Multiple User Cooperative Mobility in Mobile Ad Hoc Networks: An Interaction Position Game

Abstract

Mobile ad hoc networks (MANETs) have been widely used by individuals for residential or commercial usage in small-scale areas depending on fifth-generation (5G) and device-to-device (D2D) advancements. MANET demands extremely high system throughput, low latency, and best quality of service (QoS) maintenance. The current user mobility approaches only analyze the single movable user and use intuitive methods but cannot fundamentally solve multiple user cooperative mobility in practical applications. In this paper, we first jointly consider multiple user mobility and different geographical places and distances among all users. Then, we propose an interaction position game (IPG) to achieve high throughput and decrease computational cost. In this game, cooperative behaviors among movable users are proposed instead of assumed selfishness, as in traditional game models. In addition, we also present the simulated annealing (SA) algorithm to solve this NP-hard problem as a performance comparison. Finally, we evaluate the performance of this proposed game in various position cases. The results show that this game method improves the maximum throughput ratio evidently by 57.35% and 27.27% compared with the conventional intuitive method and SA algorithm, respectively. Compared with the exhaustive algorithm, this game reduces the computation cost by 82.79%. INDEX TERMS Mobile ad hoc networks, system throughput, multiple user cooperative mobility, interaction position game, cooperative behaviors, simulated annealing.

An Optimal Location Allocation by Multi-User Cooperative Mobility for Maximizing Throughput in MANETs

“…In our previous work [26], we proposed an interaction position game (IPG) and investigated the Spatial Adaptive Play (SAP) algorithm to work out the optimum. In this game, we employ cooperative behavior among movable nodes instead of assuming selfishness as the traditional game model.…”

“…In [26], our previous work proposed an interaction position game to achieve high throughput and decrease computation costs in the multiple user mobility systems. However, the method's completion time is also relatively long, and the communication overhead is so high that it is sometimes not efficient in the existing communication system.…”

“…However, it is a combinatorial optimization problem of exorbitant complexity considering mobility user locations' diversity and inter-user interference. Solving this optimization problem will result in a tradeoff between the accuracy of the best throughput performance and the allowed computation cost [26]. We deduce and propose an effective algorithm by analyzing the relationship between SINR, the location of movable nodes, and system throughput.…”

“…Hence, we should minimize the number of vertices that are not included in the adjacent DF links. Proposition 4: The range for D U satisfies inequality (26).…”

“…Finally, in phase 3 (line [25][26][27][28][29][30][31][32][33][34][35][36][37][38], with the search area slowly expanding, it compares old and new throughput values that are newly generated from optimal locations. If the new throughput is larger than the old value, it updates the optimal throughput and continues to expand the search range G, where we define ∆G as a per expansion area.…”