A single-channel single-winner auction model for homogeneous channel allocation in CRNs

Cognitive radio (CR) is a novel intelligent technology which enables opportunistic access to temporarily unused licensed frequency bands. A key functionality of CR is to distribute free channels efficiently amongst Secondary Users (SUs) boosting spectrum usage to assist the escalating wireless applications world wide. In this context, this paper introduces a channel allocation mechanism which enables SUs (CR enabled unlicensed users) to dynamically access unused spectrum bands to fulfill their spectrum needs. We model the channel allocation problem as a sealed-bid single-sided auction which primarily aims at maximizing the overall spectrum utilization. Market based spectrum auctions in CR networks motivate licensed users to participate and lease their under utilized radio resources to gain monetary benefits. Sequential bidding is applied to this model for auctioning homogeneous channels, which reduces communication overhead. Bid submission takes into account two major CR constraints, namely, dynamics in spectrum opportunities and differences in channel availability time, which on incorporation provide disruption free data transmission to the SUs. We reduce resource wastage in this model by performing multiple auction rounds. Application of second price auction determines winning bidders and their respective payments to auctioneer. The design of our auction mechanism is supported with the proofs of truthfulness and individually rational properties. Furthermore, experimental results indicate that our model outperforms an existing auction method. Spectrum utilization values show 22 to 75% improvement in our model with changing number of SUs, and 23 to 93% improvement in our model with changing number of channels.     

Interference and priority aware resource allocation in coexisting WBANs using game models

Wireless body area networks (WBANs) have become an integral part of our health monitoring system. However, the specific challenges offered by a dense co-existence of heterogeneous WBANs have not been properly addressed. The interference between the coexisting WBANs which cause throughput degradation and energy wastage can be mitigated by suitable channel and slot allocations. In this work, a Stackelberg game model with pricing is used for resource scheduling among multi-class WBANs. The access points (APs) act as leaders who decide the prices to be paid by the normal WBAN users for reusing the resources allocated to the critical WBAN users. The normal WBAN users act as followers which use the pricing information and a distributed learning algorithm that guarantees Pareto-optimal solution. As a benchmark for comparison purpose, we propose a centralized resource scheduling which is formulated as an optimization problem where the objective is to maximize system throughput while guaranteeing the quality of service (QoS) requirements of multi-class WBANs. To efficiently solve this problem, a column generation method is proposed. Numerical results are provided to show the efficiency and effectiveness of the proposed game model.     

The resource allocation problem for demand forecasting and performance measurement

We consider a retailer investing in two monitoring functions for unobservable demand and salesperson’s effort. We show that improving effort monitoring is more effective. Moreover, demand monitoring may be less preferable when it becomes relatively cheaper and balancing these two may be worse when they become more complementary.     

Resource allocation in rooted trees for VLSI applications

ABSTRACT

Several optimization problems of modifying the weight of vertices in rooted trees, some of which are special cases of the inverse 1-median problem, are solved. Such problems arise in Very Large Scale Integration (VLSI) design of hardware security circuits, circuit synchronization, and analog-to-digital converters. These problems require assigning costly hardware (demands) to the leaves of rooted trees. One common property of these problems is that a resource allocated to an internal node can be shared by the entire sub-tree emanated at the node. Two types of problems are studied here. (1) A tree node employs an addition operation and the demands at the leaves are obtained by summing the resources allocated to nodes along the root-to-leaf paths. A linear-time bottom-up algorithm is shown to minimize the total resources allocated to tree nodes. (2) A tree’s node employs a multiplication operation and the demands at the leaves are obtained by multiplying the resources allocated to nodes along the root-to-leaf paths. A bottom-up dynamic programming algorithm is shown to minimize the total resources allocated to the tree’s nodes. While the above problems are usually solved by design engineers heuristically, this paper offers optimal solutions that can be easily programmed in CAD tools.     

