“…Then the genetic algorithm is used to optimize the scheduling results in the first stage. Communication and calculation methods are proposed in the literature [5]. The algorithm realizes the real-time statistics of system running time and data sending time by offline method.…”
INTRODUCTION: In this paper, a scheduling algorithm for heterogeneous systems based on prioritization (PQDSA) is proposed. This algorithm is a sort method based on directed acyclic graph (DAG). The key nodes in the network are grouped according to the communication and computing costs in the network. This increases the parallelism between task schedules and reduces the completion time of work sets. Then, a method of assigning multiple tasks to multiple processors using interpolation is proposed. The PQDSA method can effectively reduce the time of scheduling multiple tasks and improve the scheduling effect. PQDSA is compared with EDL-θ and EDF scheduling methods. The results show that this method has better scheduling efficiency.
“…Then the genetic algorithm is used to optimize the scheduling results in the first stage. Communication and calculation methods are proposed in the literature [5]. The algorithm realizes the real-time statistics of system running time and data sending time by offline method.…”
INTRODUCTION: In this paper, a scheduling algorithm for heterogeneous systems based on prioritization (PQDSA) is proposed. This algorithm is a sort method based on directed acyclic graph (DAG). The key nodes in the network are grouped according to the communication and computing costs in the network. This increases the parallelism between task schedules and reduces the completion time of work sets. Then, a method of assigning multiple tasks to multiple processors using interpolation is proposed. The PQDSA method can effectively reduce the time of scheduling multiple tasks and improve the scheduling effect. PQDSA is compared with EDL-θ and EDF scheduling methods. The results show that this method has better scheduling efficiency.
“…The success of stigmergy in natural systems is an inspiration for the design of artificial systems that must act in large, unpredictable, and hazardous environments [13]. In swarm robotics, for example, stigmergy inspired by ants trails and termite mounds has found a wide variety of applications, including exploration and path planning [18,21,24], task allocation [10], foraging [8,12], and construction [2,30].…”
Ants have evolved to seek and retrieve food by leaving trails of pheromones. This mechanism has inspired several approaches to decentralized multi-robot coordination. However, in this paper, we show that pheromone trails are a fragile mechanism for coordination, and can be sabotaged to starve the colony. We introduce detractors: malicious agents that leave a misleading, but indistinguishable, trail of food pheromone to distract and trap cooperator ants in the nest. We analyze the effectiveness of detractors with respect to parameters such as evaporation rate of misleading pheromone and fraction of detractors in the colony. In addition, we propose a countermeasure to this attack by introducing a new type of pheromone: the cautionary pheromone. Cooperator ants secrete this type of pheromone atop existing food trails as a warning. When the cautionary pheromone intensity exceeds the food pheromone intensity, cooperator ants ignore overlapping food pheromone. We show that, despite its simplicity, this defense mechanism can limit, but not nullify, the effect of detractors. Ultimately, our work shows that pheromone-based coordination, while effective, is also fragile.
CCS CONCEPTS• Computing methodologies → Distributed artificial intelligence; Multi-agent systems; Intelligent agents; Mobile agents.
“…Summary of resources as the enablers from selected articles. ,15,37,38,40,41,47,46,45,43,53,52,50,49,54,62,61,60,59,58,57,56,64,69,68,67,66,65,70,71,73,74,78,80,[82][83][84][85][86][87] …”
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