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In shared-memory packet switches, buffer management schemes can improve overall loss performance, as well as fairness, by regulating the sharing of memory among the different output port queues. Of the conventional schemes, static threshold (ST) is simple but does not adapt to changing traffic conditions, while pushout (PO) is highly adaptive but difficult to implement. We propose a novel scheme called dynamic threshold (DT) that combines the simplicity of ST and the adaptivity of PO. The key idea is that the maximum permissible length, for any individual queue at any instant of time, is proportional to the unused buffering in the switch. A queue whose length equals or exceeds the current threshold value may accept no more arrivals. An analysis of the DT algorithm shows that a small amount of buffer space is (intentionally) left unallocated, and that the remaining buffer space becomes equally distributed among the active output queues. We use computer simulation to compare the loss performance of DT, ST, and PO. DT control is shown to be more robust to uncertainties and changes in traffic conditions than ST control.Index Terms-Adaptive thresholds, asynchronous transfer mode, buffer allocation, dynamic thresholds, memory management, pushout, queue length thresholds, shared-memory switch.

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Purpose -Significant advances have been made in the field of healthcare service delivery across the world; however, health coverage particular for the poor and disadvantaged still remains a distant dream in developing world. In large developing countries like India, disparities in access to healthcare are pervasive. Despite recent progress in ensuring improved access to health care in past decade or so, disparities across gender, geography and socioeconomic status continue to persist. Fragmented and scattered health records and lack of integration are some of the primary causes leading to uneven healthcare service delivery. The devised framework is intended to address these challenges. The paper aims to discuss these issues. Design/methodology/approach -In view of such challenges, in this research a Big Data and blockchain anchored integrative healthcare framework is proposed focusing upon providing timely and appropriate healthcare services to every citizen of the country. The framework uses unique identification number (UID) system as formalized and implemented by the Government of India for identification of the patients, their specific case histories and so forth. Findings -The key characteristic of our proposed framework is that it provides easy access to secure, immutable and comprehensive medical records of patients across all treatment centers within the country. The model also ensures security and privacy of the medical records based upon the incorporation of biometric authentication by the patients for access of their records to healthcare providers. Originality/value -A key component of our evolved framework is the Big Data analytics-based framework that seeks to provide structured health data to concerned stakeholders in healthcare services. The model entails all pertinent stakeholders starting from patients to healthcare service providers.