A game-theoretic multipath routing for video-streaming services over Mobile Ad Hoc Networks

Igartua, Mónica Aguilar; Llopis, Luis J. de la Cruz; Frias, V.C.; Gargallo, Emilio Sanvicente

doi:10.1016/j.comnet.2011.06.007

Cited by 14 publications

(8 citation statements)

References 29 publications

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“…In the method, multiple metrics (e.g., delay, bandwidth, hop count, and packet loss) in a path are considered as a vague set, and the vague values are partitioned into seven fuzzy levels. Then, in literature [12], a multipath routing protocol is proposed to select the routing path dynamically with a game theory for each source-destination pair. Then, according to the preference of the path metrics, an ideal best path and an ideal worst path can be obtained.…”

Section: Related Workmentioning

confidence: 99%

“…Generally, through appropriately selecting their routing path according to the path quality, for example, the load level, the QoS, and the delay, each source-destination pair can improve their transmission performances (e.g., transmission efficiency [4] and load balancing [5]). Recently, some popular theories including fuzzy logic [10], multi-objective optimization [11], and game theory [12] have been applied to the path selection.…”

Section: Related Workmentioning

confidence: 99%

“…And the mutation operation can change the sub-path randomly to make the solution escape from the local optimization. Then, in literature [12], a multipath routing protocol is proposed to select the routing path dynamically with a game theory for each source-destination pair. In the protocol, not only the paths between the source and destination are classified as the different levels according to the path metrics (e.g., packet loss), but also the traffic is classified as the difference levels according to their importance.…”

Section: Related Workmentioning

confidence: 99%

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A bio‐inspired OSPF path selection scheme based on an adaptive attractor selection model

Gong

Yang

Zhang

et al. 2015

Int J Communication

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Current Internet Protocol routers only support equal cost multi-path routing, which performs the random path selection or the traffic uniform distribution among equal-cost paths. In biology, an adaptive attractor selection model is presented to simulate the concentration changes of two kinds of Escherichia coli's mRNA in changing nutrition environments with bistability equations. Inspired by the metabolism behaviors of E. coli, we propose an adaptive path selection scheme Open Shortest Path First-path selection by attractor selection to dynamically select the transmission path by the real-time path quality. Here, the mRNA concentration is analogous to the path quality. Then, to reflect the multipath quality, multi-stability equations are adopted and redesigned. Our scheme consists of two main features. The first one is a redefined path-activity to indicate multipath transmission goodness, which is inversely proportional to the offset between current path quality and best path quality. And the second one is a new attractor expression of the multi-stability equations to concretely specify the effect of a stochastic item noise in the equations on the path selection. Compared with the greedy selection and the uniform random selection in file transfer protocol (FTP) service, our scheme gains better performance on reducing file transmission time, traffic throughput, and traffic dropped.the adaptive attractor selection model [8] is introduced into the field of the computer networks to optimize the multipath traffic transmission.Originally, the attractor selection model [9] is proposed to simulate the metabolism behaviors of the Escherichia coli in the dynamic nutrition environments with the revised bistability equations. In nature, each individual E. coli always regulates adaptively its own state in the different nutrition environments. When nutrition is adequate, the metabolism of the E. coli becomes vigorous generally. Then, the mRNA concentrations in the E. coli greatly increase to produce enough nutrition materials for growth and reproduction. Furthermore, the vigorous state will be kept if nutrition is adequate. Subsequently, when nutrition is inadequate, the metabolism of the E. coli is weak. Then, the mRNA concentrations inevitably decrease. Moreover, the concentrations are able to change stochastically to make the E. coli shift to a suitable metabolism state in the current nutrition environment [9]. Mathematically, this adaptation process of the E. coli to the changing nutrition environments can be modeled by the bistability equations, in which each attractor formulates a stable adaptation state of the mRNA concentrations.There are two key parameters in the bistability equations. One is called activity, which indicates the adaptation goodness of the E. coli to the nutrition environment. And the other one is noise, which takes the stochastic effect on the mRNA concentrations. The two parameters have a relation of ebb and flow. When the activity increases, the stochastic effect of the noise on the mRNA concentrati...

