Community Aware Source-Based Incentive Strategy to Mitigate Node Selfishness in Social Internet of Things

The Social Internet of Things (SIoT) enables autonomous nodes to form socially aware communities and collaborate based on trust and interaction history. However, ensuring fair communication and equitable resource allocation remains a challenge due to selfish or selectively cooperative node behavior. This work presents a socially adaptive framework that integrates Virtual Currency (VC), Reputation Scores (RS), and Social Preference (SP) within a community-based incentive model. Once communities are established, Community Heads (CHs) are elected to monitor node behavior, allocate VC based on RS, and enforce cooperation through localized control mechanisms. Nodes earn VC by participating in data relaying tasks. Conversely, nodes that avoid cooperation and fail to accumulate VC may become temporarily ineligible to initiate their own transmissions. In such cases, if a strong social bond exists, a destination node may assist the underfunded source by contributing to the route cost via an adjustment factor. This socially driven support mechanism enhances communication resilience under resource-limited conditions. The framework also supports a recovery mechanism that allows previously selfish nodes to rejoin the network by improving their behavior and regaining RS. Simulations conducted on a MATLAB-based SIoT testbed evaluate the framework against several recent and efficient cooperation models. Compared to the best-performing existing scheme, the proposed mechanism achieves notable improvements in packet delivery ratio (3.9% higher), energy efficiency (0.95% lower consumption), network throughput (11% higher), end-to-end delay (2% lower), and overhead control (9.4% lower). These results confirm that the proposed framework enhances communication efficiency, promotes sustainable cooperation, and mitigates fragmentation caused by non-cooperative behavior in SIoT environments.