Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146

A Game-Theoretic Framework for Energy-Efficient Scheduling and Resource Allocation in Sensor Cloud Systems

2026-10-07T02:32:01-04:00

Sensor cloud systems play a vital role in Internet of Things (IoT) applications by enabling scalable sensing, data processing, and service provisioning; however, they face significant challenges in terms of energy-efficient scheduling and resource allocation. To address these challenges, this paper proposes a game-theoretic framework for energy-efficient scheduling and resource allocation in sensor cloud systems. The interactions between sensor nodes and cloud resources are modeled as a strategic game, where each entity autonomously optimizes its utility by balancing energy consumption, execution latency, and resource usage. An iterative, distributed scheduling algorithm is developed to achieve a stable equilibrium without centralized control.

Extensive simulation-based evaluation demonstrates that the proposed framework significantly reduces overall energy consumption and task completion time while improving resource utilization, throughput, and fairness compared to baseline heuristic approaches. Convergence analysis confirms fast stabilization of the algorithm, and statistical significance tests validate the robustness of the performance gains. The results indicate that the proposed game-theoretic approach provides an effective and scalable solution for energy-efficient scheduling and resource management in sensor cloud environments.

EHARA: A Distributed Energy Harvesting-Aware Routing Algorithm for Sustainable IoT Networks

2026-10-07T02:38:45-04:00

Managing energy wisely and keeping networks running for the long haul are top priorities in IoT setups, especially when devices pull power from their surroundings. This paper unveils the Energy Harvesting-Aware Routing Algorithm (EHARA), a fresh take on routing that fine-tunes energy use, boosts packet delivery, and cuts down delays. EHARA doesn’t stick to rigid paths—it shifts gears based on how much energy nodes are harvesting and storing at any given moment. When pitted against LEACH and EAR in simulations, EHARA comes out ahead with better delivery rates, leaner energy use, and snappier performance. These outcomes underline its knack for stretching network life and sharpening efficiency, positioning it as a solid pick for IoT systems that need to keep going sustainably.

Aware Sensor Cloud Integration Model Using Game Theory for Optimal Scheduling and Resource Allocation

2026-10-07T02:46:17-04:00

The Sensor Cloud Systems (SCS) have become a promising architecture of combining the large sensor networks with cloud computing to provide scalable data processing and intelligent services. Nonetheless, the issue of efficient scheduling of tasks and allocation of resources in SCS is not an easy task because of the limited sensor energy, dynamism of the workloads, and heterogeneity of the cloud resources. In this paper, it is suggested that an energy-conscious sensor cloud integration model is proposed using the game theory to optimally schedule and assign resources. The framework proposed is based on the premise that the sensors and the cloud nodes are rational players who compete and collaborate in order to maximize individual and system-wide goals. An energy-focused payoff function is aimed at decreasing energy usage and increasing the pace of task completion and use of cloud resources. The vast amount of simulations carried out prove that the suggested game theotic model is much better than the current heuristic and traditional scheduling techniques in energy efficiency, performance of the task and the use of resources. The effectiveness and strength of the suggested approach is proved even more by statistical significance analysis and ablation studies. The findings show that the suggested model provides scalable and efficient model to energy conscious scheduling and resource utilization in sensor cloud settings.

Enhancing IoT Network Security and Scalability with Energy Harvesting-Aware Routing

2026-10-07T02:55:39-04:00

One of the most significant challenges confronting the Internet of Things relates to security, scalability, and energy efficiency, particularly considering the rapid expansion of this technology. A proposed solution involves implementing traffic routing that is aware of energy harvesting (TRAER), which has the potential to enhance network lifetimes by utilising locally available energy resources. Numerous established protocols exhibit vulnerabilities to a range of cybersecurity threats that have the potential to incapacitate a network.

Resilient and dependable IoT networks are created by the Secure and Scalable Energy Harvesting-Aware Routing Algorithm (SS-EHARA) weaving together advanced security features with energy-efficient routing. By means of the distribution of decision-making around the network, SSEHARA can choose paths in a safe and fair manner, therefore lowering the danger of attack and the energy consumption.

The results show that the proposed protocol delivers a greater number of packets successfully. It also consumes less energy, and speeds up by minimising latency compared to traditional routing approaches. In larger deployments, it scaled magnificently to accommodate extensive IoT networks.