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A bio‐inspired OSPF path selection scheme based on an adaptive attractor selection model

Gong

Yang

Zhang

et al. 2015

Int J Communication

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“…They observed that the characteristics of ad-hoc wireless networks such as of not having central coordination, mobility of hosts, and limited availability of resources made QoS provisioning very challenging. M. A. Igartua et al [24] proposed g-MMDSR a game theoretic-Multipath Multimedia Dynamic Source Routing, which was a cross-layer multipath routing protocol and utilized game theory to achieve a dynamic selection of the forwarding paths. The proposed g-MMDSR was an extension to DSR (Dynamic Source Routing).…”

Section: Related Workmentioning

confidence: 99%

Quality of Service Issues for Reinforcement Learning Based Routing Algorithm for Ad-Hoc Networks

Kulkarni¹,

Rao²

2012

CIT

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Mobile ad-hoc networks are dynamic networks which are decentralized and autonomous in nature. Many routing algorithms have been proposed for these dynamic networks. It is an important problem to model Quality of Service requirements on these types of algorithms which traditionally have certain limitations. To model this scenario we have considered a reinforcement learning algorithm SAMPLE. SAMPLE promises to deal effectively with congestion and under high traffic load. As it is natural for ad-hoc networks to move in groups, we have considered the various group mobility models. The Pursue Mobility Model with its superior mobility metrics exhibits better performance. At the data link layer we have considered IEEE 802.11e, a MAC layer which has provisions to support QoS. As mobile ad-hoc networks are constrained by resources like energy and bandwidth, it is imperative for them to cooperate in a reasonably selfish manner. Thus, in this paper we propose cooperation with a moderately punishing algorithm based on game theory. The proposed algorithm in synchronization with SAMPLE yields better results on IEEE 802.11e.

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“…Meanwhile, neighbors may choose not to send a reply due to the neighbors' own selfishness. To solve this problem, we use a Data Exchanging Dilemma Game (DEDG) mechanism based on Game Theory [19][20][21].…”

Section: Dedgmentioning

confidence: 99%

An Efficient Downloading Service of Large Popular Files in VANET Based on 802.11p Protocol

Zhao

Qin

Cheng

2015

International Journal of Distributed Sensor Networks

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With the improvement of technology and the increasing demand for convenience and comfort, new interests have emerged in commercial and entertainment service in VANET. The downloading service of large popular files has played a crucial role for those commercial and entertainment service application. In this paper the author proposed an efficient scheme to help vehicle nodes download the large popular files from the Road Side Unit (RSU). Due to the constraint density of RSU and high mobility of vehicle nodes, vehicle nodes cannot download the whole large files from RSU before they move out of the communication range. To deal with this problem, we proposed multiple access modes downloading schemes: vehicles download files from RSU directly, vehicles download files through relay vehicles, and vehicles download files through other vehicles. We give credit-based incentives for relay vehicle selection to guarantee the stability and quality of the link bandwidth. We also proposed a game theory-based way to control number of neighbors reply packets, which does not cost additional bandwidth resource and ensure integrity of the files. Finally, simulations show that our proposed schemes performed well in high mobility VANET environment and ensure the data integrity.

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A game-theoretic multipath routing for video-streaming services over Mobile Ad Hoc Networks

Cited by 14 publications

References 29 publications

A bio‐inspired OSPF path selection scheme based on an adaptive attractor selection model

A bio‐inspired OSPF path selection scheme based on an adaptive attractor selection model

Quality of Service Issues for Reinforcement Learning Based Routing Algorithm for Ad-Hoc Networks

An Efficient Downloading Service of Large Popular Files in VANET Based on 802.11p Protocol

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