task allocation concerning Unmanned Aerial Vehicle(UAV) swarms, characterized by behavioral self-organization and autonomic decision-making, is a popular term in civil and military areas. At the present time most task...
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task allocation concerning Unmanned Aerial Vehicle(UAV) swarms, characterized by behavioral self-organization and autonomic decision-making, is a popular term in civil and military areas. At the present time most task allocation algorithms are quadratic or linear, in view of this situation we establishes a new decision-making model with an integer convex optimization based on the distributed task assignment problem of UAV swarms in a confrontation environment. A distributed task event-triggered decision rule is set up, and a distributed optimal task assignment algorithm based on information consistency is proposed. Simulation verification is carried out for the three strike requirements. The results show that the method can achieve global consistency convergence while reducing the communication interaction, obtain targets optimal distribution scheme and satisfy information consistency. The target allocation approach can effectively improve the combat effectiveness of the UAV swarm.
This paper introduces a new communication abstraction, called Set-Constrained Delivery Broadcast (SCD-broadcast), whose aim is to provide its users with an appropriate abstraction level when they have to implement obj...
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This paper introduces a new communication abstraction, called Set-Constrained Delivery Broadcast (SCD-broadcast), whose aim is to provide its users with an appropriate abstraction level when they have to implement objects or distributed tasks in an asynchronous message-passing system prone to process crash failures. This abstraction allows each process to broadcast messages and deliver a sequence of sets of messages in such a way that, if a process delivers a set of messages including a message m and later delivers a set of messages including a message in', no process delivers first a set of messages including in' and later a set of message including m. After having presented an algorithm implementing SCD-broadcast, the paper investigates its programming power and its computability limits. On the "power" side it presents SCD-broadcast-based algorithms, which are both simple and efficient, building objects (such as snapshot and conflict-free replicated data types), and distributed tasks. On the "computability limits" side it shows that SCD-broadcast and read/write registers are computationally equivalent. (C) 2021 Elsevier B.V. All rights reserved.
tasks and objects are two predominant ways of specifying distributed problems where processes should compute outputs based on their inputs. Roughly speaking, a task specifies, for each set of processes and each possib...
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tasks and objects are two predominant ways of specifying distributed problems where processes should compute outputs based on their inputs. Roughly speaking, a task specifies, for each set of processes and each possible assignment of input values, their valid outputs. In contrast, an object is defined by a sequential specification. Also, an object can be invoked multiple times by each process, while a task is a one-shot problem. Each one requires its own implementation notion, stating when an execution satisfies the specification. For objects, linearizability is commonly used, while tasks implementation notions are less explored. The article introduces the notion of interval-sequential object, and the corresponding implementation notion of interval-linearizability, to encompass many problems that have no sequential specification as objects. It is shown that interval-sequential specifications are local, namely, one can consider interval-linearizable object implementations in isolation and compose them for free, without sacrificing interval-linearizability of the whole system. The article also introduces the notion of refined tasks and its corresponding satisfiability notion. In contrast to a task, a refined task can be invoked multiple times by each process. Also, objects that cannot be defined using tasks can be defined using refined tasks. In fact, a main result of the article is th at interval-sequential objects and refined tasks have the same expressive power and both are complete in the sense that they are able to specify any prefix-closed set of well-formed executions. Interval-linearizability and refined tasks go beyond unifying objects and tasks;they shed new light on both of them. On the one hand, interval-linearizability brings to task the following benefits: an explicit operational semantics, a more precise implementation notion, a notion of state, and a locality property. On the other hand, refined tasks open new possibilities of applying topological tech
This paper introduces a new communication abstraction, called Set-Constrained Delivery Broadcast (SCD-broadcast), whose aim is to provide its users with an appropriate abstraction level when they have to implement obj...
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ISBN:
(纸本)9781450363723
This paper introduces a new communication abstraction, called Set-Constrained Delivery Broadcast (SCD-broadcast), whose aim is to provide its users with an appropriate abstraction level when they have to implement objects or distributed tasks in an asynchronous message-passing system prone to process crash failures. This abstraction allows each process to broadcast messages and deliver a sequence of sets of messages in such a way that, if a process delivers a set of messages including a message m and later delivers a set of messages including a message m', no process delivers first a set of messages including m' and later a set of message including m. After having presented an algorithm implementing SCD-broadcast, the paper investigates its programming power and its computability limits. On the "power" side it presents SCD-broadcast-based algorithms, which are both simple and efficient, building objects (such as snapshot and conflict-free replicated data), and distributed tasks. On the "computability limits" side it shows that SCD-broadcast and read/write registers are computationally equivalent.
Swarm intelligence principles have been widely studied and applied to a number of different tasks where a group of autonomous robots is used to solve a problem with a distributed approach, i.e. without central coordin...
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Swarm intelligence principles have been widely studied and applied to a number of different tasks where a group of autonomous robots is used to solve a problem with a distributed approach, i.e. without central coordination. A survey of such tasks is presented, illustrating various algorithms that have been used to tackle the challenges imposed by each task. Aggregation, flocking, foraging, object clustering and sorting, navigation, path formation, deployment, collaborative manipulation and task allocation problems are described in detail, and a high-level overview is provided for other swarm robotics tasks. For each of the main tasks, (1) swarm design methods are identified, (2) past works are divided in task-specific categories, and (3) mathematical models and performance metrics are described. Consistently the swarm intelligence paradigm, the main focus is on studies characterized by distributed control, simplicity of individual robots and locality of sensing and communication. distributed algorithms are shown to bring cooperation between agents, obtained in various forms and often without explicitly programming a cooperative behavior in the single robot controllers. Offline and online learning approaches are described, and some examples of past works utilizing these approaches are reviewed. (C) 2015 Elsevier B.V. All rights reserved.
In the information construction risk management, traditional risk analysis methods define risk analysis scope according to physical or logical entities, which neglects the risks that leading to conflict between the su...
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ISBN:
(纸本)9780646480930
In the information construction risk management, traditional risk analysis methods define risk analysis scope according to physical or logical entities, which neglects the risks that leading to conflict between the subtasks of information project. This paper, basing on distributed task cooperative mode of information construction, considering the risk influence between the information construction subtasks, analyzes and infers information construction risk factors with the method of Bayesian network. The example proofs that it can be effectively identify the threat factors in information construction and offers scientific reference to the risk management of information construction.
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