Multi-path utility maximization and multi-path TCP design

Vo, Phuong Luu; Lê, Tuấn Anh; Lee, Sungwon; Hong, Choong Seon; Kim, Byeongsik; Song, Hoyoung

doi:10.1016/j.jpdc.2013.07.005

Cited by 22 publications

(34 citation statements)

References 15 publications

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“…Moreover, it can be seen from these figures that subflow 1 of source 4 travels through link 2 and link 3, which have higher outage probability than those of link 4 and link 5. In addition, although dc-mNUM and mENUM yield the same level of injection rate, the effective rate and effective utility in dc-mNUM are much lower than those of mENUM because the lossy features of wireless links is not taken into consideration in [7] while it is examined in our work. We also illustrate the aggregate effective utility in Figure 2(c) where we can observe that the utility performance (i) is negative because we use the˛-fair utility function, which is negative as˛> 1 and (ii) can converge to the optimal solution for a reasonable number of iterations.…”

Section: Performance Of Multipath Effective Network Utility Maximizationmentioning

confidence: 99%

“…In addition, literature [16,17] proved that the concurrent multipath traffic impersonating can enlarge the network efficiency and communication privacy by dividing and transferring traffic via multiple paths. The authors in [7] first formulated a multipath mNUM problem, where multipaths with different characteristics are considered. The authors in [7] first formulated a multipath mNUM problem, where multipaths with different characteristics are considered.…”

Section: Introductionmentioning

confidence: 99%

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Network utility maximization in multipath lossy wireless networks

Pham

Hwang

2015

Int J Communication

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The end-to-end rate control in multipath wireless multihop networks has been widely studied so as to exploit path diversity and improve network performance. However, it has been recognized that the hop-by-hop congestion control is stable and spatially smoothed in the absence and presence of delay, respectively. As a result, we are motivated to consider the lossy features of wireless links and propose a novel utility maximization problem for multipath communication networks. In view of the fact that the considered optimization problem formulated as a multipath network utility maximization problem is in non-convex form and hard to tackle, we first cast the underlying problem into a convex one and then solve the convex approximation problem by the Lagrangian duality technique. What is more, an efficient hop-by-hop rate control algorithm is proposed. In addition, we prove that the proposed two-loop algorithm converges to the optimal solution satisfying the Karush-Kuhn-Tucker optimality conditions of the original optimization problem. We finally validate the effectiveness of the proposed algorithm through extensive simulations and compare the performance of the proposed algorithm with a hop-by-hop single-path rate control algorithm and also with an end-to-end multipath algorithm.of 18 § We can easily extend the current paper to the case where a joint problem of rate control and power allocation is considered. In particular, the objective function takes account of transmission power, and link SINR and rate outage probability are then functions of power allocation. of 18 ¶ The step-size sequence ı.t/ is required to satisfy the diminishing rule, that is, ı.t/ > 0, t D1 P t D1 ı.t/ 2 < 1, t D1 P t D1 ı.t/ D 1.

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Section: Performance Of Multipath Effective Network Utility Maximizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Network utility maximization in multipath lossy wireless networks

Pham

Hwang

2015

Int J Communication

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“…It has been agreed that using multipath could bring enhancements to the communication reliability, and more importantly, generally increase the available bandwidth for bandwidth-hungry multimedia applications. Recent attention has been turned to the cases in multipath networks, e.g., fair resource allocation for users [21][22][23][24], effective resource allocation for elastic services [25,26], multipath transmission algorithm design [27][28][29], congestion control for heterogeneous flows [30], and some interesting research results on optimal resource allocation in multipath scenarios are obtained. For example, in [30] a unified approach is proposed to optimize performance of heterogeneous flows when inelastic and elastic services both exist in multipath networks.…”

