Exact and approximate equilibria for optimal group network formation

We consider a process called the Group Network Formation Game, which represents the scenario when strategic agents are building a network together. In our game, agents can have extremely varied connectivity requirements, and attempt to satisfy those requirements by purchasing links in the network. We show a variety of results about equilibrium properties in such games, including the fact that the price of stability is 1 when all nodes in the network are owned by players, and that doubling the number of players creates an equilibrium as good as the optimum centralized solution. For the general case, we show the existence of a 2-approximate Nash equilibrium that is as good as the centralized optimum solution, as well as how to compute good approximate equilibria in polynomial time. Our results essentially imply that for a variety of connectivity requirements, giving agents more freedom can paradoxically result in more efficient outcomes.     

Capacity allocation under noncooperative routing

The capacity allocation problem in a network that is to be shared by noncooperative users is considered. Each user decides independently upon its routing strategy so as to optimize its individual performance objective. The operating points of the network are the Nash equilibria of the underlying routing game,. The network designer aims to allocate link capacities, so that the resulting Nash equilibria are efficient, according to some systemwide performance criterion. In general, the solution of such design problems is complex and at times counterintuitive, since adding link capacity might lead to degradation of user performance. For systems of parallel links, we show that such paradoxes do not occur and that the capacity allocation problem has a simple and intuitive optimal solution that coincides with the solution in the single-user case     

The Price of Selfish Routing

We study the problem of routing traffic through a congested network. We focus on the simplest caseof a network consisting of m parallel links. We assume a collection of n network users; each user employs a mixed strategy, which is a probability distribution over links, to control the shipping of its own assigned traffic. Given a capacity for each link specifying the rate at which the link processes traffic, the objective is to route traffic so that the maximum (over all links) latency is minimized. We consider both uniform and arbitrary link capacities. How much decrease in global performace is necessary due to the absence of some central authority to regulate network traffic and implement an optimal assignment of traffic to links? We investigate this fundamental question in the context of Nash equilibria for such a system, where each network user selfishly routes its traffic only on those links available to it that minimize its expected latency cost, given the network congestion caused by the other users. We use the Coordination Ratio, originally defined by Koutsoupias and Papadimitriou, as a measure of the cost of lack of coordination among the users; roughly speaking, the Coordination Ratio is the ratio of the expectation of the maximum (over all links) latency in the worst possible Nash equilibrium, over the least possible maximum latency had global regulation been available. Our chief instrument is a set of combinatorial Minimum Expected Latency Cost Equations, one per user, that characterize the Nash equilibria of this system. These are linear equations in the minimum expected latency costs, involving the user traffics, the link capacities, and the routing pattern determined by the mixed strategies. In turn, we solve these equations in the case of fully mixed strategies, where each user assigns its traffic with a strictly positive probability to every link, to derive the firstexistence and uniqueness results for fully mixed Nash equilibria in this setting. Through a thorough analysisand characterization of fully mixed Nash equilibria, we obtain tight upper bounds of no worse than O(ln n/ln ln n) on the Coordination Ratio for (i) the case of uniform capacities and arbitrary traffics and (ii) the case of arbitrary capacities and identical traffics.     

Joint Optimization of Hardware and Network Costs for Distributed Computer Systems

Multiple combinations of hardware and network components can be selected to design an information technology (IT) infrastructure that satisfies requirements. The professional criterion to deal with these degrees of freedom is cost minimization. However, a scientific approach has been rarely applied to cost minimization, particularly for the joint optimization of hardware and network systems. This paper provides an overall methodology for combining hardware and network designs in a single cost minimization problem for multisite computer systems. Costs are minimized by applying a heuristic optimization approach to a sound decomposition of the problem. We consider most of the design alternatives that are enabled by current hardware and network technologies, including server sizing, localization of mutitier applications, and reuse of legacy systems. The methodology is empirically verified with a database of costs that has also been built as part of this paper. Verifications consider several test cases with different computing and communication requirements. Cost reductions are evaluated by comparing the cost of methodological results with those of architectural solutions that are obtained by applying professional design guidelines. The quality of heuristic optimization results is evaluated through comparison with lower bounds.     

