A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks

Abstract

The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc.) could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers) rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs) has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.

Figure 1

MPEG-2 GoP structure.

Figure 2

Multipath routing scheme using three paths.

Figure 3

PM and PMR packets.

Figure 4

Proposed framework to send the video frames.

Figure 5

Three possible allocation situations after playing the game. F and M represent the number of (I+P) and B frames to be sent, respectively. All the B frames are always sent through the worst path. (a) All the I+P frames are sent through the best path; (b) All the I+P frames are sent through the medium-quality path; (c) I+P frames will be sent through the best path with a certain probability p and through the second best path with a probability 1-p. F₁ and F₂ represent the number of (I+P) frames sent through the best path and the medium-quality path, respectively, being F = F₁ + F₂.

Figure 6

Subjective video quality measured by means of the mean opinion score (MOS) as a function of the fraction of packet losses (FPL).

Figure 7

Best response probability $p_i^{*}$ as a function of k_b/m, see Equation (26).

Figure 8

Average percentage of packet losses.

Figure 9

Percentage of packet losses vs time (N = 3 users).

Figure 10

Average end-to-end packet delay.

Figure 11

Delay jitter through the best path.

Figure 12

Delay jitter through the medium-quality path.

Figure 13

Peak Signal to Noise Ratio (PSNR).

Figure 14

Gain in terms of packet losses for I and P video frames using the game-theoretical scheme with respect to not using it.

Figure 15

Utility function graph for player 1 and 2. (a) Player 1; (b) Player 2.

Figure 16

Behaviour of $p_i^{*}$ as the fraction of packet losses (FPL) through the medium-quality path (FPL_m) increases. Here the FPL through the best path remains constant.

Figure 17

Behaviour of $p_i^{*}$ as the fraction of packet losses (FPL) through the best path (FPL_b) increases. Here the FPL through the medium-quality path remains constant.

Figure 18

Simulation scenario of Barcelona, Spain (N = 2 users). It includes two emergency units: AP1 (Ana Torres surgery clinic) and AP2 (Hospital Clinic of Barcelona).

Figure 19

Simulation results for N = 2 users. (a) Average percentage of packet losses; (b) Average end-to-end packet delay; (c) Average delay jitter.