群智感知网络中的防御任务分配策略
Defense Task Allocation Strategy in Swarm Intelligence Sensing Networks

在群智感知网络中，当执行由多个计算密集型任务组成的防御任务时，多个感知节点之间的合作是必要的。这一领域的大部分以前的工作都集中在节能和负载平衡上。然而，这些方案仅仅考虑了只需要一种资源的情况，这大大限制了它们的实际应用。为了减轻这种限制，在本文中，我们研究了复杂防御任务分配的问题，其中需要各种不同类型的资源。提出了一种基于启发式的算法来分配复杂的应用在群智感知网络。该算法分为两个阶段，在联盟间分配阶段，将防御任务的任务分配到各个联盟，以降低能耗；在联盟内分配阶段，将任务分配到适当的感知节点，兼顾能量成本和工作负载平衡。这样可以减少和平衡能量耗散，延长系统的使用寿命。
In swarm intelligence sensing networks, when performing defense tasks composed of multiple compute intensive tasks, cooperation among multiple sensing nodes is necessary. Most of the previous work in this field focused on energy conservation and load balancing. However, these schemes only consider the situation that only one resource is needed, which greatly limits their practical application. In order to alleviate this limitation, in this paper, we study the problem of complex defense task allocation, which requires various types of resources. A heuristic algorithm is proposed to allocate complex applications in swarm intelligence sensing networks. The algorithm is divided into two stages. In the inter alliance allocation stage, defense tasks are allocated to each alliance to reduce energy consumption; in the allocation phase of the alliance, tasks are allocated to appropriate sensing nodes, taking into account the energy cost and workload balance. This can reduce and balance energy dissipation and prolong the service life of the system.