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 u...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.展开更多
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 uncertain...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.展开更多
基金supported by the National Natural Science Foundation of China under grant No. 61501080, 61572095, 61871064, and 61877007
文摘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.
基金The paper is supported by theNationalNatural Science Foundation of China[grant nos 61572095,61877007].
文摘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.