On spectrum sharing games

Efficient spectrum-sharing mechanisms are crucial to alleviate the bandwidth limitation in wireless networks. In this paper, we consider the following question: can free spectrum be shared efficiently? We study this problem in the context of 802.11 or WiFi networks. Each access point (AP) in a WiFi network must be assigned a channel for it to service users. There are only finitely many possible channels that can be assigned. Moreover, neighboring access points must use different channels so as to avoid interference. Currently these channels are assigned by administrators who carefully consider channel conflicts and network loads. Channel conflicts among APs operated by different entities are currently resolved in an ad hoc manner (i.e., not in a coordinated way) or not resolved at all. We view the channel assignment problem as a game, where the players are the service providers and APs are acquired sequentially. We consider the price of anarchy of this game, which is the ratio between the total coverage of the APs in the worst Nash equilibrium of the game and what the total coverage of the APs would be if the channel assignment were done optimally by a central authority. We provide bounds on the price of anarchy depending on assumptions on the underlying network and the type of bargaining allowed between service providers. The key tool in the analysis is the identification of the Nash equilibria with the solutions to a maximal coloring problem in an appropriate graph. We relate the price of anarchy of these games to the approximation factor of local optimization algorithms for the maximum k-colorable subgraph problem. We also study the speed of convergence in these games.     

Competition yields efficiency in load balancing games

We study a nonatomic congestion game with N parallel links, with each link under the control of a profit maximizing provider. Within this ‘load balancing game’, each provider has the freedom to set a price, or toll, for access to the link and seeks to maximize its own profit. Given prices, a Wardrop equilibrium among users is assumed, under which users all choose paths of minimal and identical effective cost. Within this model we have oligopolistic price competition which, in equilibrium, gives rise to situations where neither providers nor users have incentives to adjust their prices or routes, respectively. In this context, we provide new results about the existence and efficiency of oligopolistic equilibria. Our main theorem shows that, when the number of providers is small, oligopolistic equilibria can be extremely inefficient; however as the number of providers N grows, the oligopolistic equilibria become increasingly efficient (at a rate of 1/N) and, as N→∞, the oligopolistic equilibrium matches the socially optimal allocation.     

Optimal design of robust quantitative feedback controllers using random optimization techniques

Quantitative design of robust control systems proposes a transparent and practical controller design methodology for uncertain single-input single-output and multivariable plants. There are several steps involved in the design of such controllers. The main steps involved in the design are template generation, loop shaping and pre-filter design. In the case of multivariable uncertain plants, manipulation of tolerance bounds within the available freedom, for both sequential and non-sequential designs, consideration of template size of next step in sequential design, and the appropriate selection of the nominal transfer function matrices in the equivalent disturbance attenuation design are also crucial steps. In all the quantitative designs, a time-consuming trial-and-error procedure is adapted and a successful compromise between various design requirements is very much dependent on the designer experience and expertise. In this paper, these steps are reformulated in terms of different cost functions, and it is shown that the optimization of these cost functions leads to an optimal design of quantitative controllers, for both single input single output and multivariable plants. This proposes a nonlinear constrained optimization problem that can be easily solved using any of the random optimization techniques. Simulation results are used to show the effectiveness of the proposed method.     

Cooperative network design: A Nash bargaining solution approach

The Network Design problem has received increasing attention in recent years. Previous works have addressed this problem considering almost exclusively networks designed by selfish users, which can be consistently suboptimal. This paper addresses the network design issue using cooperative game theory, which permits to study ways to enforce and sustain cooperation among users. Both the Nash bargaining solution and the Shapley value are widely applicable concepts for solving these games. However, the Shapley value presents several drawbacks in this context.For this reason, we solve the cooperative network design game using the Nash bargaining solution (NBS) concept. More specifically, we extend the NBS approach to the case of multiple players and give an explicit expression for users’ cost allocations. We further provide a distributed algorithm for computing the Nash bargaining solution. Then, we compare the NBS to the Shapley value and the Nash equilibrium solution in several network scenarios, including real ISP topologies, showing its advantages and appealing properties in terms of cost allocation to users and computation time to obtain the solution.Numerical results demonstrate that the proposed Nash bargaining solution approach permits to allocate costs fairly to users in a reasonable computation time, thus representing a very effective framework for the design of efficient and stable networks.     

Welfare Guarantees for Proportional Allocations

According to the proportional allocation mechanism from the network optimization literature, users compete for a divisible resource – such as bandwidth – by submitting bids. The mechanism allocates to each user a fraction of the resource that is proportional to her bid and collects an amount equal to her bid as payment. Since users act as utility-maximizers, this naturally defines a proportional allocation game. Syrgkanis and Tardos (STOC 2013) quantified the inefficiency of equilibria in this game with respect to the social welfare and presented a lower bound of 26.8 % on the price of anarchy over coarse-correlated and Bayes-Nash equilibria in the full and incomplete information settings, respectively. In this paper, we improve this bound to 50 % over both equilibrium concepts. Our analysis is simpler and, furthermore, we argue that it cannot be improved by arguments that do not take the equilibrium structure into account. We also extend it to settings with budget constraints where we show the first constant bound (between 36 and 50 %) on the price of anarchy of the corresponding game with respect to an effective welfare benchmark that takes budgets into account.     

