Optimizing Data Gathering in Internet of Things Networks: Discrete Optimization and MEC Offloading for Industrial IoT

Mobile agents are utilized to collect data in IoT networks through ODG-DOMEC, a new approach that utilizes knapsack optimization and mobile technologies to optimize energy savings and data collection. Using a simplified Mobile Agent (MA) format, these agents can retrieve sensor data quickly by integrating processing code and storing list nodes as they move between node sets. This approach uses a two-step decompression algorithm to maximize resource allocation efficiency. That evaluates tasks by considering their desirability, considering energy efficiency benefits and the cost-effectiveness of computing and communication resources, and making informed decision-making regarding offloading to improve system performance. The ODG-DOMEC network model uses the Adhoc On-Demand Distance Vector (AODV) protocol for route formation, which ensures chain freedom and freshness of routing information through sequence numbers. Route requests and responses are initiated by this protocol, which efficiently generates routes and dynamically manages route errors. Data collection technology based on Agent-Knap is focused on a central node that acts as a gateway to the network. Sensors act either as source nodes or as intermediate nodes that respond to data requests from external clients. A regularly modified network topology is employed by the central node to design energy-efficient routes for the mobile agent, which reduces the need for frequent data collection rounds. The ODG-DOMEC process is based on a two-stage offloading algorithm that considers the tasks' desirability at SC/MEC nodes and allocates resources accordingly. The algorithm optimizes for general appeal by considering the EE utility, computing power, and communication capabilities. An experiment with Ubuntu OS software ns3 using C++ and Python for implementation shows the effectiveness of ODG-DOMEC. Compared to current models like RRVD, EVHS, and LCM5, ODG-DOMEC exhibits a lower average ratio, throughput, and the same average packet delay but rather more packet loss due to higher usage of routing resources. The proposed protocol greatly improves data collection efficiency, energy saving, and system performance in IoT networks.

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Published
2025-03-27
DOI
https://doi.org/10.1109/icfts62006.2025.11031896
Primary Topic
IoT and Edge/Fog Computing
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article
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article

Optimizing Data Gathering in Internet of Things Networks: Discrete Optimization and MEC Offloading for Industrial IoT

B. Padmavathi, S Nithish, B S Jayanthan, Pooja Sree H et al.
1 links
IoT and Edge/Fog Computing
article

Optimizing Data Gathering in Internet of Things Networks: Discrete Optimization and MEC Offloading for Industrial IoT

B. Padmavathi, S Nithish, B S Jayanthan, Pooja Sree H, M S Hariharran, E Ramkishore
article en

Abstract

Mobile agents are utilized to collect data in IoT networks through ODG-DOMEC, a new approach that utilizes knapsack optimization and mobile technologies to optimize energy savings and data collection. Using a simplified Mobile Agent (MA) format, these agents can retrieve sensor data quickly by integrating processing code and storing list nodes as they move between node sets. This approach uses a two-step decompression algorithm to maximize resource allocation efficiency. That evaluates tasks by considering their desirability, considering energy efficiency benefits and the cost-effectiveness of computing and communication resources, and making informed decision-making regarding offloading to improve system performance. The ODG-DOMEC network model uses the Adhoc On-Demand Distance Vector (AODV) protocol for route formation, which ensures chain freedom and freshness of routing information through sequence numbers. Route requests and responses are initiated by this protocol, which efficiently generates routes and dynamically manages route errors. Data collection technology based on Agent-Knap is focused on a central node that acts as a gateway to the network. Sensors act either as source nodes or as intermediate nodes that respond to data requests from external clients. A regularly modified network topology is employed by the central node to design energy-efficient routes for the mobile agent, which reduces the need for frequent data collection rounds. The ODG-DOMEC process is based on a two-stage offloading algorithm that considers the tasks' desirability at SC/MEC nodes and allocates resources accordingly. The algorithm optimizes for general appeal by considering the EE utility, computing power, and communication capabilities. An experiment with Ubuntu OS software ns3 using C++ and Python for implementation shows the effectiveness of ODG-DOMEC. Compared to current models like RRVD, EVHS, and LCM5, ODG-DOMEC exhibits a lower average ratio, throughput, and the same average packet delay but rather more packet loss due to higher usage of routing resources. The proposed protocol greatly improves data collection efficiency, energy saving, and system performance in IoT networks.

SRM Institute of Science and Technology (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 85%
IoT and Edge/Fog Computing
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