicasts is an NP-hard problem [20]. Hence, suboptimal but practical solutions are often studied [21], [22]. A well-known practical solution to network formation is proposed based on linear optimization in [21].…”

Section: Related Workmentioning

confidence: 99%

“…Hence, Perron-Frobenius theorem [46] guarantees that there is a unique largest eigenvalue and the largest eigenvalue is 1 since P is a stochastic matrix. Therefore, the unique limiting distribution σ can be found as a row eigenvector of P associated with eigenvalue 1, i.e., σP = σ, and the initial state becomes the state with the largest limiting distribution as shown in (22). The initialization phase of the proposed system can be expedited by choosing the initial state of each node that leads to the initial network.…”

Section: Optimal Action Includes Change Of Transmission Rangementioning

confidence: 99%

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Network Coding Based Evolutionary Network Formation for Dynamic Wireless Networks

Kwon¹,

Park²

2019

IEEE Trans. on Mobile Comput.

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In this paper, we aim to find a robust network formation strategy that can adaptively evolve the network topology against network dynamics in a distributed manner. We consider a network coding deployed wireless ad hoc network where source nodes are connected to terminal nodes with the help of intermediate nodes. We show that mixing operations in network coding can induce packet anonymity that allows the inter-connections in a network to be decoupled. This enables each intermediate node to consider complex network inter-connections as a node-environment interaction such that the Markov decision process (MDP) can be employed at each intermediate node. The optimal policy that can be obtained by solving the MDP provides each node with optimal amount of changes in transmission range given network dynamics (e.g., the number of nodes in the range and channel condition). Hence, the network can be adaptively and optimally evolved by responding to the network dynamics. The proposed strategy is used to maximize long-term utility, which is achieved by considering both current network conditions and future network dynamics. We define the utility of an action to include network throughput gain and the cost of transmission power. We show that the resulting network of the proposed strategy eventually converges to stationary networks, which maintain the states of the nodes. Moreover, we propose to determine initial transmission ranges and initial network topology that can expedite the convergence of the proposed algorithm. Our simulation results confirm that the proposed strategy builds a network which adaptively changes its topology in the presence of network dynamics. Moreover, the proposed strategy outperforms existing strategies in terms of system goodput and successful connectivity ratio.

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Section: Related Workmentioning

confidence: 99%

Section: Optimal Action Includes Change Of Transmission Rangementioning

confidence: 99%

Network Coding Based Evolutionary Network Formation for Dynamic Wireless Networks

Kwon¹,

Park²

2019

IEEE Trans. on Mobile Comput.

Self Cite

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show abstract

“…The network formation game for a graph can be decomposed by network coding into independent games for edge-disjoint subgraphs. 13 There can be maximum`N V 2˘e dge-disjoint subgraphs in G as each link with two nodes becomes a subgraph of G. Hence, it is always possible to decompose G into edge-disjoint subgraphs.…”

Section: Network Coding Based Game Decompositionmentioning

confidence: 99%

“…We define edge-disjoint subgraphs of G as a set of subgraphs whose links are disjointed and the union of them is G 13 . Specifically, for N edge-disjoint subgraphs L 1 , .…”

Section: Network Coding Based Game Decompositionmentioning

confidence: 99%

“…Another challenge in the considered large-scale sensor networks comes from multi-source multicast flows, which are inevitable in ad hoc networks [12,13]. Multiple sources can be included in the network because sensor nodes can generate data based on their own sensing operations and deliver information to a set of target destination nodes, resulting in multicast flows in the network.…”

Section: Introductionmentioning

confidence: 99%

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