A randomized algorithm and performance bounds for coded cooperative data exchange

Sprintson, Alex; Sadeghi, Parastoo; Booker, Graham; Rouayheb, Salim El

doi:10.1109/isit.2010.5513313

Cited by 79 publications

(139 citation statements)

References 7 publications

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“…More analyses based on the simulation results are discussed in the following section. In the simulation, to evaluate the performance of CACM, we compare it with existing algorithms, such as Random [23], BitTorrent [24], Random+LoadBalance, and BitTorrent+LoadBalance [25].…”

Section: Results Analysis and Discussionmentioning

confidence: 99%

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Liu¹,

Yang²,

Guan³

et al. 2017

JESTR

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Complex computational tasks, such as topology construction and neighbor selection, which affect the file download efficiency in mobile peer-to-peer (MP2P) networks, are difficult to perform given the limited performance of mobile nodes. Thus, a cloud-assisted cooperative mechanism (CACM) for file download was proposed in this study to address this problem. The CACM aimed to construct a stable network topology based on the improved ant colony optimization algorithm and select appropriate neighbor nodes by adopting multiple strategies in the download process. Moreover, the main computational tasks were offloaded from the mobile nodes to the cloud server. Simulation results indicate that the file download efficiency of the CACM is close to that of BitTorrent in the first download stage, and CACM performs better at the second stage. In addition, the average download time of the CACM is reduced by at least 5% compared with BitTorrent, and its performance remains unchanged with the expansion of the network scale. The finding in this study proves that the research of CACM is crucial in improving the file download efficiency in MP2P networks.

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Section: Results Analysis and Discussionmentioning

confidence: 99%

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Liu¹,

Yang²,

Guan³

et al. 2017

JESTR

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“…Each user knows a subset of the frame and wants all the remaining packets he is missing. Soon after the introduction of this problem, NC community become applying coding technique [161,162,163,164,165] to improve the system performance. Using a network information flow formulation, the problem of minimizing the throughput (i.e.…”

Section: Trade-off Of Completion Time and Decoding Delaymentioning

confidence: 99%

“…The notable difference is that there is no BS and the users exchanging information by broadcasting packets (possibly network coded packets). In [165], Sprintson et al proposed a randomized polynomial-time solution to minimize the number of transmission in the DX problem. In [171] a deterministic polynomial time solution was proposed.…”

Section: Trade-off Of Completion Time and Decoding Delaymentioning

confidence: 99%

Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications

Douik

Sorour

Al-Naffouri

et al. 2017

IEEE Commun. Surv. Tutorials

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Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications Ahmed DouikFrom its introduction to its quindecennial, network coding has built a strong reputation in enhancing the packet recovery process and achieving maximum information flow in both wired and wireless networks. Traditional studies focused on optimizing the throughput of the network by proposing complex schemes that achieve optimal delay. With the shift toward distributed computing on mobile devices, throughput and complexity become both critical factors that affect the efficiency of a coding scheme. Instantly decodable network coding imposed itself as a new paradigm in network coding that trades off these two aspects. This paper presents a survey of instantly decodable network coding schemes that are proposed in the literature. The various schemes are identified, categorized and evaluated. Two categories can be distinguished namely the conventional centralized schemes and the distributed or cooperative schemes. For each scheme, the comparison is carried out in terms of reliability, performance, complexity and packet selection methodology. Although the performance is generally inversely proportional to the computation complexity, numerous successful schemes from both the performance and complexity viewpoint are identified.

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“…Although the number of constraints grows exponentially with the number of nodes, this integer linear program can be solved by polynomial-time algorithms due to the submodularity of the constraints. A randomized algorithm was proposed to estimate the minimum number of required transmissions [5]. Deterministic algorithms based on Dilworth Truncation optimization were proposed to compute the exact minimum number of required transmissions [3], [4], [6].…”

Section: A Related Workmentioning

confidence: 99%

Cooperative data exchange with weighted cost based on d-basis construction

Shah

Gastpar

2017

2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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Abstract-We consider the cooperative data exchange problem, in which nodes are fully connected with each other. Each node initially only has a subset of the K packets making up a file and wants to recover the whole file. Node i can make a broadcast transmission, which incurs cost wi and is received by all other nodes. The goal is to minimize the total cost of transmissions that all nodes have to send, which is also called weighted cost. Following the same idea of our previous work [1] which provided a method based on dBasis construction to solve cooperative data exchange problem without weighted cost, we present a modified method to solve cooperative data exchange problem with weighted cost. We present a polynomial-time deterministic algorithm to compute the minimum weighted cost and determine the rate vector and the packets that should be used to generate each transmission. By leveraging the connection to Maximum Distance Separable codes, the coefficients of linear combinations of the optimal coding scheme can be efficiently generated. Our algorithm has significantly lower complexity than the state of the art. In particular, we prove that the minimum weighted cost function is a convex function of the total number of transmissions for integer rate cases.

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A randomized algorithm and performance bounds for coded cooperative data exchange

Cited by 79 publications

References 7 publications

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Cloud-Assisted Cooperative Mechanism for File Download in Mobile Peer-to-Peer Networks

Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications

Cooperative data exchange with weighted cost based on d-basis construction

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