A low-cost communication security scheme of UAV based on multi-round reverse auction model

In recent years, the security of wireless communication has received more and more attention. However, with the increasing requirements for security performance in the process of wireless communication, the cost of improving security also increases. Therefore, how to improve the security of wireless communication while reducing costs has become a serious challenge. Aiming at the security problems in the UAV-assisted wireless communication link based on the premise of low cost and high profit, this paper studies how to motivate non-offloading users to send jamming power to interfere with eavesdropping UAVs, so efficiently and economically to improve the security performance of wireless communication link. Firstly, the relationship between the security performance of the communication link and the interference power is revealed through the theoretical model. Then, we propose a scenario consisting of a legitimate UAV, a ground user group, and an eavesdrop UAV. In this scenario, we divide the ground users into offloading users and non-offloading users. At the same time, the cost functions for offloading users and utility functions for non-offloading users are defined, and non-offloading users are encouraged to help to offload users unload data safely to a legitimate UAV by obtaining rewards for offloading users. Considering the selfishness of users, a reverse auction algorithm based on multi-user groups is proposed to achieve the optimal mapping between non-offloading users and offloading users. Finally, the effectiveness of the proposed scheme is verified by a large number of simulations. The research results show that the scheme innovative designs a method for users to cooperate to interfere with eavesdroppers, which can reduce costs and improve utility while maximizing the improvement of wireless communication link security.     

Reliable Communication Networks for Smart Grid Transmission Systems

In this paper, we discuss the communications reliability requirements posed by the smart power grid with a focus on communications in support of wide area situational awareness. Implementation of wide area situational awareness relies on both transmission substation networks and wide area optical networks. We study the reliability of a sample communications network of the California Power Grid and find that its reliability falls short of proposed requirements. To overcome this issue, we consider the problem of designing the substation network and the wide area network to meet the reliability requirements while minimizing the network cost. For the wide area network design problem, we propose two alternate design approaches, namely: (1) following the power lines and (2) a mesh based design interconnecting the nodes. For the first approach we develop two greedy iterative heuristics and a heuristic integer linear programming (H-ILP) model using minimum cut-sets for network reliability optimization. The greedy iterative algorithms outperform the H-ILP approach in terms of cost, but require a larger amount of computing resources. Both proposed models are in fact complementary and thus provide a framework to optimize the reliability of smart grid communications networks restricted to following the power lines. In the second approach a greenfield mesh network method is proposed based on starting with a minimum spanning tree which is then augmented through a greedy heuristic into a mesh. Comparative numerical results show that the reliable mesh design has advantages in terms of the number of links and total link distance needed.     

Routing and resource optimization in service overlay networks

Service Overlay Networks (SONs) create a virtual topology on top of the Internet and provide end-to-end quality of service guarantees without requiring support by the underlying network.The optimization of the resources utilized by an SON is a fundamental issue for an overlay operator owing to the costs involved and the need to satisfy user requirements. Careful decisions are necessary to provide enough capacity to overlay links, to route traffic, to assign users to access nodes and to deploy overlay nodes.In this paper, we propose two mathematical programming models for the user assignment problem, the traffic routing optimization and the dimensioning of the capacity reserved on overlay links in SONs. The first model minimizes the SON installation cost while providing full access to all users. The second model maximizes the SON profit by selecting which users to serve, based on the expected gain, and taking into consideration budget constraints of the SON operator. Moreover, we extend these models to include the optimization of the number and position of overlay nodes.We provide the optimal solutions of the proposed SON design formulations on a set of realistic-size instances and discuss the effect of different parameters on the characteristics of the planned networks. Numerical results show that the proposed approach is able to solve the problem to the optimum even for large-scale networks.     

Network Formation: Bilateral Contracting and Myopic Dynamics

We consider a network formation game where nodes wish to send traffic to each other. Nodes contract bilaterally with each other to form bidirectional communication links; once the network is formed, traffic is routed along shortest paths (if possible). Cost is incurred to a node from four sources: 1) routing traffic; 2) maintaining links to other nodes; 3) disconnection from destinations the node wishes to reach; and 4) payments made to other nodes. We assume that a network is stable if no single node wishes to unilaterally deviate, and no pair of nodes can profitably deviate together (a variation on the notion of pairwise stability). We study such a game under a form of myopic best response dynamics. In choosing their action, nodes optimize their single period payoff only. We characterize a simple set of assumptions under which these dynamics converge to a stable network; we also characterize an important special case, where the dynamics converge to a star centered at a node with minimum cost for routing traffic. In this sense, our dynamics naturally select an efficient equilibrium.     

