Game-Theoretic Online Resource Allocation Scheme on Fog Computing for Mobile Multimedia Users

Fog computing is introduced to relieve the problems triggered by the long distance between the cloud and terminal devices. In this paper, considering the mobility of terminal devices represented as mobile multimedia users(MMUs) and the continuity of requests delivered by them, we propose an online resource allocation scheme with respect to deciding the state of servers in fog nodes distributed at different zones on the premise of satisfying the quality of experience(QoE) based on a Stackelberg game. Specifically, a multi-round of a predictably\unpredictably dynamic scheme is derived from a single-round of a static scheme. The optimal allocation schemes are discussed in detail, and related experiments are designed. For simulations, comparing with non-strategy schemes, the performance of the dynamic scheme is better at minimizing the cost used to maintain fog nodes for providing services.

Towards Cache-Assisted Hierarchical Detection for Real-Time Health Data Monitoring in IoHT

Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.

Microsurgery for vestibular schwannoma:analysis of short-term clinical outcome

Background:Total removal of the vestibular schwannoma when preserving the function of the facial nerve is difficult.The objective of the current study was to investigate the short-term clinical outcome of vestibular schwannoma removal via retro-sigmoid approach.Methods:One-hundred consecutive patients diagnosed with vestibular schwannoma were surgically treated between December 2018 and August 2019 in Xuanwu Hospital,Capital Medical University.The clinical classification,surgical position,gross total removal rate,the anatomical and functional preservation rates of facial nerve,and the postoperative complications were retrospectively analyzed.Results:All 100 patients including 34 males and 66 females were operated on via retro-sigmoid approach.According to Koos vestibular schwannoma grading system,18 cases were grade 2,34 cases were grade 3,and 48 cases were grade 4.According to Hannover vestibular schwannoma grading system,5 cases were T2,6 cases were T3a,8 cases were T3b,30 cases were T4a,and 51 cases were T4b.Seventy-three surgeries were performed under lateral position,and 27 cases were operated under semi-sitting position.The gross total removal rate was 90.0%;the anatomic reservation rate of the facial nerve was 96.0%.According to the House-Brackman system,the facial nerve function was grades 1-2 in 78.0%cases,grade 3 in 7.0%cases,and grades 4-5 in 15%cases.For patients with effective hearing before operation,the hearing reservation rate was 19.0%.Two patients(2.0%)developed intracranial hematoma after operation.Conclusion:Most vestibular schwannoma could be completely removed with good postoperative facial nerve function.If total removal of tumor is difficult,we should give priority to the functional preservation of the nerve function.

Playing repeated security games with multiple attacker types:a Q-iteration on a linear programming approach

This paper investigates infinite horizon repeated security games with one defender and multiple attacker types.The incomplete information brings uncertainty of attackers’behaviour for the defender.Under the uncertainty of attackers’behaviours,we take the worst-case analysis to minimise the defender’s regret w.r.t.each attacker type.We wish to keep the regret especially small w.r.t.one attacker type,at the cost of modest additional overhead compared to others.The tradeoff among the objectives requires us to build a Multi-Objective Repeated SecurityGame(MORSG)model.To parameterise the regret Pareto frontier,we combine the different weight vectors with different objectives and build a linear programming approach.By running the Q-iteration procedure on linear programming for each weight vector,the optimal regret Pareto frontier can be computed.We also propose an approximate approach to approximate it.The approximation analysis proves the effectiveness of the approximation approach.