NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing

Abstract

In the edge environment, the multiobjective evolutionary algorithm based on decomposition (MOEA/D) has been widely used in the research of multitarget firepower resource allocation. However, as the MOEA/D algorithm uses a fixed neighborhood update mechanism, it is impossible to rationally allocate computing resources based on the difficulty of each subproblem optimization, which results in some problems such as reduced population evolution efficiency and poor evolution quality during the calculation process. In order to solve these problems, a decision mechanism for subproblems and population evolution stages is designed, and on this basis, a MOEA/D algorithm based on the neighborhood adaptive adjustment mechanism is proposed to adapt to the edge environment. The optimization model of multiobjective firepower resource allocation based on the maximization of damage effect and the minimization of strike cost is constructed and solved. Using the ZDT series of test functions for comparative experiments, the simulation results show that the proposed algorithm can balance the distribution and convergence of population evolution and obtain satisfactory optimization results.

Attack‐defense differential game to strength allocation strategies generation

“…These two factors have a multiplicative effect on the global confrontation system. 34 Electronic jamming affects not only the opponent's electronics equipment, but also the opponent's C 4 ISR systems, which can have emergent effects on larger, higher-level systems, exponential arithmetic is required. 34…”

“…1 For example, designing strength allocation strategies to guarantee high confrontation effectiveness was discussed for forces allocation, 2 weapon targets assignment, 3 firepower allocation. 4 For a conventional confrontation system with a single adversary and no complex factors other than attrition rate, the classic linear programming is available for achieving strength allocation strategies generation. 5 It should be stressed that, influenced by the interaction between the strength allocation strategies changes and the continuous confrontation strength changes, modern confrontations are increasingly more complicated.…”

“…The strength allocation strategies generation problem has been an area of considerable research in the attack‐defense process 1 . For example, designing strength allocation strategies to guarantee high confrontation effectiveness was discussed for forces allocation, 2 weapon targets assignment, 3 firepower allocation 4 . For a conventional confrontation system with a single adversary and no complex factors other than attrition rate, the classic linear programming is available for achieving strength allocation strategies generation 5 .…”

Data Center Resource Allocation Strategy Based on Edge Computing

“…(1) Task allocation with the goal of reducing energy consumption: The expansion of the scale of the data center has led to an increase in the energy consumption of the cloud computing system, and energy consumption has become an inevitable consideration in the task scheduling process. The main way to reduce energy consumption is to minimize the number of computing nodes used and time occupied, shorten task execution time, and improve resource utilization [15][16]. However, energy-saving priority task scheduling is likely to have uneven load or affect system performance.…”