Layered shape grammars

In this article we propose a computer-aided conceptual design system to assist modelling at the early stages of design. More precisely, we address the problem of providing the designer with design alternatives that can be used as starting points of the design process. To guide the generation of such alternatives according to a given set of design requirements, the designer can express both visual knowledge in the form of basic geometric transformation rules, and also logic constraints that guide the modelling process. Our approach is based on the formalism of shape grammars, and supplements the basic algorithms with procedures that integrate logic design constraints and goals. Additionally, we introduce a layered scheme for shape grammars that can greatly reduce the computational cost of shape generation. Shape grammars, constraints, goals and layers can be handled through a graphic environment. We illustrate the functionalities of ShaDe through two use cases taken from the architectural design and video games domains, and also evaluate the performance of the system.     

Adaptive design optimization of wireless sensor networks using genetic algorithms

We present a multi-objective optimization methodology for self-organizing, adaptive wireless sensor network design and energy management, taking into consideration application-specific requirements, communication constraints and energy-conservation characteristics. A precision agriculture application of sensor networks is used as an example. We use genetic algorithms as the optimization tool of the developed system and an appropriate fitness function is developed to incorporate many aspects of network performance. The design characteristics optimized by the genetic algorithm system include the status of sensor nodes (whether they are active or inactive), network clustering with the choice of appropriate clusterheads and finally the choice between two signal ranges for the simple sensor nodes. We show that optimal sensor network designs constructed by the genetic algorithm system satisfy all application-specific requirements, fulfill the existent connectivity constraints and incorporate energy-conservation characteristics. Energy management is optimized to guarantee maximum life span of the network without lack of the network characteristics that are required by the specific application.     

The structure and complexity of Nash equilibria for a selfish routing game

In this work, we study the combinatorial structure and the computational complexity of Nash equilibria for a certain game that models selfish routing over a network consisting of m$m$ parallel links. We assume a collection of n$n$ users, each employing a mixed strategy, which is a probability distribution over links, to control the routing of her own traffic. In a Nash equilibrium, each user selfishly routes her traffic on those links that minimize her expected latency cost, given the network congestion caused by the other users. The social cost of a Nash equilibrium is the expectation, over all random choices of the users, of the maximum, over all links, latency through a link.     

面向多租户网络资源分配的博弈优化策略

为了应对5G及未来网络中用户间差异化的服务需求,改善多租户网络切片资源利用率低和部署成本高的问题,提出一种基于多租户网络资源分配的博弈优化策略。在多租户网络中,网络切片租户（NSTs）租用基础设施提供商基站的无线频谱资源,将接入服务切片构建为网络切片即服务,为用户提供网络接入服务。将NSTs和用户的关系建模为一个多主多从的Stackelberg博弈,引入切片流行度和服务命中率指标,建立博弈双方的策略空间和收益函数,并证明NSTs的切片订购策略存在唯一的纳什均衡。通过逆向归纳法分析博弈模型,提出一种分布式迭代算法求得用户的最优吞吐量需求以及NSTs的最优切片定价。仿真结果表明,与传统考虑切片资源分配的优化策略对比,基于多租户网络资源分配的博弈优化策略能够有效提高资源利用率和用户满意度,并降低切片部署能耗,较好地实现频谱带宽资源的合理分配。     

Meeting security and user behavior requirements in Grid scheduling

Most of current research in Grid computing is still focused on the improvement of the performance of Grid schedulers. However, unlike traditional scheduling, in Grid systems there are other important requirements to be taken into account. One such a requirement is the secure scheduling, namely achieving an efficient allocation of tasks to reasonable trustful resources. In this paper we formalize the Grid scheduling problem as a non-cooperative non-zero sum game of the Grid users in order to address the security requirements. The premise of this model is that in a large-scale Grid, the cooperation among all users in the system is unlikely to happen. The users’ cost of playing the game is interpreted as a total cost of the secure job execution in Grid. The game cost function is minimized, at global (Grid) and local (users) levels, by using four genetic-based hybrid meta-heuristics. We have evaluated the proposed model under the heterogeneity, the large-scale and dynamics conditions using a Grid simulator. The relative performance of four hybrid schedulers is measured by the makespan and flowtime metrics. The obtained results suggested that it is more resilient for the Grid users to pay some additional scheduling cost, due to verification of the security conditions, instead of taking the risk of assigning their tasks to unreliable resources.     

Competitive routing in networks with polynomial costs

We study a class of noncooperative general topology networks shared by N users. Each user has a given flow which it has to ship from a source to a destination. We consider a class of polynomial link cost functions adopted originally in the context of road traffic modeling, and show that these costs have appealing properties that lead to predictable and efficient network flows. In particular, we show that the Nash equilibrium is unique, and is moreover efficient. These properties make the polynomial cost structure attractive for traffic regulation and link pricing in telecommunication networks. We finally discuss the computation of the equilibrium in the special case of the affine cost structure for a topology of parallel links