Simulation and Optimization of Task Offloading in Mine Edge Computing for Low-concurrency Devices

doi:10.16182/j.issn1004731x.joss.25-0840

Abstract

Abstract:

With the advancement of mine intelligence, task offloading technology has become a core technology of mine edge computing (MEC). For edge computing systems deployed with mine low-concurrency devices (MLCD), a discrete-event simulation model for MEC task offloading oriented to MLCD was constructed to solve the collaborative optimization problem of task processing latency and load balancing of mine edge servers (MES). By dynamically simulating the queuing, transmission, and computation processes of tasks, the objective of minimizing task processing latency was achieved. An improved evolutionary algorithm, ISBT-EA, was proposed, which integrated a task-characteristic-driven initialization strategy and local search operators, enhancing the efficiency of strategy optimization in simulation-based evaluation. The simulation results show that, compared with traditional methods, ISBT-EA reduces the average latency by at least 4.77%, providing a reliable simulation and optimization solution for addressing latency optimization and load balancing problems in MLCD scenarios.

Key words: mine edge computing, mine low-concurrency device, task offloading, evolutionary algorithm, latency optimization

CLC Number:

TP391.9

Guo Zhaolu, Liu Qianhui. Simulation and Optimization of Task Offloading in Mine Edge Computing for Low-concurrency Devices[J]. Journal of System Simulation, 2026, 38(7): 2091-2104.

Figures/Tables 6

Fig. 1

Fig. 2

Table 1

Simulation parameter settings

参数	取值
任务数量 $I$	50~300
任务 $t i$ 的数据量 $s i$ /MB	[1, 25]
任务 $t i$ 的计算量 $c i$ /cycles	[100, 500]
任务 $t i$ 所属设备编号 $u i$	1~T
MLCD数量 $R$	5~15
MLCD的并发数 $q$	3~6
$M M L C D, k$ 计算能力 $F k$ /(cycle/s)	[300, 600]
最大运行停滞次数 $c c o u n t, m a x$	3
$β$	$2 × 107$
$w r a t i o$	0.15
MES负载均衡最大容忍度 $σ m a x$	0.3
$M E S, l$ 的计算能力 $f l$ /(cycle/s)	[1 000, 1 500]
MES数量 $L$	5~10
传输功率 $P u p l o a d$	2~5
通信带宽 $B$	10
背景噪声功率 $ω ¯$	0.1
信道增益 $g c$	1
$α$	1
$χ$	$10 - 3$
$N P$	30

Table 1

Table 2

Table 3

Fig. 3

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实例	ISBT-EA-R	ISBT-EA-A	ISBT-EA-B	ISBT-EA
T1 (50)	3.007 0	2.843 0	2.946 0	2.829 0
T1 (50)	0.065 0 (-)	0.025 2 (-)	0.053 3 (-)	0.029 3
T2 (100)	5.825 3	5.368 2	5.719 4	5.323 1
T2 (100)	0.111 1 (-)	0.055 4 (-)	0.084 5 (-)	0.039 6
T3 (150)	9.177 7	8.037 8	9.046 2	7.916 2
T3 (150)	0.167 4 (-)	0.115 2 (-)	0.158 7 (-)	0.081 0
T4 (200)	12.384 8	10.721 5	12.228 9	10.597 7
T4 (200)	0.183 8 (-)	0.129 0 (-)	0.205 1 (-)	0.124 5
T5 (250)	16.965 4	15.440 9	16.718 4	15.082 7
T5 (250)	0.310 1 (-)	0.281 8 (-)	0.351 0 (-)	0.318 5
T6 (300)	19.243 1	16.859 5	19.099 1	16.579 8
T6 (300)	0.339 7 (-)	0.223 2 (-)	0.287 1 (-)	0.249 3
+/-/=	0/6/0	0/6/0	0/6/0

实例	ISBT-EA	ABC	ACO	DE	PSO
T1 (50)	2.829 0	2.835 8	2.979 0	3.043 5	2.907 6
T1 (50)	0.029 3	0.032 1 (-)	0.032 7 (-)	0.055 4 (-)	0.088 4 (-)
T2 (100)	5.323 1	5.497 9	5.670 4	5.901 4	5.343 4
T2 (100)	0.039 6	0.063 9 (-)	0.073 7 (-)	0.100 4 (-)	0.132 4 (-)
T3 (150)	7.916 2	8.841 2	8.849 5	9.238 7	8.445 6
T3 (150)	0.081 0	0.102 6 (-)	0.119 1 (-)	0.175 6 (-)	0.241 1 (-)
T4 (200)	10.597 7	11.851 8	12.033 3	12.425 3	11.439 6
T4 (200)	0.124 5	0.152 1 (-)	0.141 0 (-)	0.222 6 (-)	0.390 5 (-)
T5 (250)	15.082 7	16.276 7	16.549 4	17.027 1	15.444 5
T5 (250)	0.318 5	0.273 4 (-)	0.195 9 (-)	0.350 6 (-)	0.528 4 (-)
T6 (300)	16.579 8	18.736 7	18.911 5	19.304 9	18.332 2
T6 (300)	0.249 3	0.274 4 (-)	0.242 0 (-)	0.306 6 (-)	0.653 9 (-)
+/-/=		0/6/0	0/6/0	0/6/0	0/6/0