多组全动型变焦系统新型设计

为了寻找简单的多组全动型变焦系统的解算方法及降低全动型变焦距系统设计时对经验的过分依赖,提出了一种全新的方法来计算系统组元的光焦度分配。以组元之间的间隔为初始量,把组元的运动形式作为自由量,通过计算公式求出满足间隔要求的光焦度分配和组元运动形式。该方法在一定程度上降低了变焦系统光焦度分配的难度,更重要的是,为探寻新的变焦运动方式提供了一种新的思路。在得到系统的光焦度分配之后又推导出一种求解系统组元移动曲线的简单方法。为了验证该方法的可行性,设计了一个四组式全动型变焦系统。所设计系统优化后的光焦度分配值和计算的结果都很接近,并且得到了组元的移动曲线,从而验证了该方法的正确性。     

Safety and waste considerations in donated blood screening

We study an important problem faced by Blood Centers, of selecting screening tests for donated blood to reduce the risk of “transfusion-transmitted infectious diseases” (TTIs), including the human immunodeficiency virus (HIV), hepatitis viruses, human T-cell lymphotropic virus, syphilis, West Nile Virus, and Chagas’ Disease. This decision has a significant impact on health care quality in both developed and developing countries. The budget-constrained decision-maker needs to construct a portfolio of screening tests, from a set of available tests, each with given efficacy (sensitivity and specificity) and cost, to administer to each unit of donated blood so as to minimize the “risk” of a TTI for blood classified as “infection-free.” While doing this, it is critical, for a viable blood system, that the decision-maker does not falsely (i.e., through screening error) discard too much of the infection-free blood (“waste”). We construct mathematical models of this decision problem, considering the various objective functions (minimization of the TTI risk or the weighted TTI risk) and various constraints (on budget and wasted blood) relevant in practice. Our work generates insights on the test selection problem. We show, for example, that a reduction in risk does not necessarily come at the expense of an increase in waste. This underscores the importance of considering these different metrics in decision-making through an optimization-based model. Our work also highlights the importance of generating region-specific testing schemes that explicitly take into account the regional prevalence and co-infection rates, along with the impacts of the infections on the society and individuals.     

Assigning resources and targets to an organization’s activities

Each of an organization’s many activities transforms inputs into outputs. Managing these activities involves allocating input resources for some activities and assigning output targets for others. Making these decisions is especially difficult in the presence of uncertainty. In practice, many organizations address these problems by using a fairly simple “proportional allocation” heuristic (e.g., “allocate to each activity the same percentage increase (or decrease) in its resources or targets”). But proportional allocation does not consider the uncertainty inherent in the ability of each activity to make use of its resources (or meet its targets).     

Optimal response against bioterror attack on airport terminal

We consider a potential bioterror attack on an airport. After the attack is identified, the government is faced with the problem of how to allocate limited emergency resources (human resources, vaccines, etc.) efficiently. The government is assumed to make a one-time resource allocation decision. The optimal allocation problem is discussed and it is shown how available information on the number of infected passengers can be incorporated into the model. Estimation for parameters of the cost function (number of deaths after the epidemic is over) is provided based on known epidemic models. The models proposed in the paper are demonstrated with a case study using real airport data.     

面向产业集群内多供应商的订单分配模型研究

通过分析供应商企业内部生产状况对订单执行的影响,提出一种基于供应商生产负荷率均衡准则的订单分配方法,以生产负荷率来表征供应商企业的生产负荷状况,建立了以生产负荷均衡为目标的订单分配优化模型,并根据适应度值自适应改变交叉算子与变异算子的遗传算法进行求解．仿真计算结果表明：提出的模型和算法能获得满意的解;基于生产负荷均衡化的订单分配策略将促使产业集群内相关成员企业之间,以及同一个企业在不同时间段之间生产负荷的均衡化,有利于供应商群体的持续发展,对产业集群内部制造资源的合理配置有重要意义．