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A Wireless Sensors Network (WSN) is an ad-hoc network populated by small hand-held commodity devices, running on batteries called stations or sensors. Often used in hostiles and sometimes unreachable environments, stations are subject to energetic constraints which can significantly decrease the network life time. Permutation routing problem is mainly found in the literature of WSN. This problem occurs when some stations have items that belong either or not to them. The goal is to send each item to its receiver. To solve this problem, several works are presented in the literature. In this paper, we present a new permutation routing protocol for multi-hop wireless sensors network that, compared to recent work in the field is more efficient in terms of conservation of sensors' energy, which results in a longer life time of the network. Also, contrary to some other routing protocols which assume that the memory of the sensors is infinite, we show that the memory size of the sensors is limited, which in our opinion is more realistic.

Patrolling an environment involves a team of agents whose goal usually consists in continuously visiting its most relevant areas as frequently as possible. Hence, patrolling consists in continuously visiting relevant areas of an environment, in order to efficiently surpervise or control it. The Ant Colony Optimization (ACO) is adopted as the solution approach that efficiently solves the multiagent patrolling problem. Two stratagies are employed: all agents are located on the same node at the initial time, and the agents are dispersed over the graph, they start to patrol from their new locations. This paper mainly describes the formulation problem of event detection by a multi-objective approach, an ACO and multi-agent approach are used to model and simulate the detection of events. Different parameters are evaluated in order to minimize them. The minimization of Worst Idleness, Energy consumption and Communicational Idleness are not compatible. It is therefore necessary to seek compromise solutions. The set of compromise solutions is called Pareto Front. The set of solutions and Pareto Front are presented respectively for the cases of non-dispersion and dispersion of agents.

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