针对无线传感器网络任务调度的实时性及节点计算及能量受限的特点，根据任务截止期赋予任务优先级，优先考虑高优先级任务，设计了一个无线传感器网络中带复杂联盟的自适应任务分配算法。为尽最大努力确保任务在截止期前完成，对截止期较为紧迫的任务采用历史信息生成历史联盟，并执行快速子任务分配算法；而对截止期较为宽裕的任务，在满足任务截止期约束条件下，以节点能耗和网络能量分布平衡为优化目标，采用矩阵的二进制编码形式，设计了一种离散粒子群优化算法以并行生成联盟，并执行基于负载和能量平衡的子任务分配算法。仿真实验结果表明所构造的自适应算法是有效的，在局部求解与全局探索之间能够取得较好的平衡，并能够在较短的时间内取得满意解。%Considering the real-time requirement and some specific limitations (e.g. insufficient computing resource, energy constraint, etc) in task scheduling of wireless sensor networks, different priorities were assigned to tasks according to their deadline, and an adaptive task allocation algorithm with complicated coalition was designed through analyzing historical information. Moreover, a discrete particle swarm optimization algorithm was designed via employing binary matrix coding form. The proposed optimization algorithm generates coalitions in parallel and then performs subtask allo-cation algorithm based on load and energy balance. Finally, the experimental results show that the proposed algorithm strikes a good balance between local solution and global exploration, and achieves a satisfactory result within a short pe-riod of time.
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