Section: Introductionmentioning

confidence: 99%

Resource allocation for multi-class services in multipath networks

Sun

Tian

2015

Performance Evaluation

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“…Then, Li et al [7] considered the integration of elastic and inelastic traffic at multiple levels, and developed a distributed joint load-balancing and congestion control algorithm to achieve the goal of maximizing the aggregate utility gained by the elastic flows while satisfying the fixed throughput and prioritization requirements of the inelastic flows. Recently, Vo et al [11] introduced a modified multi-path network utility maximization model to achieve congestion control and developed a series of multi-path Transmission Control Protocols (TCPs) that are compatible with corresponding regular single-path TCPs. Li et al [9] presented a distributed primal-dual algorithm for fair resource allocation in multipath networks and obtained some sufficient conditions for local stability of the algorithm in the presence of round-trip delays.…”

Section: Introductionmentioning

confidence: 99%

“…The investigation has concentrated primarily on optimizing objectives of longterm performance metrics such as throughput subject to network stability. Much of the existing work focuses on elastic traffic with controllable packet injection rates generated by file transfer or other applications (e.g., [8][9][10][11]). However, networks are recently seeing a major growth in realtime traffic (voice and video), which are inelastic.…”

Section: Introductionmentioning

confidence: 99%

Optimal resource allocation for heterogeneous traffic in multipath networks

Sun

Chen

2014

Int J Communication

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Multipath networks allow each source to send packets from it to its destination over multiple paths, which increases the available bandwidth and throughput for source-destination pairs. Recently, a variety of flow control schemes have been presented for multipath networks to achieve optimal resource allocation. Unfortunately, much of the investigation focused on elastic traffic with controllable packet injection rates. Networks have witnessed an increase in real-time traffic (voice and video), which are inelastic. We consider resource allocation for heterogeneous traffic in multipath networks and formulate an optimization problem, which is intrinsically difficult nonconvex. In order to address the aforementioned issue and obtain the optimum, we approximate an equivalent problem of the original optimization problem to a strictly convex problem and present a primal-dual resource allocation algorithm for the approximation problem, which converges to an optimal solution satisfying the Karush-Kuhn-Tucker conditions of the original problem. We evaluate its convergence performance through theoretical analysis and illustrate it with numerical examples.OPTIMAL RESOURCE ALLOCATION FOR HETEROGENEOUS TRAFFIC 85 a significant drop in the QoS. The resource allocation on these inelastic traffic has received much attention recently in single-path networks (e.g., [12][13][14]) but very little in multipath networks.Meanwhile, the coexistence of elastic and inelastic traffic has been widely investigated in singlepath wired networks [13][14][15][16] and interesting schemes for resource allocation have been presented. Furthermore, the integration of both elastic and inelastic traffic is also studied in single-hop wireless systems in [17][18][19]; however, with the restriction of every traffic having a single route. As using multipath could aggregate the bandwidth of the transmission paths between the communicating endpoints, multipath networks become a novel approach to improve the performance of increasingly bandwidth-hungry applications, such as real-time inelastic traffic [3]. Thus, it is very significant to study the coexistence of inelastic and elastic traffic in multipath networks and investigate optimal resource allocation for these traffic, so as to satisfy the QoS requirements of real-time traffic while achieving the objective of utility maximization.In this paper, we consider the integration of elastic and inelastic traffic in multipath networks, and investigate the optimal resource allocation for heterogeneous traffic based on the idea of multipath network utility maximization, which applies utility-based method from economics into the area of bandwidth allocation in multipath networks. We first formulate the resource allocation model for heterogeneous traffic that incorporates both elastic and inelastic traffic in multipath networks, which is an intrinsically difficult problem of nonconvex optimization. In order to obtain the optimum, we approximate an equivalent problem of the original optimization problem to a strictly ...

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Multi-path utility maximization and multi-path TCP design

Cited by 22 publications

References 15 publications

Network utility maximization in multipath lossy wireless networks

Network utility maximization in multipath lossy wireless networks

Resource allocation for multi-class services in multipath networks

Optimal resource allocation for heterogeneous traffic in multipath networks

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