In Wireless Sensor Network (WSN), energy and packet forwarding tendencies of sensor nodes plays a potential role in ensuring a maximum degree of co-operation under data delivery. This quantified level of co-operation signifies the performance of the network in terms of increased throughput, packet delivery rate and decreased delay depending on the data being aggregated and level of control overhead. The performance of a sensor network is highly inclined by the selfish behaving nature of sensor nodes that gets revealed when the residual energy ranges below a bearable level of activeness in packet forwarding. The selfish sensor node needs to be identified in future through reliable forecasting mechanism for improving the lifetime and packet delivery rate. Semi Markov Process Inspired Selfish aware Co-operative Scheme (SMPISCS) is propounded for making an attempt to mitigate selfish nodes for prolonging the lifetime of the network and balancing energy consumptions of the network. SMPISCS model provides a kind of sensor node’s behavior for quantifying and future forecasting the probability with which the node could turn into selfish. Simulation experiments are carried out through Network Simulator 2 and the performance are analyzed based on varying the number of selfish sensor nodes, number of sensor nodes and range of detection threshold.

中文翻译：

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半马尔可夫过程启发了无线传感器网络的自私意识合作方案（SMPISCS）

在无线传感器网络 (WSN) 中，传感器节点的能量和数据包转发趋势在确保数据传输下的最大程度合作方面发挥着潜在作用。这种量化的合作水平表示网络在增加吞吐量、数据包传输率和减少延迟方面的性能，这取决于聚合的数据和控制开销的水平。传感器网络的性能高度倾向于传感器节点的自私行为特性，当剩余能量范围低于数据包转发中可承受的活跃水平时，这种特性就会暴露出来。未来需要通过可靠的预测机制来识别自私传感器节点，以提高寿命和数据包传递率。半马尔可夫过程启发自私意识合作方案（SMPISCS）旨在尝试减轻自私节点，以延长网络的生命周期并平衡网络的能源消耗。SMPISCS 模型提供了一种传感器节点的行为，用于量化和未来预测节点可能变成自私的概率。通过Network Simulator 2进行仿真实验，并根据自私传感器节点数、传感器节点数和检测阈值范围的变化对性能进行分析。SMPISCS 模型提供了一种传感器节点的行为，用于量化和未来预测节点可能变成自私的概率。通过Network Simulator 2进行仿真实验，并根据自私传感器节点数、传感器节点数和检测阈值范围的变化对性能进行分析。SMPISCS 模型提供了一种传感器节点的行为，用于量化和未来预测节点可能变成自私的概率。通过Network Simulator 2进行仿真实验，并根据自私传感器节点数、传感器节点数和检测阈值范围的变化对性能进行分析。