In recent years, wireless communication systems have experienced tremendous growth in data traffic. Many capacity-enhancing techniques are applied to elevate the gap between the amount of traffic and network capacity,...In recent years, wireless communication systems have experienced tremendous growth in data traffic. Many capacity-enhancing techniques are applied to elevate the gap between the amount of traffic and network capacity, and more solutions are required to minimize the gap. Traffic allocation among multiple networks is regarded as one of the most effective methods to solve the problem. However, current studies are unable to derive the quantity of traffic that each network should carry. An intelligent traffic allocation algorithm for multiple networks is proposed to obtain the optimal traffic distribution. Multiple factors affecting traffic distribution are considered in the proposed algorithm, such as network coverage, network cost, user habit, service types, network capacity and terminals. Using evaluations, we proved that the proposed algorithm enables a lower network cost than load balancing schemes. A case study of strategy rmldng for a 2G system refarming is presented to further illustrate the applicability of the proposed algorithm. We demonstrated that the new algorithm could be applied in strategy rmldng for telecommunication operators.展开更多
This paper considers a buyer＇s procuring strategy where the buyer purchases products from a supplier in order to minimize his total cost. Assume that the customer arrivals follow a Poisson process, a base-stock polic...This paper considers a buyer＇s procuring strategy where the buyer purchases products from a supplier in order to minimize his total cost. Assume that the customer arrivals follow a Poisson process, a base-stock policy is implemented by the buyer, and the supplier will afford partial operating cost incurred by the buyer; The cost shared by the buyer includes procuring cost and some operating cost; The supplier does not hold the inventory and her production time is exponentially distributed. The objective of the supplier is to maximize her profit. The buyer designs a contract to minimize his total expected cost. Two different cases are considered： One potential supplier and many competing suppliers. The optimal control approaches are used to design the buyer＇s optimal mechanism and some simple procurement mechanisms are presented.展开更多
基金supported partially by the National Science and Technology Major Projects under Grants No. 2012ZX03006003-005,No. 2012ZX03003006-002,and No. 2010ZX03002-008-01
文摘In recent years, wireless communication systems have experienced tremendous growth in data traffic. Many capacity-enhancing techniques are applied to elevate the gap between the amount of traffic and network capacity, and more solutions are required to minimize the gap. Traffic allocation among multiple networks is regarded as one of the most effective methods to solve the problem. However, current studies are unable to derive the quantity of traffic that each network should carry. An intelligent traffic allocation algorithm for multiple networks is proposed to obtain the optimal traffic distribution. Multiple factors affecting traffic distribution are considered in the proposed algorithm, such as network coverage, network cost, user habit, service types, network capacity and terminals. Using evaluations, we proved that the proposed algorithm enables a lower network cost than load balancing schemes. A case study of strategy rmldng for a 2G system refarming is presented to further illustrate the applicability of the proposed algorithm. We demonstrated that the new algorithm could be applied in strategy rmldng for telecommunication operators.
文摘This paper considers a buyer＇s procuring strategy where the buyer purchases products from a supplier in order to minimize his total cost. Assume that the customer arrivals follow a Poisson process, a base-stock policy is implemented by the buyer, and the supplier will afford partial operating cost incurred by the buyer; The cost shared by the buyer includes procuring cost and some operating cost; The supplier does not hold the inventory and her production time is exponentially distributed. The objective of the supplier is to maximize her profit. The buyer designs a contract to minimize his total expected cost. Two different cases are considered： One potential supplier and many competing suppliers. The optimal control approaches are used to design the buyer＇s optimal mechanism and some simple procurement mechanisms are presented.
