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The Distributed Constraint Optimization Problem (DCOP) is a major and powerful paradigm for modeling and solving problems in multiagent coordination. AFB BJ + is one of the most excellent algorithms for solving DCOPs. Recently, researchers have shown that including soft arc consistency (AC * ) in DCOP algorithms causes significant improvements in their performance. In this paper, we introduce AFB BJ + -AC * algorithm which connects AFB BJ + with soft arc consistency (AC * ). It relies on pruning non-optimal values of an agent domain, using AC * , and propagating them, without adding other types of messages, for generating other deletions that will likewise be propagated. Our experimental analysis on several benchmarks shows that thanks to AC * , AFB BJ + -AC * improves the basic AFB BJ + .

Coupling cellular communication networks with vehicular ad hoc networks (VANET) can be a very interesting way out for providing Internet access to vehicles in the road. However, due to the several specific characteristics of VANETs, making an efficient multi-hop routing from vehicular sources to the Internet gateways through Long Term Evolution (LTE) technology is still challenging. In this paper, an Internet mobile gateway selection scheme is proposed to elect more potential vehicles to behave as gateways to Internet in VANETs. Therefore, the discovery and the selection of route to those mobiles gateways is carried out via an efficient multiple metrics-based relay selection mechanism. The objective is to select the more reliable route to the mobile gateways, by reducing the communication overhead and performing seamless handover. The proposed protocol is compared with one recent protocol based on packet delivery ratio, average end-to-end delay and overhead. The results show that the proposed protocol ameliorates significantly the network performance in the contrast of the other protocol.

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The AFB_BJ + -AC * algorithm is one of the latest algorithms used to solve Distributed Constraint Optimization Problems (DCOPs). It is based on simple arc consistency (AC * ) to speed up the process of solving a problem by permanently removing any value that doesn't belong to its optimal solution. In this paper, we use a directional arc consistency (DAC * ), the next higher level of AC * , to erase more values and thus to quickly reach the optimal solution of a problem. Experiments on some benchmarks show that the new algorithm, AFB_BJ + -DAC * , is better in terms of communication load and computation effort.

The AFB BJ + DAC * is the latest variant of asynchronous forward bounding algorithms used to solve Distributed Constraint Optimization Problems (DCOPs). It uses Directional Arc Consistency (DAC * ) to remove, from domains of a given DCOP, values that do not belong to its optimal solution. However, in some cases, DAC * does not remove all suboptimal values, which causes more unnecessary research to reach the optimal solution. In this paper, to clear more and more suboptimal values from a DCOP, we use a higher level of DAC * called Full Directional Arc Consistency (FDAC * ). This level is based on reapplying AC * several times, which gives the possibility of making more deletions and thus quickly reaching the optimal solution. Experiments on some benchmarks show that the new algorithm, AFB BJ + FDAC * , is better in terms of communication load and computation effort.